Rank-Based Stock Rotation with Staggered Buys and Score-Based Exits

Summary

This example turns StockRanker predictions into daily portfolio orders inside BigTrader. It selects a small set of the highest-ranked stocks and assigns larger weights to higher-ranked names using inverse logarithmic weights. Per-stock exposure is capped, while the planned holding period is used to spread purchases across successive trading days. After the initial portfolio build, the strategy sells existing holdings from the bottom of the current ranking until its cash target is met, then allocates available buying cash to leading names.

The implementation also accounts for commission settings and allows somewhat larger daily purchases after the initial build to use spare cash. The article says its more detailed trading logic is often more complex without delivering a clear improvement over a simpler template. It provides no backtest results, benchmark comparison, or evidence of live performance, so the rules should be treated as an implementation example rather than a validated strategy.

Key ideas

• The strategy feeds daily StockRanker predictions directly into the trading engine.
• It allocates more weight to higher-ranked stocks using inverse logarithmic weights.
• Purchases are staged across the planned holding period, with limits on each stock’s portfolio share.
• Once the initial build is complete, it sells lower-ranked holdings to fund purchases of leading names.
• The article reports no performance results and notes that added complexity often brings no clear gain.

Tags

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