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

## 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.

### 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.

## 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

Market Cap

### =IntrinioDataPoint(”ticker”,”marketcap”)

=(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

Stock Price Over 21 Day Trading Period

(most recent divided by previous period minus 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)

## Two Months Excess Return

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

## Six Months Excess Return

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

## Twelve Months Excess Return

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

## 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!

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.

# 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.

## 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.

# 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.

# 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.

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.

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.

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
• 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.

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

## 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.