Update skills: add website-creator, mql-developer, ecommerce-astro
Changes: - Add FAL_KEY and GEMINI_API_KEY to .env.example - Update picture-it to use ~/.config/opencode/.env (unified creds) - Remove shodh-memory skill (no longer used) - Remove alphaear-* skills (deprecated) - Remove thai-frontend-dev skill (replaced by website-creator) - Remove theme-factory skill - Add mql-developer skill (MQL5 trading) - Add ecommerce-astro skill (Astro e-commerce) - Add website-creator skill (Next.js + Payload CMS) - Update install script for new skills
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skills/mql-developer/references/backtesting.md
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skills/mql-developer/references/backtesting.md
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# Backtesting & Optimization
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## Table of Contents
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- [Strategy Tester Modes](#strategy-tester-modes)
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- [Minimum Requirements for Valid Backtest](#minimum-requirements-for-valid-backtest)
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- [OnTester() - Custom Optimization Criterion](#ontester---custom-optimization-criterion-mql5)
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- [TesterStatistics() Constants](#testerstatistics-constants)
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- [Key Performance Metrics](#key-performance-metrics)
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- [Walk-Forward Analysis](#walk-forward-analysis)
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- [Avoiding Overfitting](#avoiding-overfitting)
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- [Monte Carlo Simulation](#monte-carlo-simulation)
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- [Multi-Currency Testing (MQL5)](#multi-currency-testing-mql5)
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- [Optimization Modes (MT5)](#optimization-modes-mt5)
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- [Frame Functions (Inter-Pass Communication)](#frame-functions-inter-pass-communication)
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- [Practical Backtesting Workflow](#practical-backtesting-workflow)
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---
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## Strategy Tester Modes
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| Mode | Speed | Accuracy | When to Use |
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|------|-------|----------|-------------|
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| Every tick based on real ticks | Slowest | Most realistic | Final validation with broker-specific ticks |
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| Every tick | Slow | High | Final validation, scalpers, intra-bar logic |
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| 1-minute OHLC | Medium | Good | Most strategies (4 ticks per M1 bar) |
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| Open prices only | Fast | Low | Bar-open strategies, rapid optimization |
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| Math calculations | Instant | N/A | Pure computation without ticks |
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Best practice: Optimize with Open Prices first, validate winners with Every Tick.
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## Minimum Requirements for Valid Backtest
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- 1,000+ trades minimum (ideally 2,000+)
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- 2+ full market cycles (bull + bear + range)
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- Multiple years of data
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- Consistent spread settings (or variable spread)
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## OnTester() - Custom Optimization Criterion (MQL5)
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```mql5
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double OnTester() {
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double profit = TesterStatistics(STAT_PROFIT);
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double profitFactor = TesterStatistics(STAT_PROFIT_FACTOR);
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double sharpeRatio = TesterStatistics(STAT_SHARPE_RATIO);
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double recoveryFactor = TesterStatistics(STAT_RECOVERY_FACTOR);
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double maxDrawdown = TesterStatistics(STAT_EQUITY_DD_RELATIVE);
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double totalTrades = TesterStatistics(STAT_TRADES);
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if(totalTrades < 100) return 0; // Reject small samples
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if(maxDrawdown > 25) return 0; // Reject excessive DD
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if(profitFactor < 1.3) return 0; // Reject low PF
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return sharpeRatio * recoveryFactor * MathSqrt(totalTrades);
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}
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```
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## TesterStatistics() Constants
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Complete table:
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- STAT_PROFIT - Net profit
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- STAT_GROSS_PROFIT - Gross profit
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- STAT_GROSS_LOSS - Gross loss
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- STAT_TRADES - Total trades
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- STAT_PROFIT_TRADES - Winning trades
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- STAT_LOSS_TRADES - Losing trades
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- STAT_PROFIT_FACTOR - Gross profit / gross loss
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- STAT_EXPECTED_PAYOFF - Expected payoff per trade
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- STAT_SHARPE_RATIO - Sharpe ratio
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- STAT_RECOVERY_FACTOR - Net profit / max drawdown
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- STAT_EQUITY_DD - Max equity drawdown in money
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- STAT_EQUITY_DD_PERCENT - Max equity drawdown %
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- STAT_EQUITY_DD_RELATIVE - Relative equity drawdown %
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- STAT_BALANCE_DD - Max balance drawdown
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- STAT_BALANCE_DD_PERCENT - Max balance drawdown %
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- STAT_MAX_PROFITTRADE - Largest profitable trade
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- STAT_MAX_LOSSTRADE - Largest losing trade
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- STAT_CONPROFITMAX - Max consecutive profit
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- STAT_CONLOSSMAX - Max consecutive loss
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- STAT_SHORT_TRADES - Short trades
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- STAT_LONG_TRADES - Long trades
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- STAT_WIN_SHORT_TRADES - Winning short trades
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- STAT_WIN_LONG_TRADES - Winning long trades
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## Key Performance Metrics
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| Metric | Formula | Good Value | Excellent |
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|--------|---------|------------|-----------|
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| Sharpe Ratio | (Mean Return - Rf) / StdDev | > 1.0 | > 2.0 |
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| Profit Factor | Gross Profit / Gross Loss | > 1.5 | > 2.0 |
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| Recovery Factor | Net Profit / Max DD | > 3.0 | > 5.0 |
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| Max Drawdown | Peak-to-trough % | < 20% | < 10% |
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| Expected Payoff | Net Profit / Total Trades | > 0 | Context |
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| Win Rate | Winning / Total | Context | Context |
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## Walk-Forward Analysis
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### Methodology
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```
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Window 1: [===== IN-SAMPLE =====][= OOS =]
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Window 2: [===== IN-SAMPLE =====][= OOS =]
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Window 3: [===== IN-SAMPLE =====][= OOS =]
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Window 4: [===== IN-SAMPLE =====][= OOS =]
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```
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### Steps
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1. Split data into overlapping windows (e.g., 12-month IS, 3-month OOS)
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2. Optimize on in-sample period
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3. Test optimized params on out-of-sample period
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4. Slide window forward, repeat
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5. Accept if OOS performance >= 50-80% of IS
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6. MT5 supports natively: Strategy Tester > Settings > Forward period
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### Walk-Forward Efficiency
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WFE = (OOS annualized return) / (IS annualized return)
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- WFE > 0.5 = acceptable
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- WFE > 0.7 = good
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- WFE < 0.3 = likely overfitted
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## Avoiding Overfitting
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### Principles
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1. **Parameter stability**: Good params have good neighbors. If X=14 works but X=13 and X=15 don't, it's curve-fitted
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2. **Fewer parameters**: Each extra parameter increases overfitting risk exponentially
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3. **Out-of-sample testing**: Reserve 25-30% of data untouched
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4. **Cross-market validation**: Test EURUSD strategy on GBPUSD
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5. **Regime awareness**: Test across trending AND ranging markets
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### Signs of Overfitting
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- Sharp performance drop in forward test
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- Many parameters (>5 optimized)
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- Strategy only works on specific date range
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- Unrealistically high backtest metrics
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- Parameter sensitivity (small changes cause large performance swings)
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## Monte Carlo Simulation
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### Purpose
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Test if results are due to skill or luck by randomizing trade sequence.
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### Implementation
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```mql5
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double OnTester() {
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// Collect all trade P&Ls
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double trades[];
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// ... populate from history ...
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int simulations = 1000;
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double worstDD95;
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for(int sim = 0; sim < simulations; sim++) {
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// Fisher-Yates shuffle
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// Calculate max drawdown for shuffled sequence
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}
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// Sort DDs, find 95th percentile
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// Reject if 95th percentile DD > 30%
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return profit / (1 + worstDD95);
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}
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```
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### What Monte Carlo Tells You
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- Expected range of drawdowns (not just the one historical path)
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- Probability of ruin at different risk levels
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- Confidence interval for returns
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- If strategy is fragile (high variance across simulations)
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## Multi-Currency Testing (MQL5)
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MT5 Strategy Tester supports multi-symbol natively:
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```mql5
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int OnInit() {
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// Reference other symbols to include them in test
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int handle_eur = iMA("EURUSD", PERIOD_H1, 14, 0, MODE_SMA, PRICE_CLOSE);
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int handle_gbp = iMA("GBPUSD", PERIOD_H1, 14, 0, MODE_SMA, PRICE_CLOSE);
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// Tester auto-synchronizes all referenced symbols
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return INIT_SUCCEEDED;
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}
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```
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## Optimization Modes (MT5)
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| Mode | Description |
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|------|-------------|
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| Slow (Complete) | Tests every combination (exhaustive) |
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| Fast (Genetic) | Genetic algorithm, finds near-optimal efficiently |
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| Custom max/min | Optimizes by OnTester() return value |
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### Cloud Computing
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MQL5 Cloud Network distributes optimization across thousands of agents worldwide.
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## Frame Functions (Inter-Pass Communication)
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```mql5
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// In EA (agent): send data at end of each pass
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double OnTester() {
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uchar data[];
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// serialize results into data
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FrameAdd("Results", 1, profit, data);
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return profit;
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}
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// In terminal: receive during optimization
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void OnTesterPass() {
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ulong pass; string name; long id; double value; uchar data[];
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while(FrameNext(pass, name, id, value, data)) {
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PrintFormat("Pass #%d: profit=%.2f", pass, value);
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}
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}
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// Control functions
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void OnTesterInit() { /* before optimization starts */ }
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void OnTesterDeinit() { /* after optimization finishes, aggregate results */ }
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```
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## Practical Backtesting Workflow
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1. **Quick scan**: Open Prices Only, wide parameter ranges, genetic optimization
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2. **Narrow down**: Reduce ranges around promising areas, complete optimization
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3. **Validate**: Every Tick mode with best parameters
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4. **Walk-forward**: Set forward period, verify OOS performance
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5. **Monte Carlo**: Randomize trade sequence, check robustness
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6. **Multi-market**: Test on correlated instruments
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7. **Demo forward test**: Run on demo account for 1-3 months minimum
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