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Apr 24 2018

What’s in the FastTrack Stocks Database?

We’ve posted in the past about the decreasing number of investible stocks in the US (https://investorsfasttrack.com/is-passive-active/). Per the post, there’s about 3,000 investible companies listed in the US. But, FastTrack has approximately 4,500 stocks in the database. What makes up the difference?

First, FastTrack tries to include every stock listed on the NYSE and NASDAQ exchanges (including NYSE Arca and NYSE American). Those exchanges both have their own price, market cap, and volume requirements for listing/maintaining a listing. We update new listings/ discontinued issues as they IPO and/or approximately every month.

Adding all NASDAQ and NYSE tickers brings us to approximately 4000 tickers. Next, we take any liquid, large and mega cap over the counter ticker and add those in. Those names are typically international companies such as Tencent Holding, Royal Dutch Shell, Nestle SA, HSBC Holdings, Toyota Motor, etc. Typically there are 300-400 such tickers, rounding the database out to ~4,500.

There are thousands more OTC tickers out there, but the data quality and investability of those assets are low, so we can’t include them in the database.

Now, with all those tickers at hand, it’s very useful to sort and sift those securities with the the FT Cloud or FastTrack family sieve. In the screenshots below we’ll use the FT Cloud family sieve to analyze all liquid large securities.

  1. Sign in to FT Cloud, click the “Spreadsheet/Chart” tab, then click the “Load Family” in the upper right corner.
  2. Expand the Stocks >> Avg Volume Trees on the left of the new window
  3. Select each of “Volume-Over 5 Mil” then click “Add” in the upper right
  4. Select each of “Volume-1-5 Mil” then click “Add”
  5. Select each of “Volume-500k-1Mil” then click “Add”
  6. Click “Load” at the bottom right

Now, you should see the ~1,800 liquid securities on the spreadsheet

Written by FT Cloud · Categorized: Data News, Help · Tagged: commentary, data update, investing, knowledge base, quality data

Jun 12 2014

Why Do Dividends Adjustments Matter?

FastTrack has been the premier provider of quality dividend adjusted ETF, fund, and stock data for many years. Serious investors know why dividends are critical. But, here’s a quick crash course in a few charts.

The 10 year chart below demonstrates the difference between dividend adjusted return vs non dividend adjusted return for VUSTX (Vanguard INV:Long-Term US Treasury).

This fund is one of the top five US funds in total assets (thus very popular and not picked to exaggerate the example)

vustx Div Comparison

The blue line represents VUSTX with no dividend adjustment and the gold line represents VUSTX with dividend adjustments. The blue line shows a return of 23.98%, when in reality the fund
returned 130.74%. That’s a whopping 106.76% difference in return!

Without accurate dividends, it is impossible to build the long-term, low volatility, low trading strategies that FastTrack is known for.

Another example is FMAGX (Fidelity Magellan), a very famous aggressive equity fund, since 9/1/1988 (the first date in the FastTrack database).

FMAGX div comparison

Again, we can see that dividends are essential to analyzing mutual funds accurately. Over the 23 year period, FMAGX appears to have posted a 38.45% gain without dividends, while accounting for dividends shows an accurate 550.92% gain over the period. Any analysis that does not account for distributions is not portraying the funds real total return. Dividend adjustment is essential for long term analysis.

In summary, FastTrack realizes the importance dividends make when assessing true total return
in investing strategies and in developing long-term trading systems. For the past 25 years the company’s mission has been to provide prompt, accurate, and comprehensive dividend adjustments. Getting an accurate view of a fund’s performance is essential to fund and ETF analysis.

Written by FT Cloud · Categorized: Data News, Strategy · Tagged: dividend adjustment, dividends, knowledge base, quality data, simple strategy

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