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feat(backtest): add walk-forward OOS validation to backtest_signal_ftmo

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Split IS (2020-2023) and OOS (2024-2026) periods with independent FTMO
simulations. Strategy acceptance now requires OOS sharpe > 0 and
OOS monthly return > 0 to prevent overfitting. OOS metrics stored in
strategy JSON summary and CSV reports.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
TPTBusiness
2026-04-19 12:53:00 +02:00
parent 5bc517c3bc
commit 7232ebf89d
4 changed files with 263 additions and 36 deletions
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rdagent/components/backtesting/__init__.py
+2 -1
View File
@@ -10,6 +10,7 @@ from .vbt_backtest import (
FTMO_MAX_TOTAL_LOSS,
FTMO_MAX_LEVERAGE,
FTMO_RISK_PER_TRADE,
OOS_START_DEFAULT,
backtest_from_forward_returns,
backtest_signal,
backtest_signal_ftmo,
@@ -21,5 +22,5 @@ __all__ = [
'backtest_signal', 'backtest_signal_ftmo', 'backtest_from_forward_returns',
'DEFAULT_BARS_PER_YEAR', 'DEFAULT_TXN_COST_BPS',
'FTMO_INITIAL_CAPITAL', 'FTMO_MAX_DAILY_LOSS', 'FTMO_MAX_TOTAL_LOSS',
'FTMO_MAX_LEVERAGE', 'FTMO_RISK_PER_TRADE',
'FTMO_MAX_LEVERAGE', 'FTMO_RISK_PER_TRADE', 'OOS_START_DEFAULT',
]
rdagent/components/backtesting/vbt_backtest.py
+38
View File
@@ -340,6 +340,9 @@ def _apply_ftmo_mask(
}
OOS_START_DEFAULT = "2024-01-01"
def backtest_signal_ftmo(
close: pd.Series,
signal: pd.Series,
@@ -350,6 +353,7 @@ def backtest_signal_ftmo(
max_leverage: float = FTMO_MAX_LEVERAGE,
bars_per_year: int = DEFAULT_BARS_PER_YEAR,
forward_returns: Optional[pd.Series] = None,
oos_start: Optional[str] = OOS_START_DEFAULT,
) -> Dict[str, Any]:
"""
FTMO-compliant backtest of a strategy signal on EUR/USD.
@@ -361,6 +365,7 @@ def backtest_signal_ftmo(
- FTMO daily loss limit (5%): positions zeroed rest of day after breach
- FTMO total loss limit (10%): all positions zeroed after breach
- FTMO-specific metrics added to result dict
- Walk-forward OOS split: IS metrics (before oos_start) + OOS metrics (after)
Parameters
----------
@@ -378,6 +383,8 @@ def backtest_signal_ftmo(
Hard stop-loss distance in pips (default 10).
max_leverage : float
Maximum leverage (default 30 = FTMO 1:30).
oos_start : str or None
Start of out-of-sample period (ISO date). None disables OOS split.
"""
stop_price = stop_pips * FTMO_PIP
leverage_by_risk = risk_pct / (stop_price / eurusd_price)
@@ -402,6 +409,37 @@ def backtest_signal_ftmo(
result["ftmo_end_equity"] = FTMO_INITIAL_CAPITAL * (1 + result.get("total_return", 0))
result["ftmo_monthly_profit"] = FTMO_INITIAL_CAPITAL * result.get("monthly_return", 0)
# Walk-forward OOS split
if oos_start is not None:
oos_ts = pd.Timestamp(oos_start)
is_mask = close.index < oos_ts
oos_mask = close.index >= oos_ts
def _split_bt(mask: "pd.Series[bool]", prefix: str) -> None:
if mask.sum() < 100:
return
close_s = close.loc[mask]
signal_s = signal.loc[mask] # raw signal, not masked — fresh FTMO sim per period
fwd_split = forward_returns.loc[mask] if forward_returns is not None else None
masked_s, _ = _apply_ftmo_mask(signal_s, close_s, leverage, txn_cost_bps)
split_result = backtest_signal(
close=close_s,
signal=masked_s,
txn_cost_bps=txn_cost_bps,
bars_per_year=bars_per_year,
forward_returns=fwd_split,
)
for k, v in split_result.items():
if k not in ("equity_curve", "status"):
result[f"{prefix}_{k}"] = v
_split_bt(is_mask, "is")
_split_bt(oos_mask, "oos")
result["oos_start"] = oos_start
result["is_n_bars"] = int(is_mask.sum())
result["oos_n_bars"] = int(oos_mask.sum())
return result