G-Prophet Methodology
G-Prophet emphasizes probability, ranges, validation, and risk boundaries. Model output is not presented as certainty; it becomes an interpretable, comparable, and reviewable research observation.
Research Workflow
Market-state recognition
Identify trend, range, pullback, volatility expansion, or reversal conditions before evaluating a signal.
Path modeling
Use multi-path simulation to form prediction ranges instead of relying on a single reference price.
Trend filtering
Filter low-quality samples that do not match market structure, stability, or volatility conditions.
Technical confirmation
Use RSI, MACD, Bollinger Bands, KDJ, moving averages, and volume context to explain model direction.
Rolling validation
Backfill actual results after expiry and continuously measure direction agreement rate, price proximity, and segment performance.
Risk boundaries
Flag high volatility, low stability, insufficient samples, and event shocks to avoid overinterpretation.
Metric Definitions
Direction agreement rate
Whether model-implied and actual up/down directions match at expiry. It measures direction, not return.
Price proximity
How close the predicted price is to the actual price. Useful for deviation review, not trade timing.
Model stability
Internal output consistency and data-structure quality. It is not the empirical probability of being correct.
Prediction range
A range-based expression of uncertainty that helps identify volatility boundaries and risk.
Recommended Usage
- 1Review market state before individual symbols.
- 2Read ranges and risk before reference prices.
- 3Treat every prediction as a research hypothesis, not a trade command.
- 4Review history after expiry: direction, deviation, and stability.
- 5Compare across markets, horizons, and symbol types.
Important Notice
G-Prophet outputs are for research and reference only. They are not action instructions. Financial markets are uncertain; use independent judgment.