Files
noteQuant-backtest/backend/engine/backtester.py
T
2026-04-13 20:37:21 +02:00

226 lines
8.2 KiB
Python

from data.model import Trade
from collections import defaultdict
import math
def _apply_break_even_if_triggered(position, candle, strategy):
if not position:
return
if not getattr(strategy, "use_break_even", False):
return
if position.get("break_even_armed"):
return
trigger_rr = float(getattr(strategy, "be_trigger_rr", 1.0) or 0.0)
if trigger_rr <= 0:
return
is_long = position["direction"] == "long"
entry = position["entry_price"]
risk_distance = max(position.get("risk_distance", 0.0), 0.0)
if risk_distance <= 0:
return
trigger_price = entry + (risk_distance * trigger_rr) if is_long else entry - (risk_distance * trigger_rr)
reached_trigger = candle.high >= trigger_price if is_long else candle.low <= trigger_price
if reached_trigger:
position["stop_loss"] = entry
position["break_even_armed"] = True
def run_backtest(candles, strategy, starting_balance, risk_reward=1.0,
max_daily_loss=0.0, max_consecutive_losses=0, risk_pct=1.0):
trades = []
position = None
consecutive_losses = 0
daily_pnl = defaultdict(float)
if hasattr(strategy, "prepare"):
strategy.prepare(candles)
for i, candle in enumerate(candles):
if position:
_apply_break_even_if_triggered(position, candle, strategy)
is_long = position["direction"] == "long"
sl, tp = position["stop_loss"], position["take_profit"]
hit_sl = candle.low <= sl if is_long else candle.high >= sl
hit_tp = candle.high >= tp if is_long else candle.low <= tp
if hit_sl or hit_tp:
exit_price = sl if hit_sl else tp
price_move = (exit_price - position["entry_price"]) if is_long else (position["entry_price"] - exit_price)
lot_size = max(position.get("lot_size", 0.0), 0.0)
pnl = price_move * lot_size
risk_distance = max(position.get("risk_distance", 0.0), 1e-12)
r_multiple = price_move / risk_distance
trades.append(Trade(
enter_time=position["enter_time"],
enter_price=position["entry_price"],
direction=position["direction"],
exit_time=candle.time_open,
exit_price=exit_price,
pnl=pnl,
r_multiple=r_multiple,
))
position = None
if pnl <= 0:
consecutive_losses += 1
else:
consecutive_losses = 0
daily_pnl[candle.time_open.date()] += pnl
if position is None:
if max_consecutive_losses > 0 and consecutive_losses >= max_consecutive_losses:
continue
if max_daily_loss > 0:
loss_limit = starting_balance * (max_daily_loss / 100)
if daily_pnl[candle.time_open.date()] <= -loss_limit:
continue
signal = strategy.check_signal(candles, i)
if signal is not None:
is_long = signal.direction == "BUY"
entry = signal.entry_price
sl = signal.stop_loss
sl_distance = abs(entry - sl)
if (
sl_distance <= 0
or not math.isfinite(sl_distance)
or not math.isfinite(entry)
or not math.isfinite(sl)
or risk_pct <= 0
):
continue
risk_amount = starting_balance * (risk_pct / 100)
if risk_amount <= 0 or not math.isfinite(risk_amount):
continue
lot_size = risk_amount / sl_distance
if lot_size <= 0 or not math.isfinite(lot_size):
continue
tp = entry + (sl_distance * risk_reward) if is_long else entry - (sl_distance * risk_reward)
position = {
"direction": "long" if is_long else "short",
"entry_price": entry,
"enter_time": candle.time_open,
"stop_loss": sl,
"take_profit": tp,
"risk_distance": sl_distance,
"lot_size": lot_size,
"break_even_armed": False,
}
return trades
def run_backtest_stream(candles, strategy, starting_balance, risk_reward=1.0,
max_daily_loss=0.0, max_consecutive_losses=0, risk_pct=1.0):
position = None
consecutive_losses = 0
daily_pnl = defaultdict(float)
total = len(candles)
if hasattr(strategy, "prepare"):
strategy.prepare(candles)
yield {"type": "start", "total_candles": total}
progress_interval = max(1, total // 50)
for i, candle in enumerate(candles):
if i % progress_interval == 0:
yield {"type": "progress", "processed_candles": i, "total_candles": total}
if position:
_apply_break_even_if_triggered(position, candle, strategy)
is_long = position["direction"] == "long"
sl, tp = position["stop_loss"], position["take_profit"]
hit_sl = candle.low <= sl if is_long else candle.high >= sl
hit_tp = candle.high >= tp if is_long else candle.low <= tp
if hit_sl or hit_tp:
exit_price = sl if hit_sl else tp
price_move = (exit_price - position["entry_price"]) if is_long else (position["entry_price"] - exit_price)
lot_size = max(position.get("lot_size", 0.0), 0.0)
pnl = price_move * lot_size
risk_distance = max(position.get("risk_distance", 0.0), 1e-12)
r_multiple = price_move / risk_distance
trade = Trade(
enter_time=position["enter_time"],
enter_price=position["entry_price"],
direction=position["direction"],
exit_time=candle.time_open,
exit_price=exit_price,
pnl=pnl,
r_multiple=r_multiple,
)
position = None
if pnl <= 0:
consecutive_losses += 1
else:
consecutive_losses = 0
daily_pnl[candle.time_open.date()] += pnl
yield {"type": "trade", "trade": trade, "processed_candles": i, "total_candles": total}
if position is None:
if max_consecutive_losses > 0 and consecutive_losses >= max_consecutive_losses:
continue
if max_daily_loss > 0:
loss_limit = starting_balance * (max_daily_loss / 100)
if daily_pnl[candle.time_open.date()] <= -loss_limit:
continue
signal = strategy.check_signal(candles, i)
if signal is not None:
is_long = signal.direction == "BUY"
entry = signal.entry_price
sl = signal.stop_loss
sl_distance = abs(entry - sl)
if (
sl_distance <= 0
or not math.isfinite(sl_distance)
or not math.isfinite(entry)
or not math.isfinite(sl)
or risk_pct <= 0
):
continue
risk_amount = starting_balance * (risk_pct / 100)
if risk_amount <= 0 or not math.isfinite(risk_amount):
continue
lot_size = risk_amount / sl_distance
if lot_size <= 0 or not math.isfinite(lot_size):
continue
tp = entry + (sl_distance * risk_reward) if is_long else entry - (sl_distance * risk_reward)
position = {
"direction": "long" if is_long else "short",
"entry_price": entry,
"enter_time": candle.time_open,
"stop_loss": sl,
"take_profit": tp,
"risk_distance": sl_distance,
"lot_size": lot_size,
"break_even_armed": False,
}
yield {"type": "done", "total_candles": total}