Topic · Research Practice & Backtesting
← All topicsData Quality
28 articles · 5 checkpoints · 16 deeper reads · 7 reference notes
Every article, in reading order
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Splits, dividends, spin-offs and rights issues move a stock's printed price without changing what a holder owns. Research that reads raw prices treats those moves as returns, and the errors are large, one-sided and easy to mistake for a signal.
In finance a missing value is rarely an accident. It is usually a halt, a delisting, a failure to report or a stock nobody wanted to trade. Forward-filling deletes that message and replaces it with a fake calm that optimisers find irresistible.
An impossible print and a genuine crash look identical in a histogram. Deleting the first is data hygiene, deleting the second is deleting the market. Most cleaning pipelines cannot tell them apart, and pay for it in both directions.
A point-in-time database remembers what it used to say, not just what is true now. Without that memory, every backtest quietly uses corrected figures that nobody had at the time, and the corrections are concentrated exactly where the money is.
Two datasets with sensible-looking time columns can be merged in one line of code, and that line is where cross-market backtests invent their edge. Daylight saving alone hands a naive join four weeks of free look-ahead a year.
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