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  • Example 1: Basic Gaps
  • Pitfalls of Bias
  1. Use Cases
  2. For Backtesting

Historical Gaps

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Last updated 2 years ago

Many traders are interested in data related to historical gappers. In this section, we will walk through how to pull historical gappers with a variety of different filters to help kick you off on your data-tracking journey.

Example 1: Basic Gaps

A gap is defined as the percent change between the opening price of a stock on any given day (Day [1] Open) vs the close of the previous day (Day [-1] Close). Other filters can/should be used to filter out results that are not as relevant, ie stocks with volume under 500k, outside of the target price range, or even outside of the target shares outstanding/float.

Let's use the basic example from the previous page with the following filters:

  • Date: Last 90 Days

  • Day [1] Open: Price between $2 - $15

  • Day [1] Gap %: Greater than 20%

  • Day [1] Volume: Greater than 2,000,000

  • Share Type: Equals Common Stock

This query will return the following results, in which you can click on any row in the result table and it will populate the chart with the relevant date in history to give you a good visual of how these stocks have performed in the past.

Pitfalls of Bias

When looking to add more filters, you need to always consider that filtering out stocks can build a bias that leaves you worse off than before. If you filter for only stocks that closed higher than premarket high, then you will clearly only have results that would have been great long opportunities. We will go into significantly more detail about this in the future.

History results for Example 1: Basic Gaps