StockSharp.Strategies.0351_Accrual_Anomaly.py

Accrual Anomaly (Python Version)

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.

Details

• 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