EquitiesLab is an investor’s dream. When using our prebuilt strategies investors will know what to buy and when to buy it. There are more than 100 strategies already built into the software, and more are released all of the time. Stop waiting in the past, join the future and start living the dream today with EquitiesLab.


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Quantitative Stock Screener and Backtester

Equities Lab lets you screen, backtest and manage your stocks.  Know why you bought any given stock, and when you should sell it.  Our stock screener finds the stocks you want, using quantitative criteria you set.  Our backtester tells you whether these quant strategies generate alpha, and the watchlists keep your implementation on track.  You can use our charting tools and vast data to dig into a stock’s fundamentals, and understand why it is doing what it is doing.
Check out our screening feature…

Heat map of stocks matching an investment strategies and doing well

Several strategies, in a heat map, all outperforming

Serious research

A table of stocks together with fundamental and technical data, colored by performance

A table of stocks together with fundamental and technical data

Serious quantitative investors end up using Excel, one or more software packages, and lots of math. Use our complete financials on 18,000 stocks covering the last 20 years to validate your strategies — worry free. Our data comes from Morningstar, with macroeconomic data from Quandl, and we cover data from “Accounts Payable” through “Non Current Deferred Assets” to “Write Offs”. We also include “Market Cap”, Close, Volume, and PE in our hundreds of properties.Check out our data…

Does your trading strategy generate alpha

Fundamental quantitative investment strategies seem to be the answer. But, does your trading strategy blend? More formally, do you make excess returns over the market by following your combination of factors. Validating this requires gigabytes of data, programming expertise and attention to detail — all of which we have. We use a lookahead bias free, survivorship bias free, point in time dataset. This allows you to see what would have happened had you used your strategy in the past.

You’ll see where your alpha is coming from, and be able to figure out why. Then, you’ll want to tweak it. Then you’ll want to validate that it still works. Change the rebalance period, so you trade monthly, instead of once a quarter, and see if it still works. Then try once every two weeks, or midway through each month. Add stop losses, minimum holding periods, or more. You can’t exactly backtest real life in Equities Lab, but you can come close. You can see how your strategy did, what it bought, how each position did, and more. Learn more about our backtests…

A backtest chart of Value Hybrid 20 generating massive alpha versus the S&P 500

A backtest chart of Value Hybrid 20 generating massive alpha versus the S&P 500

Express yourself

The Piotroski score expressed a formula in Equities Lab

The Piotroski score expressed as a formula in Equities Lab

Structure your formulas and ideas any way you want. You can test almost any financial anomaly with Equities Lab and see if it generates excess return. We can easily express any of the Fama French factors, see how Quality Minus Junk works, or create and validate your own anomaly.  You get auto-completion, a helpful field and operator reference, and built-in help every step of the way.  For instance, people like to use the Piotroski score to filter stocks.  Piotroski score is a nine point checklist, and a good Piotroski stock would have to match seven of these nine conditions.  Checking this in Equities Lab is easy to do: it takes ten statements — nine for the condition, and one for the count and comparison. Similarly, finding the stocks that are the second cheapest 10% of some valuation metric is easy.  If you want to filter companies before you rank, and you want to collate by industry or other segment, you just do it. It is literally easier to do than to describe.  Here are the ten statements (we just took a screen grab of our built in formula). Learn More About the Editor…

Big Data Analytics applied to the stock market

Investing in the stock market requires big data, which we have.  We can summarize the state of the entire market in a few clear lines, in a few seconds.  We can focus in on a sub sector, or a slice based on company size, or analyze one of the P/E quintiles in more detail.   If you want to know whether highly leveraged companies are overvalued versus their historical average, or whether airlines are outperforming small cap technology, you can see it on a handy chart. See this data crunching in action….

Backtest with multiple industries

Backtest with multiple industries

Think deep

Scatterplot for screener

Scatterplot for screener

We give you access to information buried in the books of thousands of companies. For example, you can test the changing inventory levels and accounts receivable of all companies over 20 years using our Morningstar data set. We have the companies that trade today, as well as the ones that are but a distant memory. You can take these comparisons and rank across their peers in their sector. Then you can see how this ranking changes over time, and select the companies that are moving in the right direction.

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