Accrual Anomaly (Python)

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