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from __future__ import annotations
from typing import Optional, Literal
import pandas as pd
from datetime import datetime
from .models import TradePlan, PositionState
def _hits_level(low: float, high: float, level: float) -> bool:
return low <= level <= high
def _decide_exit_on_bar(
side: Literal["long", "short"], low: float, high: float, target: float, stoploss: float,
tiebreaker: Literal["stoploss_first", "target_first"] = "stoploss_first",
) -> Optional[dict]:
if side == "long":
hit_target = high >= target
hit_stop = low <= stoploss
else:
hit_target = low <= target
hit_stop = high >= stoploss
if not hit_target and not hit_stop:
return None
if hit_target and hit_stop:
return {"reason": "stoploss" if tiebreaker == "stoploss_first" else "target",
"price": stoploss if tiebreaker == "stoploss_first" else target}
return {"reason": "target", "price": target} if hit_target else {"reason": "stoploss", "price": stoploss}
def simulate_trade_from_signal(
df: pd.DataFrame,
trade: TradePlan,
*,
dt_col: str = "datetime",
tiebreaker: Literal["stoploss_first", "target_first"] = "stoploss_first",
lookback_minutes: int = 60,
state: PositionState,
) -> PositionState:
required = {"open","high","low","close", dt_col}
if missing := [c for c in required if c not in df.columns]:
raise ValueError(f"Missing columns: {missing}")
if trade.status == "No trade":
return state
side = trade.type
entry_at = float(trade.entry_at)
target = float(trade.target)
stoploss = float(trade.stoploss)
ts = pd.to_datetime(df[dt_col])
entered = state.entered
exited = state.exited
entry_time = state.entry_time
entry_price = state.entry_price
exit_time = state.exit_time
exit_price = state.exit_price
exit_reason = state.exit_reason
if not entered:
if side=="long" and entry_at<=stoploss:
return PositionState(
entered=entered, entry_time=entry_time, entry_price=entry_price, side=side,
exited=exited, exit_time=exit_time, exit_price=exit_price, exit_reason=exit_reason,
pnl_pct=state.pnl_pct, open_position=state.open_position, unrealized_pct=state.unrealized_pct,
note="Error in pricing: Stoploss is higher than entry price for long side position, please adjust stoploss or entry price"
)
elif side=="short" and entry_at>=stoploss:
return PositionState(
entered=entered, entry_time=entry_time, entry_price=entry_price, side=side,
exited=exited, exit_time=exit_time, exit_price=exit_price, exit_reason=exit_reason,
pnl_pct=state.pnl_pct, open_position=state.open_position, unrealized_pct=state.unrealized_pct,
note="Error in pricing: Stoploss is lower than entry price for short side position, please adjust stoploss or entry price"
)
# iterate last 'lookback_minutes' rows (assumes 1m bars)
start_idx = max(0, abs(len(df) - int(lookback_minutes)))
for i in range(start_idx, len(df)):
row = df.iloc[i]
time_i, o, h, l, c = ts.iloc[i], float(row['open']), float(row['high']), float(row['low']), float(row['close'])
if not entered:
if _hits_level(l, h, entry_at):
entered = True
entry_time = time_i
entry_price = entry_at
out = _decide_exit_on_bar(side, l, h, target, stoploss, tiebreaker)
if out:
exited = True
exit_time = time_i
exit_price = out["price"]
exit_reason = out["reason"]
break
else:
out = _decide_exit_on_bar(side, l, h, target, stoploss, tiebreaker)
if out:
exited = True
exit_time = time_i
exit_price = out["price"]
exit_reason = out["reason"]
break
def _pnl_pct(entry: float, exit_: float, side_: str) -> float:
raw = (exit_ - entry) / entry
return (raw if side_ == "long" else -raw) * 100.0
if entered and exited:
pnl = round(_pnl_pct(entry_price, exit_price, side), 4)
return PositionState(
entered=True, entry_time=entry_time, entry_price=entry_price, side=side,
exited=True, exit_time=exit_time, exit_price=exit_price, exit_reason=exit_reason,
pnl_pct=pnl, open_position=False, unrealized_pct=None,
)
if entered and not exited:
last_close = float(df.iloc[-1]["close"]) if len(df) else entry_price
upnl = round(_pnl_pct(entry_price, last_close, side), 4)
return PositionState(
entered=True, entry_time=entry_time, entry_price=entry_price, side=side,
exited=False, open_position=True, unrealized_pct=upnl,
)
return state # entry level never touched
def slice_intraday(df_1m: pd.DataFrame, start: datetime, end: datetime, dt_col: str = "datetime") -> pd.DataFrame:
mask = (df_1m[dt_col] >= start) & (df_1m[dt_col] < end)
out = df_1m.loc[mask].copy()
out.reset_index(drop=True, inplace=True)
return out
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