A Moving-Average and Profit-Chip Stock Strategy with a Research Workflow
Summary
The note turns a discretionary stock method into explicit rules: admit a stock to an initial universe when its daily low stays above 99% of the 34-day moving average for ten consecutive days, buy when its profitable-chip proportion exceeds 73%, and sell when its high falls below that average. It also outlines a broader research process, from screening and testing individual factors through in-sample and out-of-sample validation, paper trading, limited live deployment, and ongoing monitoring.
The workflow distinguishes return factors from risk controls and recommends checking factor correlations and evaluating risk, return, and stability at each stage. It gives no backtest results or evidence that the specific entry and exit rules are profitable. The thresholds and “profitable chips” measure are not defined in detail, and the process depends on careful data handling and continued monitoring because a model can lose effectiveness after deployment.
Key ideas
- The initial stock universe requires ten consecutive daily lows above 99% of the 34-day moving average.
- A buy signal uses a profitable-chip proportion above 73%, while an exit occurs when the daily high is below the moving average.
- Factor research should assess predictive strength, individual performance, and correlations between factors.
- The proposed development path includes in-sample and out-of-sample testing, paper trading, and cautious live deployment.
- Live models require monitoring for changes in the effectiveness of their universe and rules.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.