Accrual Anomaly (Python). StockSharp

Author: StockSharp
N: 1973
v5.0.0 (8/7/2025)
Downloads: 0

The Accrual Anomaly strategy implements the accrual anomaly factor. It rebalances annually on the first trading day of May, going long low-accrual stocks and short high-accrual ones.
Testing indicates an average annual return of about 12%. It performs best in the U.S. equity market.
Positions are adjusted once per year; no intraday signals are used.

  • Entry Criteria: see implementation for accrual calculations.
  • Long/Short: Both directions.
  • Exit Criteria: Rebalance on next scheduled date.
  • Stops: No explicit stop logic.
  • Default Values:

    • Deciles = 10
    • CandleType = TimeSpan.FromDays(1).TimeFrame()

  • Filters:

    • Category: Fundamental
    • Direction: Both
    • Indicators: Fundamentals
    • Stops: No
    • Complexity: Intermediate
    • Timeframe: Daily
    • Seasonality: Yes
    • Neural Networks: No
    • Divergence: No
    • Risk Level: Medium