Building Intraday Samples of Penny Stocks After Large Gap Ups
Summary
The document considers how to assemble historical intraday data for penny stocks that gap up by at least 10%, using a definition based on low share price and market capitalization. Its suggested workflow is to identify qualifying gap-up events with a stock screener, then obtain intraday bars for the identified symbols from a market data provider. The cited example uses five-minute bars and notes that the provider limits how much history can be requested in one download.
The answer emphasizes that a narrowly filtered historical dataset may not be available as a ready-made product, so screening events and collecting price history may be necessary. It offers a practical starting point rather than a complete research pipeline: the screener may expose only recent events, historical coverage is uncertain, and the response does not address survivorship bias, delisted symbols, corporate actions, or consistent point-in-time market capitalization data. These omissions matter if the collected sample will be used for a backtest.
Key ideas
- A specific gap-up universe may need to be assembled by screening individual stocks.
- The proposed workflow is to identify qualifying events first and then retrieve intraday bars for each symbol.
- The example data source provides five-minute observations but limits the downloadable history per request.
- Historical coverage and sample quality require checks for survivorship, delistings, and point-in-time fundamentals.
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Full text
# Historical intraday dataset with penny stocks with a gap-up of 10% or above # Historical intraday dataset with penny stocks with a gap-up of 10% or above I am trying to find intraday datasets of pennystocks. My criteria for the dataset is that it needs to only contain pennystocks where the gap-up was 10% or above. I am looking for a free option but could not find any. I have also checked kaggle for datasets. I would also like to see paid plans, if that becomes my only option. Another option would be to scrape for data, but this will be more time consuming. Penny stock definition: - Price between 0 and 5 USD - Market cap between 0 and 300 million USD ## Answer by Pleb (score 4, accepted) https://quant.stackexchange.com/a/60593 Often no pre-made dataset exists when you have such specific requirements. Therefore, you have to find your own data by searching for penny-stocks that matches your criteria. This can be done via a stock-screener. Doing a quick google search on "Gap-up stock screener" I found this website, where I sorted by highest percentage gap-up changes. From this, I found 4 stocks satisfying your criteria. I believe, this website gives gap-up events happened until a week prior, however, maybe there exist a different stock screener that can give you historical gap-up events? When you have found your pennystocks, you need to download your intraday data. This can be done on Alphavantage.co. You have to sign up for a free API key. Connecting to the API and downloading data via Python or R is well documented, and I encourage you to read the documentation. However, if you do not have any experience working in R or Python, you can download intraday data via a URL call also. Eg. downloading data in a .csv file on the pennystock Neostem Inc. (ticker: CLBS) can be done via the URL: https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY_EXTENDED&symbol=CLBS&interval=5min&slice=year1month1&apikey=YOUR_APIKEY_HERE where you get the high, low, open, close prices in 5-minute increments. Also, replace "YOUR_APIKEY_HERE" with your API key. Remember that there is a limit to how much intraday data you can download at once (for 5 minute intervals, you can have a length max time-horizon of approximately one month). Hopefully this helps.
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