ChatGPT Prompts for Trading Strategies: Build and Backtest Ideas

Act as a quantitative trader and strategy developer with experience backtesting systematic trading strategies across crypto, equities, and forex.
Develop or evaluate the following trading strategy:
Strategy concept: {describe the trade idea in plain English — what market condition are you trying to capture?}
Asset class: {crypto / equities / forex / futures}
Timeframe: {intraday / daily / weekly / positional}
Entry rules: {describe entry conditions — what specific criteria trigger a trade?}
Exit rules: {describe exit conditions — profit target, stop loss, time exit?}
Position sizing: {fixed size / % risk / volatility-adjusted}
Historical data availability: {do you have data to backtest? If yes, what period?}

Strategy evaluation:
1. Edge hypothesis (what market inefficiency or behavioral pattern does this strategy exploit?)
2. Strategy rules formalization (convert your description into precise if/then rules)
3. Backtest design:
   - Required sample size for statistical significance
   - Train/test split recommendation
   - Metrics to optimize for (Sharpe / Sortino / max drawdown / win rate)
4. Failure modes (under what market conditions would this strategy fail?)
5. Overfitting risk assessment (does the strategy have enough rules? Too many? Signs of curve-fitting?)
6. Implementation requirements (data, tools, or execution infrastructure needed)
7. Similar documented strategies (if applicable — academic or practitioner strategies with similar logic)

Constraints:
- Not financial advice — for educational purposes only
- Edge hypothesis must be falsifiable — "prices go up in bull markets" is not an edge
- Sample size requirement must be calculated, not guessed
- Acknowledge if the strategy requires special execution capability (low latency, dark pool access, etc.)