Why Get Financial Data From Intrinio?

Intrinio's mission is to make financial data affordable and accessible. If you need financial data, our hope is that you are looking for data that is inexpensive and easy to work with because we are spending all of our time building a platform that meets those requirements. This article explains why we believe affordability and accessibility are critical and the unique features of the Intrinio platform that make it cheap and easy to get the data you need.

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What is an API and Why Should Your Business Care?

API stands for application programming interface and if that sounds like gibberish, you are already being left in the dust by the competition. APIs allow developers to build connections between their own applications and other applications, enabling data sources to interact. In the past, businesses that wanted their software systems to interact had to purchase expensive ERP software and implement cumbersome, time consuming solutions.

APIs make it easy and cheap for business tools to "talk" to each other, powering data driven decision making in real time. Businesses that use APIs will thrive, those that don't will be too slow to keep up.

What exactly is an API?

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Sector & Industry API – [Instant Access via SIC Code]

Accessing Intrinio data for individual US equities is affordable, easy and extremely valuable when analyzing investments. What can be even more powerful at times, is accessing that data on an industry-wide or sector-wide level. We developed a Sector & Industry API so investors and developers can instantly access data to generate lucrative insights for different segments of the market. You can check out the data feed here.

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Standardized XBRL Financial Data – [Why it matters and How We Fix It]

If you want to find out what Tesla's market capitalization was over the past ten years, and you want to access that data in Excel, it seems like it should be cheap and straightforward to do so. If you're a developer and you're looking to get the Oil Industry's performance charted on your website, it seems like accessing that data should be a no brainer. Thanks to a technology called XBRL, this has become easier over the past several years.

The truth is - there is a whole world operating behind the scenes of financial data feeds. There are professionals, companies, industries, governmental bodies and hundreds of thousands of employees working to deliver you your historical market cap.

Outside of the Intrinio Fintech Marketplace there aren't many options for accessing this data. The options that do exist are prohibitively expensive for two reasons.

  1. Financial data in its raw form requires normalization.
  2. Current normalization methods are manual and outdated

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Analyst Estimates From Zacks In the Intrinio Fintech Marketplace

The Intrinio Fintech Marketplace was designed to make financial data affordable and easy to access. We are pleased to announce the expansion of that vision with the addition of a new data partner, Zacks, whose analyst estimates data will now be available in the marketplace.

Zacks forward and historical estimates of both EPS and revenue are a trusted source of information in the investment community. Intrinio's platform features disruptively affordable data feeds accessible for financial analysts in Excel and fintech developers via an API. Pairing Zacks analyst estimates with Intrinio's platform will provide Intrinio's users with a crucial data source and make it easier than ever to access Zacks data.

This article explains which Zacks data feeds will be available, how much they cost, and how to access them in Excel or API formats.

 

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Getting Started With Intrinio

Intrinio is on a mission to provide financial data in a way that is flexible and affordable so that fintech developers can build the next generation of game changing applications for investors. Our ecosystem includes the APIs developers need to build those applications as well as the applications themselves, allowing developers and investors to come together in the same marketplace.

What follows is a quick introduction to the resources and steps both types of users will need to take to get started with Intrinio.

What is the Intrinio Fintech Marketplace?

Cutting through the marketing jargon here is what Intrinio provides. We provide a bunch of different data feeds that allow users to access many different kinds of financial data. The marketplace lets users sign up for the data they need and the pricing plan that fits their needs.

Once a user has access to data, they can analyze the data in an application like Excel or they can build their own application like Vantage for other users to use. These applications, which rely on data from the marketplace, are also available for users in the marketplace.

The idea is to provide the data users need as well as lots of new applications to make that data even easier to analyze. You can browse the apps and browse the data feeds Intrinio provides and see the prices, terms, and limits for those products in the Marketplace.

Signing Up

Signing up for Intrinio is free and easy- all we require is an email and a password, no credit card, no spam. You can signup at www.intrinio.com/login. This will give you access to your account page where you will see your subscriptions as well as three tutorials for accessing Intrinio data through an Excel add-in, a Google Sheets add-on, or directly through an API.

The Account Page

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Intrinio Stock Screener for Excel Online

We've been hard at work with Microsoft...

Building you the World's First Stock Screener Within the Excel Ecosystem!

Team Intrinio wanted to build a tool leveraging our data that would enable our users and Excel users around the world to instantly screen US equities - without ever having to leave the Excel platform.

We're pleased to have worked alongside Microsoft to deliver our customers with an innovative tool that will help save you time and provide better insights. We constantly strive to leverage Intrinio data into new tools to enhance your experience.

This stock screener is the first of it's kind - no longer do you need to tinker with outdated and inflexible screeners on the web, only to have to export to Excel and re-organize the outputs.

 

Read More

Excel 2016 For Mac – Functionality Released

Intrinio Excel add-in Now Supports Excel 2016 for Mac

We know we're late on this one - but we've been busy bees!

The Intrinio Data Feed can now be accessed via Microsoft Excel 2016 on Mac operating systems.

 

Intrinio offers the most affordable financial data feed on the market, and it's the only data feed compatible on both Mac and Windows operating systems. We strive for unprecidented flexibility, cross-platform compatibility, instant customer support, and prices that make you do a double take.

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Efficiency Upgrade: Dimensional Calls

We want to keep our customers looking their best.

So, we made an upgrade to help you be more efficient.

Introducing: Dimensional Calls

Your life just got a whole lot easier.

 

This function is built to help developers make more efficient use of our API, but it doesn't work with our Excel add-in or Google Sheets add-on.

 

Read More

Sector & Industry Data Joins the Squad

Intrinio Now Offers Aggregated Sector & Industry Data

We've unleashed the power of aggregating industry statistics so that you can efficiently perform top down analysis.

This data is based on company reported Standard Industrial Classification numbers. 

These indices are updated monthly, reflecting all newly reported filings. 

 

An Intrinio SIC Index is created with the following format: $SIC.XXXX.

Example: $SIC.1380

-> returns aggregated industry statistics for the Oil & Gas Field Services

Read More

3 Ways To Access the Most Affordable Financial Data on the Market

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started.

We're always available via 24/7 chat on our website – just click the green button in the bottom right hand corner of the page for support. 

Follow us on Twitter and LinkedIn and Like us on Facebook to stay up to date.

Historical Data: We Gave Data Point a Makeover

Historical Data: Query any data point as a historical time series.

The same data points, but now with functionality that lets you slice and dice the information historically.

Now, in addition to analyzing our wealth of financial data, you can analyze historical time series data to uncover trends, analyze patterns, chart, graph and display historical data, and project the future.

Combined with the rest of our data offering (stock prices, fundamentals, metrics, ratios, earnings estimates, news, economic data etc.) -> Intrinio users have comprehensive access to the information they need to make informed, intelligent investment decisions - without breaking the bank.

Read More

Economic Data Added to Intrinio API

We're pleased to announce that Intrinio now offers full access to over 200,000 Economic Data Series through our API, Excel add-in and Google Sheets add-on

1,000 of the most popular series are listed for you in our documentation.

The full list of 200,000 different series is available on the Federal Reserve Economic Data Website.

 

Now, in addition to analyzing our wealth of financial data, you can analyze thousands of economic data points to help you understand the economy on different levels.

You can now use Intrinio to pull in economic data to compare a company’s performance to various measures of growth or production.  For example, you can see that mining equipment purchases are down, which means production growth may stall in the future years.  To understand that correlation, you might build statistical analyses based on historical data for the company relative to the historical economic data.

Combined with the rest of our data offering (stock prices, fundamentals, metrics, ratios, earnings estimates, news, etc.) -> Intrinio users have comprehensive access to the information they need to make informed, intelligent investment decisions - without breaking the bank.

Each time we add new data sets to our data feed there is no additional charge. This means that as we grow and continue to annouce new offerings, the value of your access increases continually. We strive to provide you with a wealth of knowledge, data and insight.

Example Economic Data Series

  • Gross Domestic Product
  • Velocity of M2 Money Stock
  • Civilian Unemployment Rate
  • Effective Federal Funds Rate
  • U.S./EURO Foreign Exchange Rate
  • University of Michigan: Consumer Sentiment
  • BofA Merrill Lynch US Corporate BBB Effective Yield
  • Gold Fixing Price 10:30 A.M. (London time) in London Bullion Market, based in U.S. Dollars
  • Real Retail and Food Services Sales
  • AND 199,991 MORE.......

Functionality

The index symbol is the same as the Series ID on FRED, but you put a "$" before the Series ID for our API to recognize it.

For equity data, we call the company like this -> "AAPL"

For Federal Reserve Economic Data Series, we call the series like this -> "$GDPC96"

(this returns Real Gross Domestic Product, 3 Decimal)

Below is an example of the return values when you use the API to query historical quarterly GDP.

Intrinio API Economic Data Series return values in the browser

Remember, you can search for the 1,000 most popular Series IDs in our documentation, or search through the full 200,000 on the Federal Reserve Economic Data website.

 

Enjoy our new Economic Data feature! If you have questions, comments or suggestions, please reach out to our support team by clicking the green button in the bottom right hand corner of your screen at intrinio.com

Happy 2016!!!

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started.

We're always available via 24/7 chat on our website - just click the green button in the bottom right hand corner of the page for support. 

Follow us on Twitter and LinkedIn and Like us on Facebook to stay up to date.

Stock News Feed Added to Intrinio API

Introducing: Stock News

Intrinio now enables its users to pull in stock news on the companies they follow.

By entering in one simple formula, our users can return the most recent news stories for every company in our coverage (any US publicly traded company).

This exciting expansion of our data set enables you to stay up to date with trending topics and key events that are crucial to your investments, your portfolio, your app, your website, your blog or your customers.

Check out the full documentation to learn more.

Combined with the rest of our data offering (stock prices, fundamentals, metrics, ratios, earnings estimates, economic data, etc.) -> Intrinio users have comprehensive access to the information they need to make informed, intelligent investment decisions - without breaking the bank.

Each time we add new data sets to our data feed there is no additional charge. This means that as we grow and continue to annouce new offerings, the value of your access increases continually. We strive to provide you with a wealth of knowledge, data and insight.

Parameters

  • ticker – the stock market ticker symbol associated with the company's common stock.  If the company is foreign, use the stock exchange code, followed by a colon, then the ticker.

Return Values

  • title – the title of the article
  • publication_date – the date the article was published
  • url – the hyperlink to the article
  • summary – a brief summary of the article

Example

Below is an example request you can make to the Intrinio API to return the most recent news stories for Apple, Inc. (AAPL).

Intrinio API: /news returns the most recent news stories for a company.

API URI: https://www.intrinio.com/api
GET: /news?ticker=AAPL
FULL URL: https://www.intrinio.com/api/news?ticker=AAPL

The image below shows the API request above and the values that are returned:

Intrinio API Stock News Return Value in the Browser

Below is an example request you can make in Excel using the Intrinio Excel add-in or in Google Sheets using the Intrinio add-on to return the most recent news stories for Apple, Inc. (AAPL).

=IntrinioNews(ticker,item,sequence)

Item: Title, URL, publication_date, summary

Sequence: The number of the article from the list

=IntrinioNews("AAPL","summary",4)

Returning Multiple Companies

Using the API, you can query stock news data for up to 10 tickers at one time, separating each with a comma.

Using the API:

FULL URL: https://www.intrinio.com/api/news?ticker=AAPL,AMZN

Using Excel or Google Sheets:
=IntrinioNews("AAPL,AMZN","title",0)

Remember, full documentation is available here!

 

Enjoy our new News feature! If you have questions, comments or suggestions, please reach out to our support team by clicking the green button in the bottom right hand corner at intrinio.com

Happy 2016!!!

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started.

We're always available via 24/7 chat on our website - just click the green button in the bottom right hand corner of the page for support. 

Follow us on Twitter and LinkedIn and Like us on Facebook to stay up to date.

Weekly Valuation Feature: Can Ford Make the Transition to Vehicles as a Service (VAS)?

Each week, we'll be featuring a Report from Valuation on our Blog.

What is Valuation?

Valuation is an innovative engine online built for valuing public comapnies – and it's free. Our Users can simply type in a ticker and they'll instantly see a "default" intrinsic value for the stock. The platform is flexible, allowing you to easily click and drag your assumptions and the main drivers of the model up and down. The engine is perfect for scenario and sensitivity testing, helping you to quickly gauge whether a company is over or undervalued. You can save all of your Valuations. Currently, Valuation is structured around the Discounted Cash Flow method. Stay tuned, because we're going to be building out additional methodology and features soon.

valuation

What is a Report?

We've built a collaborative platform called Exchange. It's the only platform for exchanging investment analyses that is both qualitative and quantitiative, requiring the actual numbers to back up your conclusions. Users can "Create a Report" and choose one of their Valuations to associate it with. They can then add a written, qualitative analysis to accompany their quantitative valuation, and attach any additional files that they want. These Reports are posted to our Exchange where our users can comment, discuss, and collaborate. Visit Exchange to acquire Reports and add them to your "Library"

Report

This Week's Feature: "Can Ford Make the Transition to Vehicles as a Service (VAS)?"

Submitted by: Andrew Carpenter

I've owned Ford in a retirement account for some time. Next month it looks like Ford will announce its traditional dividend increase as well as a driverless car partnership with Google. That made me want to consider getting some of my taxable portfolio behind the stock. The lack of a recent big downturn for Ford makes me cautious about the company's ability to create a big ROI. I doubled down on IBM and STX instead. My biggest concern with Ford is that I suspect, in the long run, driverless cars will decrease the demand for cars overall.

Beta: Ford has a nice low beta of 1.17. This lack of variability reminds me of Ford's ability to not take a bailout back in the great recession- this is a company that knows about stability and I think that contributes to their brand but hinders their ability to adapt.

Dividend: At over 4% with enough free cash flow to cover payouts and an expected hike in January, Ford is a tempting dividend river to add to feed into my dividend cannon. I think of my monthly dividends as an income stream I can point at things- usually I point them at stocks but someday I want to point them at my expenses to cover my writing habit. Ford certainly qualifies for my ideal range of 3%-6%.

Price: Ford traded about 7% lower than its current price in August and later in September however it has fallen about 14% from its yearly highs in October and last spring. Forgive the roughness of these estimates, I'm really just trying to determine if any surprises have been priced in. Based on its middle of the road price for the year I wouldn't qualify this as an opportunistic time to buy.

P/E ratio: For has a P/E ratio of about 11.72 which makes sense for an old time company in such a competitive industry. I like that multiple, but I don't love it. See my insight into the future of the industry below.

Valuation: The base case valuation for Ford based on Wall Street consensus estimates shows a huge margin of safety score of 71 with an intrinsic value of $48.18. This is one case where I won't trust the algorithmic DCF that Intrinio so kindly calculates for me to make my job easier but it does provide some insight into the fundamentals of Ford- this is a strong company with a healthy balance sheet.

Insight: Here is where my concern with Ford is preventing me from investing more. Imagine the world that Ford's CEO predicted- driverless cars in 5 years. With Google (hopefully) throwing its brains behind Ford, it seems like they will get a jump on that dream. But what will this mean? Someone, maybe Ford, will win the race for government approval. That will be a huge moment for that company and if I had to pick a horse I don't see why Ford, with its strong cash flows to invest, shouldn't win, especially if it partners with Google. In that best case scenario, what would happen for Ford? It would be an initial boom- everyone who could get one would want one, and those babies would actually be worth putting up some serious cash for. 

But then what? Here is my prediction- cars will become like apartments. People with cash will buy them as assets, not liabilities, and will rent them out by the hour. Companies like Uber will become the norm as cars become an operating expense, rather than a capital expense, for most people. In general, this will mean a lot fewer cars will be sold because cars will not be sitting idol. When you aren't driving it, someone else is renting it from you. You've heard as software as a service- can Ford make that transition as well?

Maybe yes, maybe no, but the industry is about to be disrupted in a big way. That creates a lot of opportunity but also a lot of risk. I don't buy automakers because I'm looking for big risks, I'd rather save some cash for a down payment on a driverless car I can rent out. 

______________________________________________________________________________________________________________________________________________

About my strategy:

I use Intrinio’s excel add in to keep a watch list of companies- it’s a great tool because it is free for the amount of data I use and I can set the fields up exactly how I need them. Email me at acarpenter@intrinio.com and I’ll send you my template or answer your questions about the Excel add-in, you can also see it attached to each of my reports.

In that watch list I look at the following metrics:

Price: Has the stock dropped significantly (10% or more) or is the company near its 52 week low (within 10%). If so, I take this as evidence that the stock is a contrarian buy- others are bearish so I want to be bullish. The drop in price is assumed to indicate at least some negative factors are priced in, providing some margin of safety.

P/E Ratio: With the full knowledge that interpreting P/E ratios is far more complicated than simply saying lower is better, I’m looking for companies in the sweet spot between 8-14. This means the company is stable but under valued as compared to historic averages for the broader market which fluctuates between 15-22. I consider getting more earnings for a lower price to be a mark of value and as a value investor, I’m looking for stocks in this range.

Beta: Price fluctuations can be an opportunity for traders and market timers but I would rather see slow, steady growth over time. That said, I’m looking for growth and with growth comes some volatility. I’m looking for betas under 2 with betas under 1 being a big plus.

Dividend: I understand the argument for a company reinvesting in itself instead of paying money to its shareholders. Still, a dividend that has grown overtime is a sign that a company can build its asset base and provide cash to investors. That is a good sign and it is something that gives me the confidence that if I am wrong about a stock I can get paid to hold onto it until it rebounds. Someday I’d like to use my dividends as an income stream and as I find great values I plan to hold them for years or decades for this purpose. I consider 3%-6% to be the ideal balance between repaying shareholders and reinvesting in future growth.

Valuation: With the help of Intrinio’s online valuation engine I will check my assumptions against the DCF intrinsic value of the company to determine if it is the right buy at the right time.  

Insight: When I find a stock whose business model I like, I add it to my watch list and, when I have capital to invest, I look for stocks on my list that fit the criteria listed above. If I find one, I will generate a report on it that includes these factors as well as my personal insight into the future of the company. 

 

- See more at: https://www.intrinio.com/app#/report/41

 

I've owned Ford in a retirement account for some time. Next month it looks like Ford will announce its traditional dividend increase as well as a driverless car partnership with Google. That made me want to consider getting some of my taxable portfolio behind the stock. The lack of a recent big downturn for Ford makes me cautious about the company's ability to create a big ROI. I doubled down on IBM and STX instead. My biggest concern with Ford is that I suspect, in the long run, driverless cars will decrease the demand for cars overall.

Beta: Ford has a nice low beta of 1.17. This lack of variability reminds me of Ford's ability to not take a bailout back in the great recession- this is a company that knows about stability and I think that contributes to their brand but hinders their ability to adapt.

Dividend: At over 4% with enough free cash flow to cover payouts and an expected hike in January, Ford is a tempting dividend river to add to feed into my dividend cannon. I think of my monthly dividends as an income stream I can point at things- usually I point them at stocks but someday I want to point them at my expenses to cover my writing habit. Ford certainly qualifies for my ideal range of 3%-6%.

Price: Ford traded about 7% lower than its current price in August and later in September however it has fallen about 14% from its yearly highs in October and last spring. Forgive the roughness of these estimates, I'm really just trying to determine if any surprises have been priced in. Based on its middle of the road price for the year I wouldn't qualify this as an opportunistic time to buy.

P/E ratio: For has a P/E ratio of about 11.72 which makes sense for an old time company in such a competitive industry. I like that multiple, but I don't love it. See my insight into the future of the industry below.

Valuation: The base case valuation for Ford based on Wall Street consensus estimates shows a huge margin of safety score of 71 with an intrinsic value of $48.18. This is one case where I won't trust the algorithmic DCF that Intrinio so kindly calculates for me to make my job easier but it does provide some insight into the fundamentals of Ford- this is a strong company with a healthy balance sheet.

Insight: Here is where my concern with Ford is preventing me from investing more. Imagine the world that Ford's CEO predicted- driverless cars in 5 years. With Google (hopefully) throwing its brains behind Ford, it seems like they will get a jump on that dream. But what will this mean? Someone, maybe Ford, will win the race for government approval. That will be a huge moment for that company and if I had to pick a horse I don't see why Ford, with its strong cash flows to invest, shouldn't win, especially if it partners with Google. In that best case scenario, what would happen for Ford? It would be an initial boom- everyone who could get one would want one, and those babies would actually be worth putting up some serious cash for. 

But then what? Here is my prediction- cars will become like apartments. People with cash will buy them as assets, not liabilities, and will rent them out by the hour. Companies like Uber will become the norm as cars become an operating expense, rather than a capital expense, for most people. In general, this will mean a lot fewer cars will be sold because cars will not be sitting idol. When you aren't driving it, someone else is renting it from you. You've heard as software as a service- can Ford make that transition as well?

Maybe yes, maybe no, but the industry is about to be disrupted in a big way. That creates a lot of opportunity but also a lot of risk. I don't buy automakers because I'm looking for big risks, I'd rather save some cash for a down payment on a driverless car I can rent out. 

______________________________________________________________________________________________________________________________________________

About my strategy:

I use Intrinio’s excel add in to keep a watch list of companies- it’s a great tool because it is free for the amount of data I use and I can set the fields up exactly how I need them. Email me at acarpenter@intrinio.com and I’ll send you my template or answer your questions about the Excel add-in, you can also see it attached to each of my reports.

In that watch list I look at the following metrics:

Price- Has the stock dropped significantly (10% or more) or is the company near its 52 week low (within 10%). If so, I take this as evidence that the stock is a contrarian buy- others are bearish so I want to be bullish. The drop in price is assumed to indicate at least some negative factors are priced in, providing some margin of safety.

P/E Ratio- With the full knowledge that interpreting P/E ratios is far more complicated than simply saying lower is better, I’m looking for companies in the sweet spot between 8-14. This means the company is stable but under valued as compared to historic averages for the broader market which fluctuates between 15-22. I consider getting more earnings for a lower price to be a mark of value and as a value investor, I’m looking for stocks in this range.

Beta- Price fluctuations can be an opportunity for traders and market timers but I would rather see slow, steady growth over time. That said, I’m looking for growth and with growth comes some volatility. I’m looking for betas under 2 with betas under 1 being a big plus.

Dividend- I understand the argument for a company reinvesting in itself instead of paying money to its shareholders. Still, a dividend that has grown overtime is a sign that a company can build its asset base and provide cash to investors. That is a good sign and it is something that gives me the confidence that if I am wrong about a stock I can get paid to hold onto it until it rebounds. Someday I’d like to use my dividends as an income stream and as I find great values I plan to hold them for years or decades for this purpose. I consider 3%-6% to be the ideal balance between repaying shareholders and reinvesting in future growth.

Valuation: With the help of Intrinio’s online valuation engine I will check my assumptions against the DCF intrinsic value of the company to determine if it is the right buy at the right time.  

Insight: When I find a stock whose business model I like, I add it to my watch list and, when I have capital to invest, I look for stocks on my list that fit the criteria listed above. If I find one, I will generate a report on it that includes these factors as well as my personal insight into the future of the company. 

 

- See more at: https://www.intrinio.com/app#/report/41

I've owned Ford in a retirement account for some time. Next month it looks like Ford will announce its traditional dividend increase as well as a driverless car partnership with Google. That made me want to consider getting some of my taxable portfolio behind the stock. The lack of a recent big downturn for Ford makes me cautious about the company's ability to create a big ROI. I doubled down on IBM and STX instead. My biggest concern with Ford is that I suspect, in the long run, driverless cars will decrease the demand for cars overall.

Beta: Ford has a nice low beta of 1.17. This lack of variability reminds me of Ford's ability to not take a bailout back in the great recession- this is a company that knows about stability and I think that contributes to their brand but hinders their ability to adapt.

Dividend: At over 4% with enough free cash flow to cover payouts and an expected hike in January, Ford is a tempting dividend river to add to feed into my dividend cannon. I think of my monthly dividends as an income stream I can point at things- usually I point them at stocks but someday I want to point them at my expenses to cover my writing habit. Ford certainly qualifies for my ideal range of 3%-6%.

Price: Ford traded about 7% lower than its current price in August and later in September however it has fallen about 14% from its yearly highs in October and last spring. Forgive the roughness of these estimates, I'm really just trying to determine if any surprises have been priced in. Based on its middle of the road price for the year I wouldn't qualify this as an opportunistic time to buy.

P/E ratio: For has a P/E ratio of about 11.72 which makes sense for an old time company in such a competitive industry. I like that multiple, but I don't love it. See my insight into the future of the industry below.

Valuation: The base case valuation for Ford based on Wall Street consensus estimates shows a huge margin of safety score of 71 with an intrinsic value of $48.18. This is one case where I won't trust the algorithmic DCF that Intrinio so kindly calculates for me to make my job easier but it does provide some insight into the fundamentals of Ford- this is a strong company with a healthy balance sheet.

Insight: Here is where my concern with Ford is preventing me from investing more. Imagine the world that Ford's CEO predicted- driverless cars in 5 years. With Google (hopefully) throwing its brains behind Ford, it seems like they will get a jump on that dream. But what will this mean? Someone, maybe Ford, will win the race for government approval. That will be a huge moment for that company and if I had to pick a horse I don't see why Ford, with its strong cash flows to invest, shouldn't win, especially if it partners with Google. In that best case scenario, what would happen for Ford? It would be an initial boom- everyone who could get one would want one, and those babies would actually be worth putting up some serious cash for. 

But then what? Here is my prediction- cars will become like apartments. People with cash will buy them as assets, not liabilities, and will rent them out by the hour. Companies like Uber will become the norm as cars become an operating expense, rather than a capital expense, for most people. In general, this will mean a lot fewer cars will be sold because cars will not be sitting idol. When you aren't driving it, someone else is renting it from you. You've heard as software as a service- can Ford make that transition as well?

Maybe yes, maybe no, but the industry is about to be disrupted in a big way. That creates a lot of opportunity but also a lot of risk. I don't buy automakers because I'm looking for big risks, I'd rather save some cash for a down payment on a driverless car I can rent out. 

______________________________________________________________________________________________________________________________________________

About my strategy:

I use Intrinio’s excel add in to keep a watch list of companies- it’s a great tool because it is free for the amount of data I use and I can set the fields up exactly how I need them. Email me at acarpenter@intrinio.com and I’ll send you my template or answer your questions about the Excel add-in, you can also see it attached to each of my reports.

In that watch list I look at the following metrics:

Price- Has the stock dropped significantly (10% or more) or is the company near its 52 week low (within 10%). If so, I take this as evidence that the stock is a contrarian buy- others are bearish so I want to be bullish. The drop in price is assumed to indicate at least some negative factors are priced in, providing some margin of safety.

P/E Ratio- With the full knowledge that interpreting P/E ratios is far more complicated than simply saying lower is better, I’m looking for companies in the sweet spot between 8-14. This means the company is stable but under valued as compared to historic averages for the broader market which fluctuates between 15-22. I consider getting more earnings for a lower price to be a mark of value and as a value investor, I’m looking for stocks in this range.

Beta- Price fluctuations can be an opportunity for traders and market timers but I would rather see slow, steady growth over time. That said, I’m looking for growth and with growth comes some volatility. I’m looking for betas under 2 with betas under 1 being a big plus.

Dividend- I understand the argument for a company reinvesting in itself instead of paying money to its shareholders. Still, a dividend that has grown overtime is a sign that a company can build its asset base and provide cash to investors. That is a good sign and it is something that gives me the confidence that if I am wrong about a stock I can get paid to hold onto it until it rebounds. Someday I’d like to use my dividends as an income stream and as I find great values I plan to hold them for years or decades for this purpose. I consider 3%-6% to be the ideal balance between repaying shareholders and reinvesting in future growth.

Valuation: With the help of Intrinio’s online valuation engine I will check my assumptions against the DCF intrinsic value of the company to determine if it is the right buy at the right time.  

Insight: When I find a stock whose business model I like, I add it to my watch list and, when I have capital to invest, I look for stocks on my list that fit the criteria listed above. If I find one, I will generate a report on it that includes these factors as well as my personal insight into the future of the company. 

 

- See more at: https://www.intrinio.com/app#/report/41

– See more at: https://www.intrinio.com/app#/report/41

DCF Valuation Course Case Study

We like to highlight certain cases where Intrinio Financial Data makes a huge difference for our users.

This semester, students in the University of South Florida's Intro to Finance course used the Intrinio Excel add-in to help them understand DCF Valuation.

Valuation:

The process of determining the current worth of an asset or company. There are many techniques that can be used to determine value, some are subjective and others are objective.

For example, an analyst valuing a company may look at the company's management, the composition of its capital structure, prospect of future earnings, and market value of assets.

Judging the contributions of a company's management would be more of a subjective valuation technique, while calculating intrinsic value based on future earnings would be an objective technique.

For our class with USF, we used the objective approach. We helped the students use Intrinio data to construct a Discounted Cash Flow Model (DCF) in order to determine the intrinsic value of a company.

Like most parts of financial analysis, the hardest part about a DCF valuation is gathering the data necessary to build the model. Without the use of innovative tools like the Intrinio Financial Data Feed, students (and professionals) can be left spending (wasting) hours entering the data before they can actually analyze it and build their model.

Scroll to the end of this Case Study and take a peek at the last image - the finished Discounted Cash Flow model. Can you imagine how long this would take if you needed to type it all in by hand? Hours.

Instead, using the Intrinio Excel add-in, the students at USF were able to quickly build a dynamic model that saves them time moving forward. If they want to value a new company - they simply change the ticker. Without the Intrinio Excel add-in, they'd need to type each new value in by hand.

It is estimated that Intrinio saved each student at University of South Florida an average of 10 hours of data entry during their studies of Valuation.

Aside from learning the valuable skills of Valuation (pun intended) the students at USF gained an advanced understanding of Excel modeling and learned tips, tricks and shortcuts for getting the most out of the functionality of Excel - very important skills for a future in the business world.

Installation

The class began by quickly installing the Intrinio Excel add-in on each student's own personal computer (Mac OS X & Microsoft Windows). The entire install process took less than 5 minutes, and the students followed along with the directions and YouTube video on the Intrinio channel.

Installation link: https://home.intrinio.com/getting-started-excel-step-1/

Excel

Once the Excel add-in was installed on each student's computer, we walked them through the process of building a DCF step by step.

Setup

Begin by naming your first Sheet in Excel "DCF" (discounted cash flow), and naming a second sheet "WACC" (weighted average cost of capital).

Choose a ticker and enter it in cell A1 - so that it can be referenced throughout the entire model. In our example, we use AAPL (Apple).

Click on the A1 Cell, then click on the named range box just above it. Delete "A1" and type the word "ticker". Now, in each of your formulas you'll be able to simply type "ticker" instead of "AAPL" or "A1".

Note: Some of your data will look different from the data in this Case Study because it will be more current - the data in the following screenshots and examples is how it looked for the USF students the day they built their DCF.

Cash Flow Model

Skipping a couple of lines, enter in each item that we will pull in data for and forecast for AAPL in cells B7-B19.

In the next column, next to the actual values (Total Revenues) but not the ratios/percentages (% Revenue Growth), put the associated "Intrinio Tag" that we'll use to pull the data in. This will make building our formulas much easier.

  • totalrevenue
  • ebit
  • capex
  • depreciationandamortization
  • nwc

So far, your DCF workbook should look something like this:

Intrinio DCF Valuation Case Study Y Axis

Historical & Projected Fiscal Years

For this case, we're going to be pulling in historical data dating back to 2009, and forecasting out two years to 2017. We use something called a "sequence" number in our data feed, which represents the "nth" item in a data series. Since we're going back 6 years (2015 is sequence number 0), we'll need 6 items in the sequence.

In cell J2 type "0", then in cell I2 type "J2+1", then drag across to cell "D2".

You should have populated 6, 5, 4, 3, 2, 1, 0 across row 2.

Intrinio DCF Valuation Case Study Periods

Next, underneath each of these sequence numbers in row 3, we'll want to populate the corresponding end-dates for the income statement (the data we're pulling in).

In cell J3 type the following formula to pull this data in:

=IntrinioFundamentals(ticker,"income_statement","FY",J2,"end_date")

It should populate with: 2015-09-26

You can drag this across to sequence number 6 in D3 and the whole row should populate.

By using formulas like this to pull in seemingly simple numbers, we are making the model extremely dynamic and flexible. It may seem simpler to type out 2015-09-26 -> but in fact you'll be creating a dynamic model and saving time by using the formulas to pull this data in.

 

Next, underneath these dates in row 4, we'll want to populate the fiscal year associated with the historical dates and statements (2009-2015).

In cell J4 type the following formula to pull this data in:

=IntrinioFundamentals(ticker,"income_statement","FY",J2,"fiscal_year")

It should populate with: 2015

You can drag this across to column D, and the whole row should populate with the correct fiscal years corresponding to the sequence number.

Intrinio DCF Valuation Case Study Years

Lastly, underneath this we'll want to pull in the fiscal period for each cell (this is just FY, indicating that these are fiscal year values, as opposed to quarterly, etc.).

In cell J5, type the following formula to pull these fiscal periods in:

=IntrinioFundamentals(ticker,"income_statement","FY",H2,"fiscal_period")

It should populate with: FY

You can drag this across to column D, and the whole row should populate with the correct fiscal periods.

 

Back up in row 1, merge and center the cells from D1 to J1, and type in "Historical" to indicate that these columns will have historical data.

Merge and center cells K1 and L1, and type in "Forecasted" to indicate that these columns will have forecasted data.

 

We want our first forecasted date to be next year on the same month, same day.

In cell K3, type the following formula to pull this date in:

=DATE(YEAR(J3)+1,MONTH(J3),DAY(J3))

It should populate with: 09/26/2016

You can drag this cell over one into L3 to populate the following year.

 

Underneath this, we want to pull in the associated years (2016 and 2017).

In cell K4, type the following formula in:

=+J4+1

It should populate with: 2016

You can drag this cell over one into L4 to populate the following year.

So far, your DCF workbook should look something like this:

Intrinio DCF Valuation Case Study X-axis

Historical Data

Next we're going to populate the raw historical data from 2009 - 2015. Using Intrinio formulas we'll pull in all the historical data for Revenues, EBIT, CAPEX, Depreciation and Net Working Capital.

In cell D7, type the following formula to pull in AAPL's total revenues for FY 2009:

=IntrinioFinancials(ticker,"income_statement",D4,D5,$C$7,"M")

You're referencing the ticker, "2009" (D4), "FY" (D5), as well as the associated tag "totalrevenue" ($C$7).

$C$7 is being hard coded ($) so that when we drag the formulas it doesn't auto-populate. This value will change.

"M" stands for millions. You can return values in "A" (actuals), "K" (thousands), "M" (millions) or "B" (billions).

If we were writing the whole formula out by hand, it would look like this:

=IntrinioFinancials("AAPL","income_statement",2009,"FY","totalrevenue","M")

You can click and drag this cell across all the way to J7 and you should see the associated revenue values populate.

 

In cell D9, type the following formula to pull in AAPL's EBIT for FY 2009:

=IntrinioFinancials(ticker,"calculations",D4,D5,$C$9,"M")

You're referencing the ticker, "2009" (D4), "FY" (D5), as well as the associated tag "ebit" ($C$9).

If we were writing the whole formula out by hand, it would look like this:

=IntrinioFinancials("AAPL","calculations",2009,"FY","ebit","M")

You can click and drag this cell across all the way to J9 and you should see the associated EBIT values populate.

 

In cell D11, type the following formula to pull in AAPL's CAPEX for FY 2009:

=IntrinioFinancials(ticker,"calculations",D4,D5,$C$11,"M")

You're referencing the ticker, "2009" (D4), "FY" (D5), as well as the associated tag "capex" ($C$11).

If we were writing the whole formula out by hand, it would look like this:

=IntrinioFinancials("AAPL","calculations",2009,"FY","capex","M")

You can click and drag this cell across all the way to J11 and you should see the associated CAPEX values populate.

In cell D13, type the following formula to pull in AAPL's Depreciation for FY 2009:

=IntrinioFinancials(ticker,"calculations",D4,D5,$C$13,"M")

You're referencing the ticker, "2009" (D4), "FY" (D5), as well as the associated tag "depreciationandamortization" ($C$13).

If we were writing the whole formula out by hand, it would look like this:

=IntrinioFinancials("AAPL","calculations",2009,"FY","depreciationandamortization","M")

You can click and drag this cell across all the way to J13 and you should see the associated capex values populate.

 

In cell D15, type the following formula to pull in AAPL's NWC for FY 2009:

=IntrinioFinancials(ticker,"calculations",D4,D5,$C$15,"M")

You're referencing the ticker, "2009" (D4), "FY" (D5), as well as the associated tag "nwc" ($C$15).

If we were writing the whole formula out by hand, it would look like this:

=IntrinioFinancials("AAPL","calculations",2009,"FY","nwc","M")

You can click and drag this cell across all the way to J15 and you should see the associated capex values populate.

Historical Ratios

Next we'll want to use some basic math and formulas to calculate historical ratios based off of the data we just pulled in. For example, we'll want to know how Revenue has grown over past years in order to predict how it will grow in the future.

To calculate Revenue growth, we'll want to take the chosen year divided by the previous year minus one. Because this ratio takes into account the previous year to measure growth, we'll start in 2010 and leave 2009 blank.

In cell E8, type the following formula to pull in AAPL's revenue growth from 2009 to 2010:

=E7/D7-1

You can click the % button in the top ribbon bar to make this a percentage, and click and drag this cell across to J8 to populate the rest of the revenue growth numbers.

 

To calculate % EBIT Margin, we'll want to take the 2009 EBIT and divide it by the 2009 Total Revenues.

In cell D10, type the following formula to pull in AAPL's % EBIT Margin for 2009:

=D9/D7

You can click the % button in the top ribbon bar to make this a percentage, and click and drag this cell across to J10 to populate the rest of the % EBIT Margin numbers.

 

To calculate CAPEX/Revenue, we'll want to take the 2009 CAPEX and divide it by the 2009 Total Revenues.

In cell D12, type the following formula to pull in AAPL's CAPEX/Revenue for 2009:

=D11/D7

You can click the % button in the top ribbon bar to make this a percentage, and click and drag this cell across to J12 to populate the rest of the CAPEX/Revenue numbers.

 

To calculate Depreciation/Revenue, we'll want to take the 2009 Depreciation and divide it by the 2009 Total Revenues.

In cell D14, type the following formula to pull in AAPL's Depreciation/Revenue for 2009:

=D13/D7

You can click the % button in the top ribbon bar to make this a percentage, and click and drag this cell across to J14 to populate the rest of the Depreciation/Revenue numbers.

 

To calculate NWC/Revenue, we'll want to take the 2009 NWC and divide it by the 2009 Total Revenues.

In cell D16, type the following formula to pull in AAPL's NWC/Revenue for 2009:

=D15/D7

You can click the % button in the top ribbon bar to make this a percentage, and click and drag this cell across to J16 to populate the rest of the Depreciation/Revenue numbers.

 

To calculate the change in NWC, we'll want to take the 2010 NWC and subtract the 2009 NWC (since this is a growth number we'll leave 2009 blank and start in 2010).

In cell E17, type the following formula to pull in AAPL's change in NWC for between 2009 and 2010:

=E15-D15

You can click and drag this cell across to J17 to populate the rest of the change in NWC numbers.

 

So far, your DCF workbook should look something like this:

Intrinio DCF Valuation Case Study Ratio Projections

 

Forecasted Values

Next, we want to pull in our forecasts for Revenue, EBIT, CAPEX, Depreciation, and NWC for 2016 and 2017.

To forecast Total Revenues, we'll use the Intrinio formula for Wall Street consensus Revenues. We get this data from a company called Zacks, which sources it from top Wall Street analysts. We'll want to divide this value by 1,000,000 to adjust the raw data.

In cell K7, type the following formula to pull in our forecast for AAPL's revenue in 2016:

=IntrinioDataPoint(ticker,"current_yr_ave_revenue_est")/1000000

In cell L7, type the following formula to pull in our forecast for AAPL's revenue in 2017:

=IntrinioDataPoint(ticker,"next_yr_ave_revenue_est")/1000000

 

To project % Revenue Growth in 2016, we'll want to take the Revenue forecast for 2016 and divide by Revenues in 2015 minus 1.

In cell K8, type the following formula to project % Revenue Growth for AAPL in 2016:

=K7/J7-1

You can click and drag this cell across to L8 to project % Revenue Growth for AAPL in 2017.

 

To forecast EBIT in 2016, we need to first know the % EBIT Margin for 2016. To calculate this, we'll take the average of all the historical data for % EBIT Margin.

In cell K10, type the following formula to forecast AAPL's % EBIT Margin for 2016:

=AVERAGE(D10:J10)

You can click and drag this formula across to cell L10 to forecast AAPL's % EBIT Margin for 2017.

 

Moving back up a line to EBIT in 2016, we can now forecast this by multiplying Revenues in 2016 by % EBIT Margin in 2016.

In cell K9, type the following formula to forecast AAPL's EBIT in 2016:

=K10*K7

You can click and drag this formula across to cell L9 to forecast AAPL's EBIT for 2017.

 

Similarly, to calculate CAPEX in 2016 we'll need to first calculate CAPEX/Revenue for 2016. We do this by taking the average of all the historical data for CAPEX/Revenue.

In cell K12, type the following formula to forecast AAPL's CAPEX/Revenue for 2016:

=AVERAGE(D12:J12)

You can click and drag this formula across to cell L12 to forecast AAPL's CAPEX/Revenue for 2017.

 

Moving back up a line to CAPEX in 2016, we can now forecast this by multiplying Revenues in 2016 by CAPEX/Revenue in 2016.

In cell K11, type the following formula to forecast AAPL's CAPEX in 2016:

=K12*K7

You can click and drag this formula across to cell L11 to forecast AAPL's CAPEX for 2017.

 

The same goes for Depreciation: we must first calculate Depreciation/Revenue for 2016.

In cell K14, type the following formula to forecast AAPL's Depreciation/Revenue for 2016:

=AVERAGE(D14:J14)

You can click and drag this formula across to cell L14 to forecast AAPL's Depreciation/Revenue for 2017.

 

Moving back up a line to Depreciation in 2016, we can now forecast this by multiplying Revenues in 2016 by Depreciation/Revenue in 2016.

In cell K13, type the following formula to forecast AAPL's Depreciation in 2016:

=K14*K7

You can click and drag this formula across to cell L13 to forecast AAPL's Depreciation for 2017.

 

Surprise, in order to calculate NWC for 2016 we must first calculate NWC/Revenue in 2016.

In cell K16, type the following formula to forecast AAPL's NWC/Revenue for 2016:

=AVERAGE(H16:J16)

In this case, we only take the average of the past three years instead of averaging all of the historical data. We do this because NWC/Revenue in years 2009-2012 is substantially higher than the rest of the years (outliers) and that doesn't fit into a normalized projection for the future - so we don't want to include it in our calculation of the average.

You can click and drag this formula across to cell L16 to forecast AAPL's NWC/Revenue for 2017.

 

Finally, we can calculate NWC for 2016 by multiplying Revenues in 2016 by NWC/Revenue in 2016.

In cell K15, type the following formula to forecast AAPL's NWC in 2016:

=K16*K7

You can click and drag this formula across to cell L15 to forecast AAPL's NWC for 2017.

 

To finish off our projections, we'll project the change in NWC from 2016 to 2017. We do this by subtracting the actual historical value for NWC in 2015 from our projected value for NWC in 2016.

In cell K17, type the following formula to forecast AAPL's change in NWC:

=K15-J15

You can click and drag this formula across to cell L17 to forecast AAPL's change in NWC from 2016 to 2017.

 

Your projections for the DCF should now look something like this:

Intrinio DCF Valuation Case Excel Projections

Weighted Average Cost of Capital

At this point in the model, we're going to switch over to the WACC worksheet and calculate the weighted average cost of capital before we finish this DCF.

Setup

In your WACC worksheet, type the following to get set up:

  • "DEBT" into cell D4
  • "EQUITY" into cell J4
  • "WACC" into cell D11

Cost of Debt

Underneath "Debt", type the following into cells D5-D7:

  • Moody's AAA Yield
  • Tax Rate
  • After Tax Cost of Debt

In cell E5, we'll use the Intrinio formula that pulls in Moody's AAA Yield from the Federal Reserve. This percentage represents the riskiness of investment grade corporate bonds. In the case of AAPL we'll use the AAA curve because it represents the highest rated corporates yield to maturity, and AAPL carries a lot of cash and is unlikely to go bankrupt. However, depending on the riskiness of the company you have chosen, you can also pull in the BBB curve.

In cell E5 type the following formula to pull in Moody's AAA Yield:

=IntrinioDataPoint("FRED.AAA","value")/100

We divide by 100 to transform the return value into a percentage.

In cell E6 type the following formula to pull in the Tax Rate:

=IntrinioDataPoint(ticker,"efftaxrate")

To calculate the after-tax cost of debt, we need to take the AAA Yield times (1-tax rate).

In cell E7, to calculate the After-Tax Cost of Debt, type in the following formula:

=E5*(1-E6)

 We calculate the cost of debt "after" taxes, because interest expense is tax deductive and dividends paid is not. This means there is a tax advantage to taking out debt.

Your Cost of Debt section should look something like this:

Intrinio DCF Valuation Case Study WACC Cost of Debt

 

Cost of Equity

Underneath "Equity", type the following into cells J5-J8:

  • Risk Free Rate
  • Beta
  • Equity Risk Premium
  • Cost of Equity

In cell K5, we'll use the Intrinio formula to pull in the risk free rate from the Federal Reserve:

This is the 10-year treasury constant maturity

=IntrinioDataPoint("FRED.DGS10","value")/100

In cell K6, type the following formula to pull in the Beta for AAPL:

=IntrinioDataPoint(ticker,"beta")

To calculate the Equity Risk Premium, we use data from Aswath Damodaran a finance professor at the Stern School of Business at New York University. At Intrinio, we call him the Godfather of Value Investing. He is a recognized authoritative source for equity risk premium data.

In cell K7, type in the following formula to pull in Professor Damodaran's ERP value:

=IntrinioDataPoint("DMD.ERP","ttm_erp")

Lastly to calculate the Cost of Equity, we'll take the Risk Free Rate plus (Beta times the Equity Risk Premium).

In cell K8, type in the following formula to pull in the Cost of Equity:

=K5+(K6*K7)

Your Cost of Equity Section should look something like this:

Intrinio DCF Valuation Case Study WACC Cost of Equity

 

WACC

Underneath "WACC", type the following into cells D12-D14:

  • Debt
  • Equity
  • Total Market Value

In cell E12, type the following formula to pull in AAPL's Total Debt:

=IntrinioDataPoint(ticker,"debt")/1000000

In cell E13, type the following formula to pull in AAPL's Total Equity:

=IntrinioDataPoint(ticker,"marketcap")/1000000

In cell E14, type the following formula to calculate AAPL's Total Market Value:

=SUM(E12:E13)

In cell F12, next to the value of debt, we want to calculate debt as a percentage of the total market value.

In cell F12, type the following formula to calculate AAPL's Debt as a percentage of Total Market Value:

=E12/$E$14

In cell F13, next to the value of equity, we want to calculate equity as a percentage of the total market value.

In cell F13, type the following formula to calculate AAPL's Equity as a percentage of Total Market Value:

=E13/$E$14

In cell G12, next to the debt as a percentage of total market value, type the following formula to pull in the after tax cost of debt that we previously calculated above:

=E7

In cell G13, next to the equity as a percentage of total market value, type the following formula to pull in the cost of equity that we previously calculated above:

=K8

In cell H12, type in the following formula to calculate the weighted cost of debt:

=F12*G12

In cell H13, type in the following formula to calculate the weighted cost of equity:

=F13*G13

Lastly, in cell H14, type in the following formula to add the two together and calculate the Weighted Average Cost of Capital:

=SUM(H12:H13)

Your WACC worksheet should now look something like this:

Intrinio DCF Valuation Case Study WACC

Free Cash Flow to Firm

Now that we have calculated the WACC for AAPL, we can head back to the DCF page to finish off the Free Cash flows, discount them, and arrive at an intrinsic value.

Back in the DCF worksheet, we need to calculate the historical FCFF (Free Cash Flow to Firm) for years 2009-2015.

The formula to calculate FCFF is the following:

EBIT * (1-Tax Rate) - CAPEX + Depreciation - Change in NWC

In cell E19, type in the following formula to pull in the FCFF for AAPL for 2009:

=E9*(1-IntrinioFinancials(ticker,"calculations",E4,E5,"efftaxrate"))-E11+E13-E17

You can click and drag this formula across to cell J19 to calculate FCFF for the remaining historical years.

 

To calculate the projected FCFF, we'll use the effective tax rate from the WACC calculation for consistency, since there is no projected tax rate.

In cell K19, type in the following formula to pull in the projected FCFF to AAPL for 2016:

=K9*(1-WACC!$E$6)-K11+K13-K17

The "WACC!$E$6" populates when you reference the effective tax rate from the WACC workbook (cell reference).

You can click and drag this formula across to cell L19 to project FCFF for AAPL for 2017.

Your DCF Worksheet should now look something like this:

Intrinio DCF Valuation Case Study FCFF

 

Discounting Free Cash Flows

The next step after calculating Free Cash Flows is to Discount those Free Cash Flows to their present value. To do this, we need to calculate the discount rate. We'll need to calculate the time periods for the future cash flow as well as the terminal value (FCFF into perpetuity).

In cells J20-J22, type in the following:

  • Periods
  • Terminal Value
  • Discount Factor

In cell K20, type the following formula to calculate the period value for 2016:

=(K3-NOW())/365

You can click this cell and drag across to cell L20 to calculate the period value for 2017.

Leaving cell K22 blank, we'll calculate the Terminal Value in cell L22.

The formula for Terminal Value is the following:

Last Period FCFF / (WACC - long term growth rate)

In cell L22, type in the following formula to calculate the Terminal Value for AAPL:

=L19/(WACC!H14-0.02)

WACC!H14 is a cell reference to the WACC value calculated on the WACC workbook.

We use 0.02 as a long term growth rate because economist consensus for long term nominal GDP growth is around 2-3%.

Next we want to calculate the discount factor.

The formula for discount factor is:

(1-r) ^ t

r = rate and t = time periods

In cell K22 type the following formula to calculate the discount factor for 2016:

=(1-WACC!H14)^DCF!K21

You can click and drag this cell across to L22 to calculate the discount factor for 2017.

Next, to calculate the Discounted Free Cash Flow to Firm we want to multiply the Free Cash Flow for each projected year by the associated Discount Rate.

In cell K25, type the following formula to calculate the DFCFF for AAPL for 2016:

=K19*K22

In cell L25, type the following formula to calculate the DFCFF for AAPL for 2017:

=L21*L22

The Discounted FCFF section of your DCF worksheet should now look like this:

Intrinio DCF Valuation Case Study Discounted FCFF

Calculating Intrinsic Value

Now that we've discounted our cash flows, we're ready to use them to calculate the intrinsic value of AAPL.

In cells J27-J29, type the following:

  • Intrinsic Value of the Firm
  • Total Debt
  • Intrinsic Value of Equity

Next, skipping a row each time, in cells J31, J33, J35 and J37, type the following:

  • Weighted Average Shares Outstanding
  • Intrinsic Value Per Share
  • Last Stock Price
  • Expected Return

Intrinsic Value of The Firm is calculated by simply adding the Discounted FCFF for the projected years together.

In cell K27, type the following to calculate AAPL's Intrinsic Value of The Firm:

=SUM(K25:L25)

In cell K28, type in the following formula to pull in AAPL's Total Debt:

=IntrinioDataPoint(ticker,"debt")/1000000

In cell K29, type in the following formula to calculate AAPL's Intrinsic Value of Equity:

=K27-K28

In cell K31, type in the following formula to pull in AAPL's Weighted Average Shares Outstanding:

=IntrinioDataPoint(ticker,"weightedavedilutedsharesos")/1000000

To calculate the intrinsic value per share, we simply take the intrinsic value of equity divided by the weighted average shares outstanding.

In cell K33, type in the following formula to calculate AAPL's intrinsic value per share:

=K29/K31

In cell K31, type in the following formula to pull in AAPL's Last Stock Price:

=IntrinioDataPoint(ticker,"close_price")

Lastly, to calculate our expected return, we want to take the intrinsic value per share divided by the last stock price minus one.

In cell K37, type in the following formula to calculate the expected return for AAPL:

=K33/K35-1

The intrinsic value section of your DCF workbook should look like this:

Intrinio Valuation Case Study DCF Intrinsic Value

Congratulations, you're done! We've just created a comprehensive discounted cash flow valuation for AAPL, calculating an intrinsic value of $165.52 and an expected return of 53.22%. Obviously, this entire exercise is based on a set of assumptions. Feel free to play around with the model, change some assumptions, and see how it affects the calculated value of the company.

For the students at USF, and hopefully for you too - this has been:

  • A valuable exercise in how valuation works

  • A valuable lesson in Excel functionality

  • A powerful exhibition of the capabilities of the Intrinio Financial Data Feed and Excel add-in

In the end, the DCF workbook should look something like this:

Intrinio Valuation Case Study DCF

If you are a student or professor interested in Intrinio Financial Data or have questions about this Quant Model exercise, please click the green chat button in the right hand corner of this website. We promise to get back to you within the hour.

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or YouTube videos for help getting started. We're available 24/7 by clicking the green button in the bottom right hand corner of the page.

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API Call: What is it, and What Does it Get Me?

The Intrinio Financial Data Feed is delivered to our users via an API. This API interfaces directly with Google Sheets and Microsoft Excel, enabling you to pull in any financial data point from our database. After downloading the Intrinio Excel add-in or installing the Intrinio Google Sheets add-on, you can use Intrinio formulas to pull in any type of data that you want. When you query data into a cell, you are making an API Call.

Developers use the API to pull Intrinio data into any system that they are using. If you're not a developer, it can be confusing to understand API Calls and how they work with Excel and Google Sheets.

At Intrinio, we price by the API Call. This means that you only pay for the data you use - and nothing more. We're the only financial data provider to ever provide this model to our users, and it's saving you hundreds of dollars.

This infographic will help you understand how API Calls work. On our Free Plan, you can make 500 API Calls per day. On average, this will get you all of the financial data for about 5 companies.

Generally speaing, 1 API Call is equivalent to pulling in one piece of data from our database into Excel or Google Sheets. However, there are a few exceptions - including pulling in entire financial statments, and pulling in all price history for one company.

Check out the infographic below to learn what an API Call is.

Intrinio API Call Infographic

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started. We're always available via our Support Page if you need help. 

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Quant Modeling: Intrinio Financial Data Case Study

We like to highlight certain cases where Intrinio Financial Data makes a huge difference for our users.

This semester, students in the University of Tampa's Investments class used the Intrinio Excel add-in to help them understand quant modeling.

Quantitative Modeling:

A financial analysis technique that uses mathematical and statistical modeling, measurement and research to predict real world outcomes for financial instruments. Quantitative analysts assign numerical values to variables to replicate reality mathematically.

The hardest part about quant modeling is gathering the data necessary to build it. Without the use of innovative tools like the Intrinio Financial Data Feed, students (and professionals) can be left spending (wasting) hours entering the data before they can actually analyze it.

We estimate that Intrinio saved each student at University of Tampa an average of 10 hours of data entry during their studies of quant modeling.

The class began by quickly installing the Intrinio Excel add-in on each student's own personal computer (Mac OS X & Microsoft Windows). The entire install process took less than 5 minutes, and the students followed along with the directions and Youtube video on the Intrinio website.

Downloading the Intrinio Excel add-in

The professor had selected a group of metrics that he wanted the students to include in their quant model.

These metrics included:

  • ROE
  • Book to Price Ratio
  • Earnings to Price Ratio
  • Cash Flow to Price Ratio
  • Trading Volume to Market Cap
  • 1 Month Excess Return
  • 2 Month Excess Return
  • 6 Month Excess Return
  • 12 Month Excess Return

The students added these metrics across Row 1.

Next they hard coded two dates into two cells to reference throughout. Current date and the 'start-date' so that they can be referenced and dynamically updated.

  • =TEXT(Now(),”YYYY-MM-DD”)
  • =TEXT(Now()-365*2,”YYYY-MM-DD”)

Typing in "AAPL" into the Row 2 under "Ticker Colum" to start, the students set out filling in the formulas for each cell across.

ROE

=IntrinioDataPoint(“ticker”,”roe”)

The students typed this into the cell beneath ROE, referencing "AAPL" in A2.

Earnings to Price

=IntrinioDataPoint(“ticker”,”earningsyield”)

The students typed this into the cell beneath Earnings to Price, referencing "AAPL" in A2 (earnings yield is the Intrinio tag).

Book to Price

=1/IntrinioDataPoint(“ticker”,”pricetobook”)

We have 1 divided by the price to book ratio to take the inverse.

Quant Model With Intrinio Financial Data - Calculating Price to Book

Cash Flow to Price

=1/IntrinioDataPoint(“ticker”,”evtoocf”)

We have enterprise value to operating cash flow, but we don’t calculate out the price to cash flow ratio in our tag set. Technically cash flow is for the whole entity and not just the equity, and it would be inconsistent to do a ratio for the whole entity versus just the equity. We take the inverse of EV to operating cash flows.

Trading Volume to Market Cap

Trading Volume

=(IntrinioDataPoint(“ticker”,”volume”)*IntrinioDataPoint(“ticker”,”close_price”))

Market Cap

=IntrinioDataPoint(”ticker”,”marketcap”)

Trading Volume to Market Cap

=(IntrinioDataPoint(“ticker”,”volume”)*IntrinioDataPoint(“ticker”,”close_price”))

/ IntrinioDataPoint(“ticker”,”marketcap”)

Volume is the number of shares traded, but we want value of number of shares traded, so we must multiply by the value of the shares traded.

One Month Excess Return

Stock price for most recent period

=IntrinioHistoricalPrices(“ticker”,”adj_close”,0,”start date”,”current date”)

Stock Price Over 21 Day Trading Period

(most recent divided by previous period minus 1)

=(IntrinioHistoricalPrices(“ticker”,”adj_close”,0,”start date”,”current date”)

/

IntrinioHistoricalPrices(“ticker”,”adj_close”,20,”start date”,”current date”) )-1

Excess Return Over The S&P500 Over The 21 Day Trading Period

(copy whole formula and subtract it, same formula substituting in the S&P ($SPX) for the ticker)

 =(IntrinioHistoricalPrices(“ticker”,”adj_close”,0,”2013-10-01”,”current date”)

/

IntrinioHistoricalPrices(“ticker”,”adj_close”,20,”2013-10-01”,”current date”) -1)

-

 (IntrinioHistoricalPrices(“$SPX”,”close”,0,”2013-10-01”,”current date”)

/

IntrinioHistoricalPrices(“$SPX”,”close”,20,”2013-10-01”,”current date”) -1)

Quant Modeling With Intrinio Financial Data - Calculating One Month Excess Return

Two Months Excess Return

Copy WHOLE formula, paste it and change 20 to (20*2)

=(IntrinioHistoricalPrices(“ticker”,”adj_close”,0,”2013-10-01”,”current date”)

/

IntrinioHistoricalPrices(“ticker”,”adj_close”,20*2,”2013-10-01”,”current date”) -1)

-

 (IntrinioHistoricalPrices(“$SPX”,”close”,0,”2013-10-01”,”current date”)

/

IntrinioHistoricalPrices(“SPX”,”close”,20*2,”2013-10-01”,”current date”) -1)

Six Months Excess Return

Copy WHOLE formula, paste it and change 20 to (20*6)

=(IntrinioHistoricalPrices(“ticker”,”adj_close”,0,”2013-10-01”,”current date”)

/

IntrinioHistoricalPrices(“ticker”,”adj_close”,20*6,”2013-10-01”,”current date”) -1)

-

 (IntrinioHistoricalPrices(“$SPX”,”close”,0,”2013-10-01”,”current date”)

/

IntrinioHistoricalPrices(“SPX”,”close”,20*6,”2013-10-01”,”current date”) -1)

Twelve Months Excess Return

Copy WHOLE formula, paste it and change 20 to (20*12)

=(IntrinioHistoricalPrices(“ticker”,”adj_close”,0,”2013-10-01”,”current date”)

/

IntrinioHistoricalPrices(“ticker”,”adj_close”,20*12,”2013-10-01”,”current date”) -1)

-

 (IntrinioHistoricalPrices(“$SPX”,”close”,0,”2013-10-01”,”current date”)

/

IntrinioHistoricalPrices(“SPX”,”close”,20*12,”2013-10-01”,”current date”) -1)

Finishing Up The Quant Model

One the students had the formulas filled in for one stock (AAPL, in our example) it took a matter of seconds to fill in the rest of the model. The students simply added a list of tickers below AAPL, highlighted the row of formulas, and dragged it down. When you click Recalculate, the data will automatically populate. It's as simple as that!

Quant Model With Intrinio Financial Data

After the students successfully pulled in all of the data and metrics they needed (in about 10 minutes instead of hours) - they were ready to start digging into building the model.

 

If you are a student or professor interested in Intrinio Financial Data or have questions about this Quant Model exercise, please click the green chat button in the right hand corner of this website. We promise to get back to you within the hour.

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started. We're always available via our Support Page if you need help. 

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Stock Price Data: Intrinio Adds More Frequencies

Introducing: Daily/Weekly/Monthly/Quarterly/Yearly Historical Price Data

We've officially added a new frequency parameter to our stock price data. The Intrinio Financial Data Feed now offers Daily, Weekly, Monthly, Quarterly, and Yearly Historical Stock Price Data. You can easily and flexibly pull this data into Microsoft Excel, Google Sheets, or any platform using our API. Our pricing is one-of-a-kind, enabling you to get started pulling in 500 API calls per day for Free. Easily upgrade to a higher plan, and still - ONLY pay for the data you use.

 Intrinio Historical Stock Price Data

Intrinio Stock Price Data

Returns professional-grade historical stock prices for a security or stock market index.  New EOD prices are available at 5p.m. EST and 15 minute delayed prices are updated every minute during the trading day.  Historical prices are available back to 1996 or the IPO data in most cases, with some companies with data back to the 1970s.  Stock market index historical price data is available back to the 1950s at the earliest.

Return Values Available for Stock Price Data

  • date – the date of the stock price historical data
  • open – the actual observed first traded stock price of the trading date
  • high – the actual observed highest traded stock price on the trading date
  • low – the actual observed lowest traded stock price on the trading date
  • close – the actual observed last trade stock price on the trading date
  • volume – the actual observed number of shares of stock traded between market participants of the trading date
  • ex_dividend – the non-split adjusted dividend per share on the ex-dividend date – not available on index historical prices
  • split_ratio – the split factor on the split date – not available on index historical prices
  • adj_open – the dividend and split adjusted open price – not available on index historical prices
  • adj_high – the dividend and split adjusted high price – not available on index historical prices
  • adj_low – the dividend and split adjusted low price – not available on index historical prices
  • adj_close – the dividend and split adjusted close price – not available on index historical prices
  • adj_volume – the dividend and split adjusted volume – not available on index historical prices

Example Requests

=IntrinioHistoricalPrices("ticker",'item",sequence,"frequency)

=IntrinioHistoricalPrices("AAPL","close",0,"yearly")

 

Keep in mind, Intrinio offers a breadth of financial data, flexibly and affordably, directly into Excel, Google Sheets, or any program you might be using:

  • Last Stock Price Data: 50,000 securities
  • Historical Stock Price Data: 8,700 securities
  • As-Reported Financial Statement Data: 7,000 securities
  • Standardized Financial Statement Data: 3,500 securities
  • Basic Company Information
  • Hundreds of Metrics and Ratios
  • Sales, Growth & Earnings Estimates
  • Pricing Data for 16 Indices
  • Economic Data

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started. We're always available via our Support Page if you need help. 

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Is Your Data Feed Data Freed?

A financial data feed without restrictions.

At Intrinio, our Data Feed is Data Freed. We provide a wealth of financial data to users, but we do it differently than you've ever experienced. Whether you're an individual investor, a professional investor, a student, a startup or a developer - our Data Feed gives you a degree of flexibility that was never possible before. We're constantly breaking down barriers for you and making your experience more and more seamless.

Our goal? To free you from data feed restrictions that have held you back so you can be as efficient and productive as possible.

What have we freed you from? Quite a bit:

High Prices

Historically, financial data feeds have been a premium product reserved for those who are willing to fork out thousands a month.

Seatbelts

The "seat license" means paying for data you don't even use. It's time to remove the seat belt.

Errors

Manual process have left your data prone to human error. Don't make decisions with unreliable data.

Terminals

Many data licenses require you to be either at a physical terminal, or logged into a particular license or IP address.

Redistribution Fees

It has been the norm to charge outrageous fees in order to redistribute financial data. Think hundreds of thousands of $s.

Data Delays

Large data firms employ outdated processes. You don't get the data until days after it becomes public.

 


 

How have we changed the game at Intrinio?

Low Prices

Large data firms employ outdated processes. You don't get the data until days after it becomes public.

Pay as You Go

Large data firms employ outdated processes. You don't get the data until days after it becomes public.

Quality

Our automated processes ensure investment-grade quality and eliminate human error. Data you can rely on.

Cross Platform

Intrinio is the first cross-platform financial data provider. Access our data on any device, anywhere, anytime.

Redistribute Free

We have completely eliminated redistribution fees. Do whatever you want with our data. Seriously.

Right Away

Within 2 minutes of new company filings, you'll have the data at your disposal. We're speedy.

 

 

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started. We're always available via our Support Page if you need help. 

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Valuation: An Innovative Stock Valuation Engine [tutorial]

This short tutorial is designed to walk you through each step of valuing a company on the Intrinio Valuation engine.

The Valuation platform enables you to scenario test the value of companies under different circumstances. For example, you could run and save three different valuations that show the value of a company as a base case, bearish/downside or bullish/upside.

In this tutorial, we’re going to calculate the intrinsic value of Michael Kors (NYSE: KORS) under the scenario of a recession in 2016.

Step 1: Go to www.intrinio.com and sign in. If you have not already registered, click “Register” in the upper right hand corner and follow the directions to verify your email.

Step 2: Click on “Valuation” in the top header bar, and then "Create a Valuation" in the sub-menu bar.

Step 3: In the first entry box, name your Valuation “Michael Kors 2016 Recession Scenario”. In the second entry box, type KORS. You'll see "KORS - Michael Kors Holdings Ltd." pop up - click on it. Then click “+Save”.

Step 4. The default Valuation will immediately open up, and you’ll see your Valuation title at the top, as well as the default Intrinsic Value, the most recent stock price, and the default Margin of Safety.

Intrinio Valuation - Header

The Intrinsic Value represents the inherent worth of a company. It is the present value of all of the future cash flows the company will generate. Typically, it differs from the current stock price. When the Intrinsic Value is lower than the stock price the company is overvalued, and when the Intrinsic Value is higher than the stock price the company is undervalued. The Margin of Safety represents the difference between the intrinsic value of a stock and its market price. In theory, the further a stock’s price is below its intrinsic value, the greater the margin of safety against future uncertainty and the greater the stock’s resiliency to market downturns. In short – a higher Intrinsic Value and a higher (and positive) Margin of Safety is better.

The Initial Intrinsic Value and Margin of Safety that you see at the top are simply a baseline. They are calculated based off of default assumptions derived from both Wall Street Consensus Data and Mean Reversion calculations. Valuation is as much of an art as it is a science – it requires human input. You’ll want to adjust the assumptions used in the model to more accurately reflect the true intrinsic value of KORS during a recession. These initial numbers are simply a starting point.

We see that initially, without adjusting any assumptions, our base-case analysis shows KORS to be undervalued.

Step 5: This first page we’re on is the Assumptions page. We’ve boiled the Valuation down to 5 main assumptions that drive the DCF model. 3 Cash Flow assumptions (Revenue Growth, NOPAT Margin and Invested Capital Turnover) in a graphical form, and 2 Cost of Capital assumptions (Credit Spread and Company Specific Risk Premium) with slider bars. You can flexibly adjust all of these values here on the Assumptions page.

First off is the Revenue Growth graph. You’ll see the historical data pull in on the left hand side and the default assumptions for future revenue growth populate on the right hand side. Given that KORS is a luxury goods company we will want to drop the Revenue Growth assumptions. Luxury goods companies do not preform well during recessions.

Click on the green dot above the year 2016 and drop it down to -2.50%. Drag 2017 down to -1.00%, drag 2018 down to 1.00%, drag 2019 down to 0.85% and don’t change 2020. (You can also double click on the dot and manually type it in.) Click the green “Save” button in the upper right hand corner. You’ll see the intrinsic value re-calculate at the top.

Intrinio Valuation - Revenue Growth

Step 6: The next assumption is the NOPAT or (Net Operating Profit After Tax) Margin. For a luxury company like KORS, during a recession, we can expect this Margin to collapse as well. Click on the green dot above 2016 and drag it down to 10%. Drag 2017 down to 9%, drag 2018 down to 8%, and drag 2019 down to 9%. Click the green “Save” button in the upper right hand corner. You’ll see the intrinsic value re-calculate at the top.

Intrinio Valuation - NOPAT Margin

Step 7: The last cash flow assumption is Invested Capital Turnover. During a recession, it’s typical for a luxury goods company to have stabilized Invested Capital Turnover. The default values here are already fairly stabilized, so let’s leave this as it is.

Intrinio Valuation - Invested Capital Turnover

Step 8: The first Cost of Capital assumption is the Credit Spread on the Cost of Debt.

This is an evaluation of the riskiness of the debt. Increasing it adds a premium to the Cost of Debt based on the risk that the company will default on their debt. The Credit Spread is calculated in Basis Points (bps). This is a common unit of measurement for interest rates and other financial percentages. One bps is equal to 1/100th of a percent (0.01% or 0.0001). In other words, a 1% change = 100bps and a 0.01% change – 1bps.

During a recession, debt becomes substantially more risky and more companies default. Let’s raise the Credit Spread. Click and drag the green dot up the slider bar to 350 bps. Click the green “Save” button in the upper right hand corner. You’ll see the intrinsic value re-calculate at the top.

Intrinio Valuation - Cost of Capital Assumptions

Step 9: The last assumption is the CSRP (Company Specific Risk Premium). This additional premium has been added to account for company specific risk scenarios as well as any faults in the CAPM model. This is where you can account for any personal knowledge about the company or insights you’ve gained from research. Some factors to consider when increasing or decreasing this premium include:

  • Company size
  • Access to Capital Markets
  • Breadth of Customer Base
  • Geographic Area
  • Key Executive Dependency
  • Limited Product Line
  • Litigation/Regulatory Risk
  • Industry Volatility

For example, when valuing smaller companies, you’ll want to increase the CSRP. The CSRP is a fairly long-term assumption, so it shouldn’t be altered too much based on a recession in 2016. However, equity does become more risky during recessions, so let’s increase this premium to 1.5%. Click the green “Save” button in the upper right hand corner. You’ll see the intrinsic value re-calculate at the top.

And you’re done! At the time we ran this Valuation, we calculated the intrinsic value of KORS in the event of a recession in 2016 to be approximately $52/share and slightly undervalued, regardless of the recessionary conditions. KORS would be a wise investment in this scenario, under these assumptions.

The only changes needed to complete a Valuation are on the “Assumptions” page. However, a wealth of additional information is provided within the Valuation. Other tabs such as the “WACC” and “DCF” show you exactly how those calculations are being made and exactly how your assumptions translate into cash flows. We also provide each of the financial statements (Income Statement, Balance Sheet, Statement of Cash Flows) as well as a multitude of Metrics and Ratios. All of this additional information is meant to aid you in adjusting your assumptions to arrive at an Intrinsic Value and make wiser investment decisions.

If you're interested in digesting any of the data used in this Valuation in more depth, check out our Data Feed. Everyone gets 500 API calls/day for free, and after that - we only charge you for the data you use. No expensive seat license.

 

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started. We're always available via our Support Page if you need help. 

Follow us on Twitter and LinkedIn and Like us on Facebook to stay up to date.

 

App Developers – Say Goodbye to Redistribution Fees

The World's First Financial Data Feed With No Redistribution Fees

With the unveiling of a new pricing model, Intrinio has not just opened a new door for app developers - we've knocked down the walls of an old system that left them paying steep fees for the ability to feed data into their creations.

AFFORD

App developers and investors alike have historically been charged outrageous fees for access to financial data. At Intrinio, we believe this access should be affordable and accessible to everyone - especially those who are turning that data around and creating valuable innovations. Our new pricing model is architected ideally for startups and developers. We've completely ditched the seat license. You only pay for the data you use. This means that we're only successful if you and whatever you are building is.

Let's grow together. 

REDISTRIBUTE

Apart from eliminating the seat license, we've completely done away with redistribution pricing. It doesn't matter to us if you show off our data, and we want to support your products and innovations without breaking your bank. App developers pay the same price as regular/individual users or financial professionals. For the first time ever, integrate and display financial data wherever, and however you want. We're here to eliminate your roadblocks.

Build without restrictions. 

MANAGE

Our REST API is built with a flexible user interface that allows you to manage an unlimited amount of collaborators from one account. Have a team of 10 app developers? Add them as collaborators, manage their usage from your admin dashboard, and all of their API calls are logged to your main account. You won't be charged for 10 expensive seat licenses - you'll only be charged for the data your team uses. 

Support your team.

 

WELCOME TO #DATAFREED NOT #DATAFEED

Get started for free today by visiting www.intrinio.com. Register with your email, visit our pricing page, and check out our documentation or Youtube videos for help getting started. We're always available via our Support Page if you need help. 

Follow us on Twitter and LinkedIn and Like us on Facebook to stay up to date.

Financial Data – A Radical Change in Pricing

Say goodbye to the seat license.

At Intrinio, you only pay for the financial data you use.

Last week we decided to do away with an age-old pricing model in the financial data industry. For years, investors have been constrained within a pricing model that leaves them overpaying for data (and let's be honest - "sharing" their seat licenses among the whole team). On average, you only use 10% of the data from your expensive data subscription. The model doesn't work, and it isn't fair to users of financial data.

So we changed it.

The Intrinio Financial Data Feed is now priced based on your usage. You can start for free at 500 API Calls. We have pricing Tiers that go all the way up to 1,000,00 Average API calls per day - and more. Our Pricing Tiers are flexible, so you can move up and down depending on your usage. View our new pricing!

Add as many collaborators to your account as you'd like. These unlimited collaborators are all easily managed by the administrator under one account, and their API usage is applied to that account.

This video shows you how to manage, add, remove or group individual users within your account from one location.

We also won't charge you anything extra to redistribute our data. Seriously. Post it on your blog, integrate it into your app, tattoo it on your bicep. Most financial data firms will charge you steep fees for this - but honestly, we don't care. Redistribute away.

At Intrinio, we believe in transparency and flexibility. Our job is to provide you with financial data and resources easier, faster, and more affordable than ever before. Every morning we wake up with the mission of removing your roadblocks. It's not just a Data Feed, it's #DataFreed.

Break free of the old financial data pricing model, and get started for free today.

#LosetheSeatbelt #DataFeedDataFREED #DataFreed

 

FinTech Sandbox Welcomes Intrinio as a Data Partner

FinTech Sandbox, a nonprofit whose mission is to promote entrepreneurship and innovation globally in the financial technology sector, today announced a new data partnership with Intrinio. Intrinio will provide residents of the FinTech Sandbox program with free access to their flexible, dynamic, cross-platform financial data feed.

FinTech Sandbox facilitates free access to financial data and infrastructure for highly qualified FinTech startups. The Sandbox is an industry-lead organization that doesn’t require equity or fees from residents who are selected into the program. Instead, residents are expected to collaborate with each other in order to share learning and promote advances that benefit the entire FinTech ecosystem. The six-month program includes:

  • A robust set of data feeds and APIs from a wide array of data partners
  • Cloud hosting from industry-leading infrastructure partners
  • Membership in a vibrant, global FinTech community

Intrinio is offering FinTech Sandbox participants access to the following types of data:

  • Last Stock Price Data: 50,000 securities
  • Historical Stock Price Data: 8,700 securities
  • As-Reported Financial Statement Data: 7,000 securities
  • Standardized Financial Statement Data: 3,500 securities
  • Basic Company Information
  • Hundreds of Metrics and Ratios
  • Sales, Growth & Earnings Estimates
  • Pricing Data for 16 Indices
  • Economic Data

Intrinio enables users to access its financial data through their API, Excel add-in, and Google Sheets add-on. FinTech Sandbox residents can interface with Intrinio financial data using different platforms, including Apple, Microsoft, or Google products. The Intrinio Data Feed is the only true cross-platform provider of financial data, offering startups and developers an unprecedented degree of flexibility. The Intrinio Data Feed is dynamic and continuously updated, and new data sets are added frequently.

“I’m thrilled to announce our partnership with Fintech Sandbox,” said Rachel Carpenter, Co-Founder and Vice President of Intrinio, “because Intrinio was founded in response to many of the same challenges these financial technology startups face. We invented a solution that makes high quality financial data available at prices students, individuals, and startups can afford because we knew they were being priced out of the market. The companies working with Fintech Sandbox are inventing their own industry transforming technology, and we are excited to play a part in their success.”

“Intrinio shares FinTech Sandbox’s belief that highly qualified FinTech startups should have affordable access to financial data and resources,” stated Jean Donnelly, executive director of FinTech Sandbox, “Our residents are creating innovations that bring new efficiencies, speed, and flexibility to financial services - the same kind of benefits that Intrinio brings to the arena of financial data. This shared vision makes Intrinio an excellent partner for our startups.”

About Intrinio

Intrinio is a financial data firm that provides investors, developers and entrepreneurs with access to cross-platform, investment-grade data at disruptively low prices. Users can access the Data Feed via an API, Excel add-in, and a Google Sheets add-on. Intrinio is the only cross-platform provider of financial data. Users can access it anywhere, anytime from any device (Apple, Google, and Microsoft products). As the only financial data provider compatible on Mac OS X and in the cloud, Intrinio strives to deliver an unprecedented level of flexibility. In addition, Intrinio provides access to a collaborative valuation engine online where users can analyze the intrinsic value of publicly traded stocks. Intrinio was founded in 2012 and is headquartered in St. Petersburg, Florida. For additional information, visit http://www.intrinio.com or email admin@intrinio.com.

About FinTech Sandbox

FinTech Sandbox is a Boston-based nonprofit founded to promote financial technology innovation globally by providing free access to critical data and resources to FinTech entrepreneurs and startups. Sponsors include Fidelity Investments, F-Prime Capital, Thomson Reuters, Silicon Valley Bank, Amazon Web Services, Intel, SIX Financial Information, Goodwin Procter, and .406 Ventures. For more information, please visit http://www.fintechsandbox.org and https://twitter.com/fintechsandbox.

 

To view the original press release or download a PDF version, please visit: PR Web - Fintech Sandbox Welcomes Intrinio as a Data Partner.

Stock Index Data Now Available Through Intrinio

The team at Intrinio is pleased to announce that we now offer Stock Index data!

In an effort to continue providing our customers with the fastest, most flexible, high-quality financial data, we have officially expanded our data set to include Stock Index data.

Intrinio Stock Index Data Example API Request

We now offer:

  • Name of Index
  • Country
  • Historical AND 15-Minute Delayed Pricing Data
  • Pricing Data: Open
  • Pricing Data: High
  • Pricing Data: Low
  • Pricing Data: Close
  • Pricing Data: Change in Price
  • Pricing Data: % Change
  • Pricing Data: 52-Week High
  • Pricing Data: 52-Week Low
  • Pricing Data: Volume

For the following Stock Indices:

  • AORD -> ASX All Ordinaries Index
  • CACD -> French CAC 40 Index
  • COMPQ -> Nasdaq Composite
  • DAX -> German DAX Composite
  • DJI -> Dow Jones Industrial Average
  • FTSE -> London FTSE 100 Index
  • HSI -> Hong Kong Hang Seng Index
  • NDX -> S&P 100 Index
  • NIKK -> Tokyo Nikkei 225 Index
  • NYA -> NYSE Composite
  • RUT -> Russell 2000 Index
  • SPX -> S&P 500 Index
  • SSEC -> Shanghai Composite Index
  • STOXX50 -> STOXX 50 Europe Index
  • TA100 -> Tel Aviv TA-100 Index
  • WLSH -> Wilshire 5000 Total Index

The indices are called with a ($) in our Intrinio functions =>

Example: =IntrinioDataPoint("$SPX","close_price")

Visit our main page to get started. When you register you'll receive a free 10-day trial and you can immediately get started accessing the Stock Index data. Contact us at any time for pricing or support by clicking the green "Help" button in the lower right hand corner of your screen.

For those of you that are already registered, please be sure you have downloaded and are using the most up-to-date version of the Excel add-in, which can be downloaded on the "Data Feed" page of our site.

When you download the Intrinio Excel add-in, there is a template in the add-in folder called "IntrinioSecurityPrices.xlsm". This template is a great way to get started understanding this data set and how you can leverage the API, Excel add-in or Google Sheets add-on to digest our stock index data.

In addition to Stock Index Data we offer a wealth of financial data:

  • Last Stock Price Data: 50,000 Securities
  • Historical Stock Price Data: 8,700 Securities
  • As-Reported Financial Statement Data: 7,000 Securities
  • Standardized Financial Statement Data: 3,500 Securities
  • Basic Company Information
  • Hundreds of Metrics & Ratios
  • Sales, Growth & Earnings Estimates
  • Pricing Data for 16 Indices
  • Economic Data

We welcome all comments, suggestions or feedback – so don’t be shy. Shoot us a message at any time.

Let's Grow Together.

Financial Data API – Intrinio Data for Developers

The dawn of the API is officially upon us. This new trend in software engineering and system-to-system interaction is being emphasized by many tech though leaders including Intel CEO Brian Krzanich, but a recent Tech Crunch article put it best:

"It’s called API-first design, and it presents a tremendous opportunity for developers who adapt — not to mention a major risk for developers (and companies) who don’t."

The API-centric focus of many of our tech giants (Apple, Google, Intel, IBM, Oracle, Salesforce, Expedia) and the resulting and familiar household names and products (Apple Watch, virtual reality, literally any app that you use...) are a testament to the power and prevalence of APIs.

Twilio founder James Parton issued a warning over a year ago:

“APIs  are going to be the driver for the digital economy and unless they [companies] are talking about APIs already, they will be left behind.”

Intrinio Splash Image - Financial Data API

The advent of the API has recently started to take shape within the financial data industry. The speed of transactions, availability of information and emergence of high frequency trading has changed the way we invest. Just this week Goldman Sachs announced they will be disseminating their earnings report through twitter, leaving behind more traditional media methods. To compete in today's investment world, we need data faster - and we need it more flexibly.

Enter the Financial Data API.

 

Large data giants like Bloomberg and Thomson Reuters are typically very restrictive and don't make it easy or affordable for investors or companies to access their APIs. New entrants in the financial data market such as Quandl and Xignite are transforming the landscape by listening to customer needs and delivering a more accessible product at a lower price point.

At Intrinio we built a unique solution to the changing investment and financial data landscape. Beautifully crafted and elegantly simple, our data feed is available through a flexible, straightforward REST API...

and it's the most affordable Financial Data API on the market.

 

Intrinio Financial Data API - Excel add-in - Metrics & Ratios

The Intrinio Financial Data API enables developers to instantly integrate and build seamless, dynamic systems and applications to digest Intrinio data.

The Intrinio Financial Data API offers affordable, extremely flexible access to a wealth of financial data:

  • Last Stock Price Data: 50,000 Securities
  • Historical Stock Price Data: 8,700 Securities
  • As-Reported Financial Statement Data: 7,000 Securities
  • Standardized Financial Statement Data: 3,500 Securities
  • Basic Company Information
  • Hundreds of Metrics & Ratios
  • Sales, Growth & Earnings Estimates
  • Pricing Data for 16 Indices
  • Economic Data

To get started, visit our main page and register with your email. You'll receive a free 10-day trial and can get started working with our API immediately. Contact us for pricing at any time by clicking the green "Help" button at the bottom of your screen. We'll help create a plan that fits your needs.

The Financial Data API is the framework for the future of investing, and we're here to help you be a part of it.

Let's grow together.

 

We welcome all comments, suggestions or feedback - so don't be shy. Shoot us a message at any time.

Women in Fintech: Rachel Carpenter’s Intrinio

One of the co-founders of Intrinio, Rachel Carpenter, was recently featured on the Female Entrepreneurs Institute website - a highlight on women in fintech. We've re-posted the article below:
Women in fintech: Rachel Carpenter and her founding team at Intrinio

Women in Fintech: Rachel's Story

Hungry. Humble. Hustling to close the next big deal. Rachel Carpenter, founder of Intrinio, has big plans (she's already signed Harvard Business School). She's interested in disrupting financial valuation and creating efficiencies in how we know where it's best to invest. Here's her take on being a woman entrepreneur in the investment sector!

What inspired you to start Intrinio? Where did you start and where are you now?

Intrinio provides investors, entrepreneurs, and students with disruptively affordable access to high-quality financial data. We’re the only financial data providers available in the cloud and on Mac OS X—our cross-platform compatibility enables our users to flexibly access the data anywhere, anytime, from any device. We’ve also built a transparent, flexible online engine for valuing companies.

During my education as a finance student it was easy to see multiple inefficiencies in the industry—problems that needed to be solved through the use of technology. Just one afternoon spent waiting in line for access to an expensive data feed with a horrible user experience is enough to make you want to build a better solution. My co-founder and I refused to accept the “way it’s always been” in the financial industry.

Almost three years ago we were fresh out of school. We had a massive prototype in Microsoft Excel (40 pages long), no access or control over our own data, and zero funding. We were working through the night (this hasn’t changed much), sleeping on couches, and teaching ourselves web development. Today, my co-founder and I are advanced programmers. We’ve raised substantial funding and our team has grown to 7. We built our prototype into a web application. We also built a proprietary automated backend solution for gathering and standardizing financial data, and we own our entire data set (over 37 million data points). We’ve closed multiple large clients and are growing rapidly. It’s been a long couple of years—but with passion, persistence, and a little bit of patience, things truly start to blossom.

What do you see for your future?

We’re ramping up our marketing towards developers and startups—we’ll be the best source of affordable financial data integrations for other entrepreneurs. This year we’re also going to build our platform out to support private company valuation—then things will get really interesting. We’ll begin gathering some very valuable sentiment data from both public and private company valuations. In the next few years, Intrinio will become the go-to engine for valuing any type of investment opportunity. We’ll grow to be one of the most affordable and valuable data resources in the industry.

What do you see as challenges for you and your business? What are some opportunities?

Intrinio has faced plenty of challenges already, but our team is extremely agile. We’re flexible, yet resilient. One of the largest challenges facing any entrepreneur is fundraising. I think it goes without saying that being a woman sets you back before you even begin the process. Being young doesn’t help either—especially in the South. We’ve been lucky so far to find investors that understand the magnitude and value of what we’re building as well as the tenacity of our team and our ability to execute regardless of our youth. Fintech is a challenging arena to play in. We know the quality of our data surpasses that of traditional data feeds, but that’s difficult to explain to those who are ingrained in the old systems. Data is also becoming more of a commoditized product every day, which is why we have mid- and long-term strategies in place that don’t rely on the revenues generated from this part of our business.

Women in fintech: Rachel Carpenter and her Intrinio co-founder, Joey French

How can we help Intrinio succeed?

We’re on the lookout for any fintech startups or developers building apps who can’t afford inflexible, expensive financial data integrations. We offer disruptively affordable, easy to integrate access that will revolutionize the products that they are building.

We’re hoping to close out the rest of our current funding round within the next couple of months. If anyone knows a fintech investor or fund that would like to hop on board and help us disrupt the changing financial industry—send them my way!

Where did you grow up? And how is where you came from material to your identity as an entrepreneur?

In my personal life, I have a passion for fitness and exercise. I’ve always been extremely competitive. I competed in tennis and soccer growing up, I competed as a Division 1 Rower in college, and most recently I’ve competed in my first NPC bikini bodybuilding competition. My competitive nature has been essential while building Intrinio. I’m from a city in Wisconsin called Oconomowoc. It was a fantastic place to grow up. It had the small-town community but was close to major cities, it was scattered with beautiful lakes and plenty of outdoor places to enjoy the seasons, and it had great schools.

I certainly didn’t have a rough childhood. It was more the societal norms that set me on a different path, as well as the sentiment of my classmates in college. Most of the kids I grew up with ended up following the path you’re “supposed” to take—go to a decent public school, get a solid degree, then get a job working for a large company like Target or Edward Jones that recruits heavily at your school. I assume, to most students, this offers a degree of comfort and certainty heading into the scary land of adult life. For me, it just meant succumbing to the expectations of society and spending your time creating value for someone else rather than for yourself. It didn’t interest me. Growing up amidst this Midwest culture of “head-down, follow-the-rules, get-in-line” certainly influenced my desire to branch out, build, create, and break the rules.

Tell us a story about a success in your business and a mistake you overcame.

We recently closed a deal with Harvard Business School, and we’re officially providing unlimited access to our data feed to all HBS students. It’s exciting exposure for us, and we’re thrilled to know that the next generation of top finance professionals will be using the latest and greatest in financial data and tools. It came as a direct result of hustle—my co-founder and I flew out to Boston to physically meet with the librarian and show her how much value we could provide to the education of HBS students. Of course there are also mistakes. We came really close to partnering with a large data firm way too early in the game. We made it through a month or two of working with them before we realized it was a bad move. We were too young of a company, and we would have had to give away a substantial portion of equity and control to partner with them. We graciously and professionally cut ties with them and went on to build everything we needed ourselves, retaining all of that value and keeping everything in-house.

What picture is on your phone’s home screen?

It’s a picture of me with my family. They’re everything to me, and they’re a huge part of why I’ve been able to take the risks I have. They’ve supported me my entire life and helped me grow into the woman that I am today. They keep me sane and balanced, and I’m forever grateful to them.

What do you love about being an entrepreneur?

Every single day you are learning and embracing the creative freedom that comes with being in control. It only works if you’re an extremely self-motivated person, which is easy for me because I know every single day when I wake up that I’m creating value for myself and my team, and nobody else. Lastly, you’re forced to learn how to fail—hard and fast. Eventually you become so willing to fail that you’re learning more rapidly than ever.

What about your business matters most deeply to you? How does it engage your values?

I believe strongly that there is always a better, faster, more efficient way to do things. I get absolutely peeved by those who are stuck in the past and live under the assumption that they have to accept the way things are.

Intrinio is built on a foundation of automation and efficiency. The residual effect of this is that our resources are more affordable—which means we are able to provide them to the masses on an unprecedented level. Our data and tools are enabling a powerful generation of developers to build game-changing products. Our resources are empowering the next generation of investors to make wiser, more informed investment decisions. Knowing that our solutions are supporting these doers, makers, and game-changers helps fuel my fire. It gives me hope that our generation will continue to break the rules, push the envelope, and build solutions that actually make a difference.

What would you say is your “entrepreneurial superpower?”

You could call me a multitasking, tenacious hustler. I’m uncannily good at handling a multitude of things at once. I perform extremely well under pressure while juggling a hundred responsibilities. I can soak up information, analyze it, recall it, and most importantly act on it with extreme tenacity. I’m great at pulling the strings to simply make things happen when they need to come through. In other words, I hustle. I’m also a people person through and through. I can relate, sympathize, empathize, and get along with just about anyone, and being good at “people” has been integral in getting Intrinio to where it is today.

Which entrepreneur do you admire most right now?

Elon Musk.

Why Elon?

Mostly because he is not following the lean startup mentality. There is so much emphasis and education right now that idolizes and focuses on prioritizing the “lean startup,” but true innovation doesn’t come about by solving problems and looking only at what’s in front of you. It grows in the hearts and minds of fearless entrepreneurs who have a vision for the future and dream of the possibilities most of us can’t even see. Great innovations like Apple products weren’t solving a “problem”—people were happy with their clunky products and terrible user experiences. They couldn’t see a better way until it was put in front of them. In fact, Apple, Facebook, and Google all improved upon products built by startups that were following this mentality and then dominated them. If we think bigger—about not just our industry or economy but about society moving forward as a whole, progress is stalled when we solve only the problems we can see directly in front of us. Elon is unapologetically building things without asking for your permission, creating and affecting change, and for that I admire him.

What’s the best and the worst thing about being an entrepreneur, as a woman?

The worst thing about being a female entrepreneur is not being taken seriously. I’ve actually been asked “do you have a guy that you work with to help you with all of the hard stuff like math?” I can’t even count on both hands the number of “potential investors” who made inappropriate advances. I’ve had my business called a “cute project” dozens of times. I’ve had my clothes criticized. Most people assume I don’t play a technical role in my company. When I’m not taken seriously, it can be the worst kind of frustration. I do my best to shake it off and carry on, but I’d be lying if I said it wasn’t entirely disheartening at times. Choosing to build a business as a woman is not an easy road, but I can assure you that it is worth it. On the bright side, I love the dynamic that I have with my male co-founder. My strengths compliment his weaknesses and vice versa. We bring the best of both worlds to the table, and together we are an unstoppable team.

Do you think male entrepreneurs are “different” from female entrepreneurs?

I wish I could say no. I’ve constantly struggled to be perceived as “one of the guys” and be treated just like every other male founder. But men and women are inherently different, so the way that we build and grow companies is different as well. There are “feminine” traits that give women an entrepreneurial advantage, but we certainly have our disadvantages. We all know that women can multitask and men can’t. We’re intuitive, empathetic and compassionate. We know that men are more dominant and competitive than women. They’re assertive, and they’re natural risk takers. However, this is not a one-size-fits-all answer. I’ve met women who are more direct and commanding than any male founder I’ve known, and I’ve met male founders who are astoundingly soft-spoken and introverted. I’ve seen incredibly emotional male leaders, and I’ve seen women with a scary level of competitiveness. Unfortunately, many of the traits that female entrepreneurs exhibit come as a direct result of the societal pressures, assumptions and norms imposed upon us. Some of us are submissive for fear of being perceived as “bossy.” On the other hand, it’s been proven that men and women can produce the same results and the male is perceived as more effective. This can make us more competitive and aggressive. I’d say we have an edge because most people aren’t expecting what we bring to the table. Hopefully that changes. I plan on being a part of it.

What the best advice you ever got, and from whom?

My dad used to sign every letter or note he left me with two simple words “Hungry & Humble.” It’s left such a lasting impression on me that I had it tattooed on my wrist in his handwriting as a constant reminder. Staying hungry in all aspects of life is so important to me. It drives me forward and ensures that I’m constantly striving to do more and do better. He also taught me the concept of humility. I strive to live my life always assuming I might be wrong—that in every case there might be a better way. I embrace the fact that I don’t know everything. There is always more to learn. I’ll never forget my roots, where I came from, those who are less fortunate than me or those who are far superior. This does not come at the expense of my dreams, my desire to succeed, or my drive and tenacity. The balance of hunger and humility is the recipe for success, and it’s the best advice I’ve ever received.

How can our readers keep up with Intrinio and contact you?

Twitter: @Rachel_Ann_C @intrinio

Facebook: https://www.facebook.com/intrinio

Website: https://www.intrinio.com/

Fintech’s Biggest Nightmare – Bloomberg’s Fortran

Bloomberg's Codebase Unsurfaced

The fintech community has circled around a recent post (which is actually a re-blog from a 2006 article by John Sullivan) which unearths the fact that Bloomberg, a multi-billion dollar financial software, data and media company - has built their infrastructure with an archaic programming language called Fortran. Fortran would give most fintech firms nightmares.

For those of you unfamiliar with the rise of computing and programming, Fortran is a programming language that was developed in the 1950's by IBM. It's a powerful language for scientific and numeric computation - but this language is 65 years old. As the author notes:

"Apparently, Bloomberg has been trying to make the jump from Fortran to C++ for some time, but the Fortran codebase and the guys that maintain it are too entrenched. Cripes – in the oil industry we made that transition 15 years ago !"

fortran code gives fintech developers nightmares

The Issue With Overhead

Making the jump from one language to another on a platform of that size and significance is certainly not an overnight task. Yet a portion of this "failure to launch" is also due to the inherent inability of large, entrenched data firms and banks to be agile, flexible and innovative.

In the fintech space we like to highlight the concept of overhead in these large firms and how it can be such a hindrance ( think 25 million lines of Fortran). Inefficient overhead creates an opportunity for more responsive firms with less onerous code bases and smarter processes in general, allowing firms to compete through innovation. The very innovations that form the backbone of fintech are designed to create flexible, agile, and efficient processes that leave the concept of "overhead" in the dust.

Fintech - A Better Solution

Take Robinhood for example, who is slicing the overhead out of the brokerage process, or YCharts which squashes charting and analytics overhead.

From payments to portfolio management, and from blockchain to trading - fintech is taking the stage and bringing a competitive, lean edge that large traditional institutions are unable to replicate.  It's no surprise that we see banks such as Santander and Citi incubating young fintech startups and backing them with millions. Based in St. Petersburg, Florida - C1 Bank is ahead of the game developing internal technologies through "C1 Labs".

The team here at Intrinio is tackling overhead within the financial data industry. Our data feed is built on a contemporary framework utilizing modern, scalable technologies. We live and breathe automation at Intrinio, eliminating overhead, and building innovative solutions to age-old processes allows us to bring investors financial data faster, more efficiently, and therefore more affordably than ever before. We're fast, we're efficient, we're streamlined, and we don't use Fortran - we can promise you that.

Valuation snapshot from fintech firm Intrinio

Harvard Business School Partners with Intrinio

Harvard Business School Library Resources Page with Intrinio ListedStarting this fall (2015) Harvard Business School (HBS) professors and students will have free, unlimited access to the Intrinio Data Feed. The Intrinio Data Feed provides students with faster, cheaper, and more flexible access to investment-grade financial data.

Harvard Business School Library Database Resources - Intrinio

Harvard Business School students will become industry leaders...

“We’re extremely pleased to announce that we’re working with Harvard Business School,” says Intrinio Co-Founder and President Joseph French. “We recognize that access to high-quality data is of utmost importance to the educational community. I’ve personally experienced being barred from information during my education due to price hurdles, industry controls and lack of flexibility. These are not issues that the next generation of investors should have to deal with in their pursuit of an education. These students will become industry leaders. We’ve worked hard to ensure that they’ll have the most innovative and efficient resources at their fingertips while they grow.”

“Partnerships with the higher education sector, including Harvard Business School, indicate a growing interest in offering cutting-edge resources to students,” says Intrinio Co-Founder and Vice President Rachel Carpenter. “Our data feed provides them with unparalleled flexibility in their studies. Instead of waiting in line at the library for restricted access to an expensive service, they can access our data feed on their phone or tablet, from their dorm room, from an airplane – anywhere they want, providing a real-time experience. They can share financial models via Google Sheets. Students and professors are all hungry to be on the leading edge of tools and resources. It will be exciting to see the next generation of investors and developers leverage Intrinio’s resources in their work.”

As the first fintech startup to emerge from a budding entrepreneurial scene in Tampa Bay, Intrinio is challenging the traditional approach to finance through a culture of automation and a dedication to flexibility and transparency. Intrinio is introducing these innovations to both Ivy League institutions such as Harvard Business School and local institutions such as University of South Florida (USF).

“Being affordable is not the only way we are transforming a very traditional industry,” says Conor Farley, Director of Business Development at Intrinio. “We’re the only financial data provider available in the cloud. Our customers can use our data feed to build models in Google Sheets, giving them unlimited flexibility in where they access their tools and on what devices. We’re also the only financial data firm offering access and compatibility on Mac OS X, which is particularly useful for students. Unlike other systems, Intrinio is truly cross-platform – this is the future of finance.”

Now offering Financial Data on Over 8,000 Securities

Intrinio has recently expanded its financial data coverage to offer data on over 8,000 securities. New functionality offers a breakdown of common and preferred stock (and other securities) within companies when available.

As the only cross-platform provider of financial data, our users can access investment-grade financial data anywhere, anytime on any device. This means you can work on your models on your tablet on the plane, on your laptop in the office, or on your phone on the subway. Our Data Feed is compatible on Apple, Microsoft and Android devices. Each user has unlimited access to our entire financial database. It's our goal to provide you with the flexibility, affordability and transparency that has been missing in the financial data industry.

The Intrinio financial data feed includes: standardized fundamentals, as-reported fundamentals, historical stock prices, 15-minute delayed stock prices, basic company information, economic data, and over 120 ratios and metrics. 

income

Users can access our financial data via our API, Excel add-in, or Google Sheets add-on. This is not a data dump.  Utilize any of the easy-to-use formulas outlined in our documentation to flexibly query data into any cell in Excel or Google Sheets. Dynamicly drag data up or down and see it populate. Save and close - your data will be continuously updated.

It's very easy to sign up and instantly access a wealth of financial data. Simply visit www.intrinio.com, click Register, follow the steps, and you'll have a free 10-day trial to the Intrinio Data Feed. To sign up and find out more about pricing, please click the "Contact for Pricing" button or the green "Help" button in the bottom right hand corner of the website. This will put you in touch with the Intrinio team. We're ready to help!

Tutorial: Valuation Walkthrough

This short tutorial is designed to walk you through each step of valuing a company on the Intrinio Valuation Webapp.

The Valuation platform enables you to scenario test the value of companies under different circumstances. For example, you could run and save three different valuations that show the value of a company as a base case, bearish/downside or bullish/upside.

In this tutorial, we're going to calculate the intrinsic value of Tiffany & Co. (NYSE: TIF) under the scenario of a recession in 2016.

Step 1: Go to www.intrinio.com and sign in. If you have not already registered, click "Register" in the upper right hand corner and follow the directions.

Step 2: Click on "Valuation" >> "Create a Valuation" in the top header bar.

Step 3: A modal will pop up with two entry spaces. In the first entry box, name your Valuation "Tiffany & Co Recession Scenario". In the second entry box, type TIF. Click "Create".

Step 4. The Valuation will immediately open up, and you'll see your Valuation title at the top, as well as the Intrinsic Value, the most recent stock price, and the Margin of Safety.

The Intrinsic Value represents the inherent worth of a company. It is the present value of all of the future cash flows the company will generate. Typically, it differs from the current stock price. When the Intrinsic Value is lower than the stock price the company is overvalued, and when the Intrinsic Value is higher than the stock price the company is undervalued. The Margin of Safety represents the difference between the intrinsic value of a stock and its market price. In theory, the further a stock's price is below its intrinsic value, the greater the margin of safety against future uncertainty and the greater the stock's resiliency to market downturns. In short - a higher Intrinsic Value and a higher (and positive) Margin of Safety is better.

The Initial Intrinsic Value and Margin of Safety that you see at the top are simply a baseline. They are calculated based off of default assumptions derived from both Wall Street Consensus Data and Mean Reversion calculations. Valuation is as much of an art as it is a science - it requires human input. You'll want to adjust the assumptions used in the model to more accurately reflect the true intrinsic value of TIF during a recession. These initial numbers are simply a starting point.

Step 5: This first page we're on is the Assumptions page. We've boiled the Valuation down to 5 main assumptions that drive the DCF model. 3 Cash Flow assumptions (Revenue Growth, NOPAT Margin and Invested Capital Turnover) in a graphical form, and 2 Cost of Capital assumptions (Credit Spread and Company Specific Risk Premium) with slider bars. You can flexibly adjust all of these values here on the Assumptions page.

First off is the Revenue Growth graph. You'll see the historical data pull in on the left hand side and the default assumptions for future revenue growth populate on the right hand side. Given that TIF is a luxury goods company we will want to drop the Revenue Growth assumptions. Luxury goods companies do not preform well during recessions.

Click on the green dot above the year 2016 and drop it down to -1.64%. Drag 2017 down to -0.05%, drag 2018 down to 1.36%, and don't change 2019. (You can also double click on the dot and manually type it in.) Click the green "Save" button in the upper right hand corner. You'll see the intrinsic value re-calculate at the top.

Step 6: The next assumption is the NOPAT or (Net Operating Profit After Tax) Margin. For a luxury company like TIF, during a recession, we can expect this Margin to collapse as well. Click on the green dot above 2016 and drag it down to 12%. Drag 2017 down to 11%, drag 2018 down to 10%, and drag 2019 down to 10.25%. Click the green "Save" button in the upper right hand corner. You'll see the intrinsic value re-calculate at the top.

Step 7: The last cash flow assumption is Invested Capital Turnover. During a recession, it's typical for a luxury goods company to have stabilized Invested Capital Turnover. The default values here are already fairly stabilized, so let's leave this as it is.

Step 8: The first Cost of Capital assumption is the Credit Spread on the Cost of Debt.

This is an evaluation of the riskiness of the debt. Increasing it adds a premium to the Cost of Debt based on the risk that the company will default on their debt. The Credit Spread is calculated in Basis Points (bps). This is a common unit of measurement for interest rates and other financial percentages. One bps is equal to 1/100th of a percent (0.01% or 0.0001). In other words, a 1% change = 100bps and a 0.01% change - 1bps.

During a recession, debt becomes substantially more risky and more companies default. Let's raise the Credit Spread. Click and drag the green dot up the slider bar to 350 bps. Click the green "Save" button in the upper right hand corner. You'll see the intrinsic value re-calculate at the top.

Step 9: The last assumption is the CSRP (Company Specific Risk Premium). This additional premium has been added to account for company specific risk scenarios as well as any faults in the CAPM model. This is where you can account for any personal knowledge about the company or insights you've gained from research. Some factors to consider when increasing or decreasing this premium include:

  • Company size
  • Access to Capital Markets
  • Breadth of Customer Base
  • Geographic Area
  • Key Executive Dependency
  • Limited Product Line
  • Litigation/Regulatory Risk
  • Industry Volatility

For example, when valuing smaller companies, you'll want to increase the CSRP. The CSRP is a fairly long-term assumption, so it shouldn't be altered too much based on a recession in 2016. However, equity does become more risky during recessions, so let's increase this premium to 1.5%. Click the green "Save" button in the upper right hand corner. You'll see the intrinsic value re-calculate at the top.

And you're done! We've calculated the intrinsic value of TIF in the event of a recession in 2016 to be approximately $22/share and significantly overvalued. TIF would not be a wise investment in this scenario.

The only changes needed to complete a Valuation are on the "Assumptions" page. However, a wealth of additional information is provided within the Valuation. Other tabs such as the "WACC" and "DCF" show you exactly how those calculations are being made and exactly how your assumptions translate into cash flows. We also provide each of the financial statements (Income Statement, Balance Sheet, Statement of Cash Flows) as well as a multitude of Metrics and Ratios. All of this additional information is meant to aid you in adjusting your assumptions to arrive at an Intrinsic Value and make wiser investment decisions.

If you run into issues or have any questions, please feel free to contact us at any time on the Contact Page, or click the green "Help" button in the lower right hand corner of the screen.

Fintech: Replacing Humans or Making Them Better?

If you haven't heard of Fintech in the past few years, you're probably living in a Faraday cage. Fintech companies use technology to disrupt existing financial services. This entrepreneurial industry has sprung from disgruntled financial employees and even large banks themselves, bleeding into an industry that has historically resisted change, technology, and innovation. It encompasses everything from payments to trading, and there is no question that Fintech innovations are stirring up controversy.

It used to cost (at a minimum) between $200 and $500 to execute a trade in the stock market. Today, due to the rise of companies like RobinHood, you can execute a trade for free. Transferring money overseas used to be an arduous and expensive process, taking weeks to execute. Now companies like TransferWise are performing these transactions for up to 10x less than the typical bank. Robo-advisors like Wealthfront are eliminating the need altogether (especially among millennials) for a financial advisor.

It's easy to see why this revolution has some people worried. In many cases, the argument could be made that these companies are eliminating the need for many different financial services jobs and even for existing institutions altogether. But is it the case for all fintech companies? At Intrinio, we believe Fintech has the potential to improve existing businesses rather than eliminating them. Far from eliminating the need for the human touch in financial services, new technologies can increase the impact of these companies and their employees by providing the tools they need to provide value for their clients.

Intrinio's technology operates primarily within the realm of Valuation. We've built an application that automates a large part of the valuation process for publicly traded companies. A user simply enters a ticker, adjusts a few assumptions, and is given the intrinsic value or inherent worth of the company. Any seasoned Valuation professional will tell you that valuing a company is both an art and a science. The science is undeniable, typically relying on a discounted cash flow model (DCF), and the calculation of a weighted average cost of capital (WACC). Although the valuation relies heavily on these methods and calculations, human insight is invaluable to the model. For example, an analyst might know that pharmaceutical companies tend to perform well in recessions (so don't plunge those revenue growth assumptions quite so much) or that the cost of oil has risen substantially (so lower the NOPAT margin assumptions for your valuation of an airline with an unhedged gas position). No matter what, human input is and always will be of paramount importance in valuing companies.

Having come from both financial and technological backgrounds, the team at Intrinio fully understands the value of Fintech for human beings, and this knowledge forms the basis for the design of our platform. We wanted to build a technology that would automate the mindless parts of performing a valuation so that users can spend more time adding value where no machine can. Our Valuation platform doesn't eliminate the need for a human - rather it makes the job of valuing companies easier and increases the quality of analysis.

Intrinio is just one example of the ways in which Fintech is transforming the financial landscape. Not everyone is building technological innovations that enable humans to do their jobs better - some are building technologies that remove the need for human work altogether. But how much should this worry us? Is this a change we should resist? Even the big banks have begun to embrace these new disruptive companies, funding them, incubating them, and even acquiring them.

Peter Thiel, a well-respected entrepreneur, venture capitalist, early investor in Facebook and co-founder of PayPal, has spoken out against resistance to technological change. His discussion focuses mainly on robots, but the parallels are hard to ignore. He claims "It's a problem we would like to have...It would free people up to do far more productive things." The team at Intrinio has built our platform to do just that. We automate the repetitive, manual and mindless parts of gathering financial data and performing a valuation so that the user can spend their time more productively and focus on what matters. Time usually spent manually entering data or ensuring that formulas are calculating correctly can instead be focused on the assumptions driving the model.

While it's inconceivable to directly compare the Fintech revolution to the larger revolutions of the past, it's helpful to take a look back and compare. During the Second Industrial Revolution of the late 1800's innovations such as mass production and production lines significantly increased productivity. It took less people less time to make products because of the steam engine. Jobs were lost, but more were created. Intrinio’s platform allows analysts to produce more valuations in less time. As more of an analyst's time is freed up to focus their attention on details, the quality of their work will improve.

We see today, just as we did with the Industrial Revolution, a resistance to new technologies. Is this Luddism, or simply a concern for the future of human work? We have already begun to observe labor’s reaction to technological displacement. And while some Fintech companies are undoubtedly displacing workers, the argument can be made that they are being placed into more effective positions. At Intrinio, we strive to continue building technological innovations that create more efficient workers, higher quality work, and positive change within the financial industry.

How Intrinio’s Valuation Webapp Helps Value Investors

As value investors, we tend to live in the domain of spreadsheets. Value investing is the strategy of finding stocks that are undervalued relative to their intrinsic value, or inherent worth. The intrinsic value of a stock is the the sum of all cash flows that a company will generate in its perpetual existence, discounted at the weighted expected return of the debt and equity investors in the company. Traditionally, investors have used Microsoft Excel to build complex discounted cash flow (DCF) models to estimate the cash flows generated by the company and a weighted average cost of capital (WACC) model for estimating the weighted expected return for the firm. This practice is one of the primary activities of any financial/investment analyst and there is even a Financial Modeling World Championship to showcase the best of the best at this art.

While there are many reasons to build complex financial models in Excel, the intrinsic value of a company's stock can be calculated much more simplistically using a standardized system. This is what we've created at Intrinio. Our web application brings the flexibility of Excel onto the web without the complexity of a having to manage a spreadsheet filled with calculations or bad data. This makes it very easy for performing scenario testing, value driver analysis, or sensitivity testing. Merging this with an easy-to-use user interface, Valuation is exactly what value investors need to bring their investment analysis to the next level.

Because of the difficulty of managing financial models in Excel, most value investors tend to focus on Valuation ratios, such as the Price-to-Earnings ratio, the Price-to-Book ratio, the Enterprise Value-to-EBITDA ratio, the Enterprise Value-to-Revenue ratio, etc. Comparing these valuation ratios to those of similar companies, industry aggregates, or the S&P 500 aggregate, along with other performance metrics provides an indication of whether a company is over- or under- valued. Valuation ratios are in essence a single period cash flow perpetuity. A Price-to-Earnings ratio can be disaggregated to equal 1 / (Cost of Equity - Long-term Growth Rate) and the intrinsic value equal to next years expected EPS multiples by the calculated Price-to-Earnings multiple.

For example, Apple's cost of equity is 8.66% and has an expected long-term growth rate of 2.47% (1 / (8.66% - 2.47%)) equals a Price-to-Earnings multiple of 15.97x. Based on Zack's EPS Wall Street Consensus Estimate of $8.51 for the current year, the intrinsic value of Apple based on this basic model is $135.90, which is approximately 6% above the price of Apple of $127.39 as of April 6th, 2015.

While this simplistic model is nice for giving an approximate intrinsic value quickly, in many cases a single period perpetuity is not an accurate reflection of the company's strategy and earnings generation. For example, during a recession, a single period perpetuity would likely understate the intrinsic value of the company, given an expected rebound in revenues and margins in the coming years. A company may be making large capital expenditures in the current year, which are expected to generate greater revenues and margins in the future. Therefore, to assess the company's intrinsic value, a focus on cash flow generation based on the current company's strategy, the industry competitive landscape and the macroeconomic environment is much more complex than a simple approximation of the Cost of Equity and the Long-term Growth Rate.

With Intrinio's Valuation Webapp, we allow you to estimate the revenue growth, net operating profit margin after tax, and the invested capital turnover to forecast the free cash flows to the firm for the next five fiscal years. We also allow you to change the spread on the long-term debt to assess the riskiness of the debt and the company specific risk premium to assess the riskiness of the equity above or below that of a modified capital asset pricing model cost of equity. These assumptions combine to create a discounted free cash flow to firm intrinsic value model, which can help you calculate the intrinsic value of any company. Because of how simple it is to use Valuation, you can easily perform scenario testing, such as understanding what Apple is worth if there were a recession in 2016. The flexibility of this web application provides value investors an invaluable tool to make better investment decisions. We have taken the complexity of an Excel valuation model onto the web, while providing a user experience that makes it fun and easy to really understand how and why a company offers a high probability of a good investment opportunity.

The Four Horsemen of Tech – $AAPL, $GOOGL, $AMZN, $FB

The previous video was presented at the Digital-Life-Design (DLD) Conference, which occurred in January of this year. In this 15 minute clip, Scott Galloway discusses the Four Horsemen of technology: Amazon, Apple, Facebook, and Google. Each has carved its own niche in the modern technology world and plays a major role in the lives of most Americans and even most people in the world. With 1.75 billion smartphones in the world connected through the internet via mobile networks and wi-fi, we can begin to grasp the power that these companies have to shape the future evolution of technology.

At Intrinio, we offer full access to a whole host of financial data on these companies through our API, Excel add-in and Google Sheets add-on. We have used Intrinio data to analyze the trends observed by Professor Galloway. You can find all the supporting data in the Four Horseman Google Sheet, which was gathered using the Intrinio Google Sheet add-on.

Before we begin, it's interesting to make the observation that back in 2000, only Amazon and Apple were publicly traded companies. Amazon was a poster-child of the dot-com bubble and Apple was starting to find success in redefining itself. Google was beginning to make an impact on the internet with its revolutionary search engine and had just launched AdWords. Mark Zuckerberg was 16, had just transferred to Phillips Exeter Academy and was still four years away from launching The Facebook. The main point here is that 15 years ago, at the apex of the technology bubble in 2000, none of these companies had a dominate market position. Realistically speaking, only Apple had experienced major success. We can expect the next 15 years to be similar, with new entrants disrupting existing companies as technology evolves. However, it is likely that a major paradigm shift must occur for one or all of these players to lose their position as the Four Horsemen of the mobile era. Each of these companies are where they are today because they successfully transitioned their revenue models from a desktop environment to a mobile environment and were able to continue capturing market share as others failed to adapt.

Lets take a look at the recently reported last twelve months revenues and Zack's consensus revenue forecasts for 2015 and 2016 for the Four Horsemen:
[gdoc key="https://docs.google.com/spreadsheets/d/1LNRygMjOti7errtjSVPLUrU_Dj05m3bU1a1atbjF_2Q/edit" chart="Pie" title="Reported 2014 Revenue ($mm)"]

[gdoc key="https://docs.google.com/spreadsheets/d/1LNRygMjOti7errtjSVPLUrU_Dj05m3bU1a1atbjF_2Q/edit" gid="1961885633" chart="Pie" title="Zack's Wall Street Consensus 2015 Revenue ($mm)"]

[gdoc key="https://docs.google.com/spreadsheets/d/1LNRygMjOti7errtjSVPLUrU_Dj05m3bU1a1atbjF_2Q/edit" gid="830162448" chart="Pie" title="Zack's Wall Street Consensus 2016 Revenue ($mm)"]

As these pie charts illustrate, Amazon and Facebook are the current projected winners by Wall Street analysts, growing their revenues faster than Google and Apple. Apple is projected to increase its share in 2015, but slide slightly in 2016, while Google is projected to lose steam in 2015 and 2016.

When looking at the following graph, it is interesting to note that the profit margins of three of the Four Horseman are very close to one another. Amazon trails behind. This is largely expected since Amazon is the only primary retailer of the group and retailers tend to have much lower profit margins. However, its made up for in a high asset turnover. Yet what's most interesting here is that Amazon has made virtually no profit over the past 10 quarters.

[gdoc key="https://docs.google.com/spreadsheets/d/1LNRygMjOti7errtjSVPLUrU_Dj05m3bU1a1atbjF_2Q/edit" gid="627348650" chart="line" title="Historical Profit Margins"]

Professor Galloway's observation of Amazon is that it must open stores as flexible, robust "warehouses" to sell their inventory. Amazon's strategy is as "the last mile, last man standing", where Amazon leverages its cheap access to capital to build a massive network of fulfillment centers throughout the world. However, Professor Galloway notes per research by Satish Jindel that Amazon spent $6.6bn on shipping costs, but only brought in $3.1bn for shipping charges, leaving net shipping costs of $3.5bn. With 2014 revenue of $88.98bn, net shipping costs were close to 4% of total revenue. Amazon has historically had profit margins for the past 10 quarters on a trailing twelve months basis on average of 0.1%. Without the necessity to ship products to consumers, profit margins for Amazon would be closer to 3%.

[gdoc key="https://docs.google.com/spreadsheets/d/1LNRygMjOti7errtjSVPLUrU_Dj05m3bU1a1atbjF_2Q/edit" gid="1908684967" chart="Bar" title="Amazon vs. Brick & Mortar"]

When comparing Amazon (a pure-play online retailer) to Wal-Mart, Costco, and Target (mixed e-commerce and brick and mortar stores) it is clear that Amazon's margins would be closer to the average of these three players, around 2.5%. Since companies like Wal-Mart and Best Buy optimize their in-store pick up options, you can receive your items faster and potentially cheaper than Amazon - without the burden of shipping costs. Items are either already in the store or the store distribution system can be leveraged for a very low marginal cost versus sending a package via USPS, UPS, FedEx, or other accelerated shipping company. This means, as brick and mortar stores make it easier to pick up your items from their store (curbside pickup, for example) it now makes sense to use the e-commerce/brick and mortar shopping option to receive both lower prices and to get your product faster. Alternatively, leveraging services like Uber, the delivery process can be further optimized from store to front-door. This is something Amazon may struggle to adapt to due to its focus on delivery services such as the USPS. Professor Galloway hypothesizes that Amazon must acquire a brick and mortar company in 2015, with the likely candidates being Radio Shack, a major gas station chain or even the U.S. Postal Service. Otherwise, Amazon's achilles heel, it's net shipping costs, leaves the company vulnerable - especially if its cheap access to capital erodes.

Professor Galloway discusses Facebook's grip on the App Economy, wherein Facebook properties dominate all age groups with their Facebook, Facebook Messenger, Instagram, and WhatsApp mobile apps. While Facebook on its own is a dominant force, it is the acquisitions Facebook has made with its access to cheap capital that has propelled the company to its dominant position. Instagram was a phenomenal acquisition, where Facebook paid $1bn to acquire the company and it is expected to generate $250-400 million in revenues in 2014 and has over 300 million users. The worst acquisition, according to Professor Galloway, was Yahoo's acquisition of Tumblr for $1.1bn, which is expected to have "material" revenues and only has 200 million users.

The biggest concern for Facebook in 2012 was their ability to transition from deriving their primary revenues from their desktop-based webapp to their mobile applications. We can see in fiscal year 2012 on the previous profit margin graph that Facebook's profit margins slid to around 1% before their mobile advertising strategy began to pay off. The acquisition of Instagram was a key driver of this success due to their emphasis on visual and mobile. Engagement rates are extremely high on Facebook properties and the company has a unique position to understand user identities both within its ecosystem, but also on other Facebook connected apps. This unique value proposition for advertisers and the successful transition from webapp to mobile app for their advertising platform has now cemented Facebook as one of the dominant Four Horsemen. Facebook currently has the highest profit margin of the Four Horseman at 23.58% for fiscal year 2014.

As mentioned previously, Google appears to be losing market share. This is evidenced by its declining revenue growth relative to the Four Horseman and its falling profit margins, as seen on the profit margin graph. Google's Return on Equity, a measure of value creation for it's stockholders, has been declining consistently for the past 10 quarters. Google is losing momentum across the board in search volume, engagement rates and video posts. Also, Google+ and Google Glass are now deemed to be busts with no clear commercialization opportunities.

[gdoc key="https://docs.google.com/spreadsheets/d/1LNRygMjOti7errtjSVPLUrU_Dj05m3bU1a1atbjF_2Q/edit" gid="1283756845" chart="line" title="Return on Equity"]

While Google still has a dominant advertising service (AdWords) and a dominant position as the primary operating system in mobile phones (Android), it has seen its momentum slow in the past few years. However, Professor Galloway did not mention Google's opportunities for the future of the company, which includes self-driving cars, multiple bets on "the Internet of Things", and increasing bets in the life sciences technology sector led by the extremely active Google Ventures. Google has a significantly higher R&D Expense to Revenue compared to Apple, and is also very high compared to Facebook, which has much lower revenues. Therefore, we can see that Google is investing in the future, and likely making much more bold and expansive bets on the future compared to any of the other Four Horseman. With the Google ecosystem maturing and losing momentum, Google needs to hit a grand slam with one of its Google X projects in order to remain a dominant force for the next 15 years.

[gdoc key="https://docs.google.com/spreadsheets/d/1LNRygMjOti7errtjSVPLUrU_Dj05m3bU1a1atbjF_2Q/edit" gid="1869291543" chart="line" title="R&D Expense to Revenue"]

Finally. We are to Apple. The glamorous King of the Four Horseman. Professor Galloway describes Apple's luxury brand competitive advantage based on its attention to craftsmanship, its iconic founder, its ability to achieve an exceptional price point, its complete vertical control of its value chain, its global reach, and its self-expressive benefit. It is these factors that allow Apple to continue dominating the other three horsemen. Professor Galloway focuses on the psychology that Apple has achieved that no other luxury or technology brand has ever achieved in modern history. He asserts that the luxury brand Apple has built implies that by owning an iPhone you are a better mate and are more capable of providing a prosperous future for offspring. He shows several graphs overlaying Apple iOS and Andriod on maps of New York City and Los Angeles to show that the higher income parts of the city use iOS. Apple products have become a modern day status symbol. This is extremely difficult for any company, especially a technology company, to achieve and is a major driver for why Professor Galloway believes Apple will be the first $1 trillion brand. Ironically (or not), the Intrinio intrinsic value (based on the default assumptions of Wall Street consensus growth and mean reversion margins) implies that Apple has an intrinsic value of just less than $1 trillion. As seen on the Return on Equity graph below, Apple has consistently achieved a higher Return on Equity for the past several years, illustrating its dominant position for creating value and its place as Professor Galloway's King of the Four Horseman.

[gdoc key="https://docs.google.com/spreadsheets/d/1LNRygMjOti7errtjSVPLUrU_Dj05m3bU1a1atbjF_2Q/edit" gid="410508477" chart="line" title="Return on Equity - Last 6 Years"]

While presentations such the one delivered by Professor Galloway at the DLD15 Conference help us understand what top technology thinkers are forecasting as the future prospects of dominant companies like The Four Horesmen - there is no substitute for seeing the data for yourself and making your own conclusions. Professor Galloway has a whole team of researchers working with him to gather all the data points used in his analysis of the technology industry. We have made it extremely accessible to access all kinds of financial data and ratios for every publicly traded company in the United States. This means you can draw your own conclusions on industries and sectors including their investment prospects. In addition, we created a valuation engine to help you understand the intrinsic value of these companies, so you know you are buying a company with positive investment prospects at a great price. Many times great stories are already baked into the stock price, leaving little room for error in the execution of the company's plan. We help you see the whole picture so that you can make a well informed investment decision.

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Intrinio – Investing. Redefined.

We have been hard at work over the past several months building the first investing community of its kind - a complete ecosystem for financial data and investment analysis. Intrinio features a robust and transparent Valuation WebApp, a comprehensive API with Excel Add-in, and a collaborative platform for discussing investment prospects.

While we still have much work to do, we are making our beta app available for testing and feedback.  You have the opportunity to tell us exactly what you want us to build. This includes everything from views of certain data in the Webapp, to data sets delivered by the API/Excel Add-in, to companies you would like for us to cover.

We are in the process of writing documentation for everything, specifically the API and Excel Add-in, so in the mean time, please feel free to ask any questions in the Forum. We will do our best to respond within a few hours.

Thanks for the interest in Intrinio. We are very excited for what the next several months will bring.