Batch-Filtering Stocks With a Preloaded Intraday Data Set
Summary
The document answers a programming question about applying a per-stock price-pattern test to stocks first selected by daily market filters. The suggested workflow reads hourly bars for the candidate instruments in one batch, then passes the shared data frame and each instrument to a function that filters rows for that stock. This avoids making a separate data-source request inside the loop and is presented as a more efficient way to process the list.
The example’s initial screen uses adjusted daily prices and trading amount, while the intraday function examines sequences of highs and lows and applies a numerical condition to decide whether to print a positive result. The page also notes that a date filter is redundant when the data request already starts later. It does not explain the pattern’s market rationale, edge, or out-of-sample performance, and the code is supplied as a forum response rather than a validated strategy.
Key ideas
- Select candidate instruments with daily filters before applying an intraday pattern test.
- Load hourly data for the candidate list in one request, then filter the resulting data by instrument.
- Avoid repeated data-source calls inside a per-stock loop to reduce unnecessary work.
- A date condition is redundant when the requested data already begins after that date.
- The sample pattern rule is not supported by evidence of trading performance.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.