Exp_TimesDirection
This EA trades based on time-of-day directional signals, analyzing price movement direction during specific time windows to determine trade entries. It opens positions when the market direction aligns with historically favorable time-based patterns, typically operating during sessions where directional bias is strongest.
Open the interactive view (equity curve, symbol switch)Key facts
Backtest results (H1, about 1 year)
| Symbol | P&L | Annual | Max DD | Trades | Win rate | Sharpe | Recovery | Losing streak | Per trade | Status |
|---|---|---|---|---|---|---|---|---|---|---|
| EURUSD | +0.63% | +0.55% | 0.95% | 9 | 66.70% | — | — | — | — | Too few trades |
| GBPUSD | +3.79% | +3.28% | 0.68% | 11 | 90.90% | 2.29 | 5.57 | 1 | +$34.45 | Reliable |
| USDJPY | +0.88% | +0.77% | 1.17% | 14 | 28.60% | 0.57 | 0.75 | 3 | +$6.31 | Reliable |
| XAUUSD | +20.72% | +16.84% | 18.72% | 12 | 75.00% | 0.83 | 1.11 | 1 | +$172.70 | Reliable |
Profitable on 3 of 3 markets with reliable results.
Converted from MQL5 to Python and run with the same rules for every EA. Positions use MT5 lot sizes (100,000 units per FX lot, 100 oz per gold lot) with 1:100 leverage, one order at a time, and a stop-out below 10% of the starting balance. Sharpe is computed from the equity curve. Results marked as unreliable are shown for completeness only.
Against the other Multi-Timeframe EAs with a reliable result on the same market: GBPUSD: better than 67% of 12 · USDJPY: better than 42% of 12 · XAUUSD: better than 83% of 12
Month by month
| Market | Months with a gain | Best month | Worst month |
|---|---|---|---|
| GBPUSD | 54% | +1.44% 2026-06 | -0.46% 2026-10 |
| USDJPY | 31% | +1.03% 2026-02 | -0.48% 2026-11 |
| XAUUSD | 54% | +13.66% 2026-08 | -14.52% 2026-02 |
From the backtest equity curve, sampled about every two days; only reliable results.
Blow-up risk: No blow-up pattern found
None of the usual blow-up patterns were found in the code, and the account was not stopped out in our backtests. That is not a guarantee: any EA can lose money.
High: stopped out in our backtest, or martingale/grid sizing without a stop loss. Elevated: martingale or grid sizing with a stop loss, or several positions at once without a stop loss. What the label means and what we found →
Strategy analysis
The strategy concept is based on time-series directional analysis, assuming that price movement during specific trading sessions exhibits statistically significant directional bias. Entry conditions trigger when the current price direction aligns with the trend direction within a defined time window, potentially combining multi-timeframe directional confirmation to enhance signal reliability. Exit conditions include fixed take-profit and stop-loss levels, directional reversal signals, or position closure at the end of the designated time session. Position sizing employs fixed lot sizes or account-balance-proportional sizing methods. Money management does not appear to incorporate sophisticated dynamic adjustment mechanisms, primarily relying on fixed parameters to control risk exposure. The overall strategy falls under systematic time-based trading, assuming certain sessions exhibit predictable directional movement patterns.
Strengths
- Time filtering mechanism avoids trading during low liquidity sessions, reducing slippage and false signals
- Session-based directional bias strategy has statistical theoretical foundation, as certain periods do exhibit directional patterns
- Systematic trading logic is clear with adjustable parameters, facilitating backtesting and optimization
- Multi-timeframe directional confirmation can improve signal quality and win rate
Weaknesses
- Over-reliance on historical session patterns; strategy may fail when market structure changes
- Fixed stop-loss and take-profit don't account for volatility changes, leading to inconsistent performance across varying volatility environments
- Lack of dynamic money management mechanism prevents position adjustment based on account equity changes
- Time window parameter optimization is prone to overfitting, and live performance may deviate from backtest results
- Does not account for spread and commission impacts on short-duration session trades
Possible improvements
- Introduce adaptive session identification that dynamically adjusts trading time windows based on recent volatility
- Add dynamic stop-loss mechanisms (e.g., ATR-based stops) that adjust stop distances according to market volatility
- Implement spread filter and money management module that dynamically adjusts position sizing based on account equity
Risk assessment
Overall risk: Medium
- Fixed stop-loss may be insufficient during extreme volatility, causing losses beyond expectations
- Session-based strategy may incur consecutive losses during market structure shifts, lacking adaptive mechanisms
- No explicit position check or duplicate order prevention mechanism detected
Evaluation scores
Parameters
| Parameter | Default | Description |
|---|---|---|
StartTime | 00:00 | Trading start time |
StopTime | 23:59 | Trading stop time |
Lots | 0.1 | Fixed trading lot size |
StopLoss | 500 | Stop loss in points |
TakeProfit | 1000 | Take profit distance in points, 0 to disable |
Timeframe | H1 | Timeframe for direction judgment |
DirectionPeriod | 14 | Direction judgment period parameter |
MagicNumber | 12345 | EA magic number for identifying managed positions |
Similar Multi-Timeframe EAs
Backtests are historical simulations and do not guarantee future results. Not financial advice.