Hercules Index Volatility
A percentile rails framework for indices. It learns what is normal for the last window and places rails above and below price. You get rule based entries near the lower rail, exits near the upper rail, and an optional sell side when extremes and trend conditions align. Signals are alert ready. The aim is fewer impulsive decisions and more planned action.
People do not buy strategies. They buy peace of mind that the next move follows a plan. Index Volatility is designed to give you that with rules you can verify in minutes.
How it works
Short window rails
A short lookback computes two percentiles on the active symbol. The lower rail sits near the fortieth percentile of the last thirty closes. The upper rail sits near the sixty fifth percentile of the same window. Price pressing below the lower rail sets up long interest. Price above the upper rail completes the cycle for exits.
Long window extremes
A long lookback computes an upper extreme and a lower extreme using higher thresholds on a much larger sample. When price touches the long window extreme and that extreme is still rising, a sell side setup can appear. Exits then watch for a return toward the long window lower bound.
Time guard
A start year filter keeps the study inside a stable data regime. Use it to avoid distorted periods if your feed changed format or quality.
Reporting
The performance table shows monthly and yearly results, drawdowns, MAR, and CAGR. Commission in the reference script is set to zero in order to show the raw behavior of the rules. You can set your venue cost and retest.
Inputs
length
Short window for the near rails. Thirty in the reference script. Raise for calmer rails. Lower for more responsive rails.
length2
Long window for extremes. One thousand in the reference script. This anchors the sell side logic and the lower extreme used for exits.
percentile thresholds
Near rails around forty and sixty five for the short window. Extremes around eighty and ninety for the long window. You can tune, but change one at a time and journal the impact.
long entry and short entry toggles
Enable or disable sides. Many users begin with long only and add the sell side after a full review.
year start
Include trades only from this year onward. Aligns the study to your preferred regime.
Signals
- Long entry when price is below the short window lower rail and the start year condition is met.
- Long exit when price moves above the short window upper rail.
- Short entry when price reaches the long window upper extreme and that extreme is rising over several bars. The start year condition must be met.
- Short exit when price returns to the long window lower extreme.
- Short sizing can use a pragmatic rule of quarter equity divided by price as in the reference script. You can replace with your own risk sizing.
Signals are model outputs for research and education. They are repeatable and alert ready. You decide timing, size, and execution. Your slippage and fills are your responsibility.
Workflow
- Select a liquid index or index tracking product with a reliable feed.
- Set the start year and keep it stable for your study window.
- Begin with default thresholds. Change one variable at a time after a full cycle review.
- Run the performance table and note return, drawdown, and time in drawdown. Check that the rail logic is doing what you expect in bull and bear stretches.
- Wire alerts for long and short signals. Journal each action and compute your Discipline Score weekly.
Risk
- Use fixed risk per trade and a daily or weekly loss cap. Flat is a valid state.
- Reduce size when realized volatility expands. Rails will widen and exits can come faster in both directions.
- Prefer instruments with tight spreads and deep books. Avoid products with irregular sessions that break the lookback math.
Testing notes
Backtests use realized equity and the embedded monthly table. Commission is set to zero in the reference script so you can see the raw effect of rules. You can add your venue cost and retest. On major indices the model has shown periods of outperformance versus buy and hold with a different drawdown profile and fewer decisions. The edge comes from pressing near the lower rail and exiting near the upper rail, and from a cautious sell side that appears only at long window extremes.
Backtest caveats
- Historical results are hypothetical and depend on data quality and assumptions including commission and execution.
- No slippage model captures every gap or auction. Your fills can differ.
- Past performance does not guarantee future results. Index microstructure can change across regimes.
FAQ
Does it generate signals
Yes. Entries and exits are rule based and alert ready. They are model outputs for education and research.
Can it beat buy and hold
In several windows it has outperformed with different drawdown and a different return path. That does not promise future results. Discipline still decides outcomes.
Which markets
Large liquid indices and their primary ETFs. Start with your main index. Expand only after a complete journal review.
Can I change thresholds
Yes. Change one value at a time and validate across a full cycle. Avoid curve fitting. Simplicity survives.
Compliance
Educational analytics and model signals. No personalized investment advice. We do not assess suitability, we do not execute trades, and we do not hold client assets. You are responsible for your decisions, sizing, and execution.
This product is offered as research and software access. Payments via Stripe or crypto are for software and educational content, not for investment services. Taxes and refunds are handled by Stripe where applicable. Crypto payments may be subject to basic AML checks.
Built with European regulatory context in mind and framed as education and research. Nothing here should be interpreted as a solicitation to engage in specific transactions.
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