Alternative Data For Trading — Statistical Arbitrage

Data Quality Checks

The data looks fine except for a couple of obvious errors such as the -150 closing price. We just need an automated way to fix such obvious and any other errors.

  • The standard deviation of the last 5–20 data points.
  • We create a couple of lower and upper barriers using 6 sigmas as the threshold.
  • Flag any points lying beyond the six sigma from the average.

Efficacy Check

Now, that we want to understand if the signal has any predictive power. We need to be able to define a metric and measure the same. We use the percentage change in signal and if it has any predictive power over computing 1-day forward-looking price change or returns.


This is one of the ways to go about measuring the efficacy and looks into the use of alternative data for trading instead of trying to use the same data points and processing them better aka use more complex models/data transformations.



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