Computing and Combining the Alpha101 Equity Factors

Summary

This document outlines a two-stage workflow for calculating Alpha101 factors. First, it reads daily stock data, derives base series such as returns and VWAP, and computes time-series intermediate variables for storage. Later, factor construction retrieves the needed intermediates and combines them. Because many formulas require ranks across stocks on each date, the workflow needs a specified candidate universe before those cross-sectional calculations are performed.

The page lists many Alpha101 formulas and notes implementation limitations: some depend on industry classifications or market capitalization data that the author could not obtain, and at least one factor reportedly returned only zeros in local checks. Alpha#101 is given as a normalized close-open difference over the high-low range with a small stabilizing constant. These details describe implementation and data dependencies, not evidence that the factors predict returns; no portfolio backtest or performance comparison is reported.

Key ideas

• The workflow stores reusable factor intermediates before constructing the final Alpha101 signals.
• Base inputs include OHLC prices, prior close, volume, traded value, dates, and symbols.
• Many factor calculations need cross-sectional ranks and therefore a defined stock universe.
• Some listed factors cannot be implemented without industry classifications or market capitalization data.
• The document reports an unresolved all-zero output for one factor and provides no portfolio performance evidence.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.