Add research methodology for EA-096 Intraday Range Extension
This document outlines the research methodology for EA-096 Intraday Range Extension, detailing the purpose, baseline principles, test parameters, performance metrics, and testing strategies.
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# Research Methodology
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## 1. Purpose
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This document defines the methodology used to research and validate EA-096_Intraday_Range_Extension.
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The objective is to separate:
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* strategy discovery
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* baseline measurement
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* parameter research
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* robustness testing
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* out-of-sample validation
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* forward testing
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---
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## 2. Baseline Principle
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The first completed test is treated as the baseline:
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`EA096-M1-BASELINE-001`
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The baseline must remain unchanged.
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All future experiments are compared against this reference.
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---
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## 3. Baseline Test
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### Market
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* Symbol: XAUUSD.PRO
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* Timeframe: M1
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### Period
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`2026.01.02 – 2026.03.31`
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### Data
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`100% real ticks`
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### Initial Capital
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`$1,000`
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### Core Strategy Parameters
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* ATR Period = 14
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* Extension ATR = 1.0
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* Minimum Range Bars = 30
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### Execution
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* Lot = 0.01
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* SL = 300 points
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* TP = 600 points
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* Break-Even = 150 points
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* Trailing Start = 200 points
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* Trailing Distance = 100 points
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---
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## 4. Baseline Performance
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| Metric | Baseline |
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| --------------- | -------: |
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| Net Profit | +$30.80 |
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| Profit Factor | 1.37 |
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| Expected Payoff | $0.36 |
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| Recovery Factor | 2.11 |
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| Sharpe Ratio | 49.56 |
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| Total Trades | 86 |
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| Win Rate | 53.49% |
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| Max Equity DD | 1.44% |
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## The tester report records 86 trades and a maximum equity drawdown of 1.44%.
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## 5. Controlled Experiment Principle
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A research experiment should change as few variables as possible.
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For example:
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### Experiment A
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Change:
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`ExtensionATR`
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Keep everything else equal.
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### Experiment B
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Change:
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`InpMinRangeBars`
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Keep everything else equal.
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### Experiment C
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Change:
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`StopLoss / TakeProfit`
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Keep entry logic unchanged.
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This makes it possible to identify which component actually changes performance.
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---
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## 6. Primary Metrics
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Every experiment should record:
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### Profitability
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* Net Profit
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* Gross Profit
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* Gross Loss
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* Profit Factor
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* Expected Payoff
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### Risk
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* Maximum Balance Drawdown
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* Maximum Equity Drawdown
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* Relative Drawdown
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* Recovery Factor
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### Trade Quality
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* Total Trades
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* Win Rate
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* Average Profit Trade
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* Average Loss Trade
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* Largest Profit Trade
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* Largest Loss Trade
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### Consistency
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* Consecutive wins
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* Consecutive losses
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* Average holding time
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* Long versus short performance
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---
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## 7. Statistical Discipline
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A positive backtest with a small number of trades should not be treated as proof of a stable edge.
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The current EA-096 baseline contains:
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`86 trades`
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Therefore additional data is required before making a strong statistical conclusion.
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The research should prioritize increasing the sample size before aggressive parameter optimization.
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---
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## 8. Parameter Robustness
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A robust strategy should continue to perform reasonably when parameters are changed slightly.
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For example, if:
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`ExtensionATR = 1.0`
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produces a strong result but:
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`0.9`
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and
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`1.1`
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produce poor results, the strategy may be overly sensitive.
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The research should therefore examine parameter neighborhoods rather than searching for one perfect value.
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---
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## 9. Out-of-Sample Testing
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After identifying a candidate configuration:
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1. Freeze all parameters.
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2. Select data not used during discovery.
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3. Run the EA without additional optimization.
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4. Record all performance metrics.
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5. Compare the result with the baseline.
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A configuration should not be accepted solely because it performs well on the data used to discover it.
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---
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## 10. Walk-Forward Testing
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A later research stage should use walk-forward testing.
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General process:
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`Historical Data`
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↓
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`Research / Optimization Window`
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↓
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`Parameter Freeze`
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↓
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`Out-of-Sample Window`
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↓
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`Record Result`
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↓
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`Move Forward`
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The objective is to determine whether the strategy can adapt without repeatedly optimizing itself to past data.
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---
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## 11. Robustness Testing
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Robustness should eventually include:
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* different historical periods
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* different market regimes
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* nearby ATR thresholds
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* nearby range lengths
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* different exit parameters
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* BUY versus SELL separation
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* trading-session analysis
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The purpose is not to find the highest historical profit.
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The purpose is to determine whether the strategy's underlying behavior remains stable.
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---
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## 12. Production Readiness
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EA-096 should only be considered production-ready after:
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* sufficient historical trade sample
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* stable baseline comparison
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* parameter robustness
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* out-of-sample validation
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* walk-forward validation
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* forward testing
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* acceptable drawdown
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* acceptable execution behavior
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The current supplied baseline does **not** satisfy all of these requirements.
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Current status:
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`RESEARCH — NOT PRODUCTION READY`
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---
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## 13. Current Research Reference
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The official baseline for EA-096 is:
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`EA096-M1-BASELINE-001`
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Current conclusion:
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**The supplied test is positive and worth further research, but the sample size of 86 trades is insufficient to establish production-level robustness.**
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