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9ff4b7f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | import numpy as np
from typing import Dict, Any
from config import (
MAX_RISK_PER_TRADE,
HIGH_VOLATILITY_THRESHOLD,
REDUCED_RISK_FACTOR,
)
def compute_stop_distance(atr: float, multiplier: float = 2.0) -> float:
return atr * multiplier
def compute_position_size(
account_equity: float,
entry_price: float,
stop_distance: float,
risk_fraction: float = MAX_RISK_PER_TRADE,
) -> float:
if stop_distance <= 0 or entry_price <= 0:
return 0.0
dollar_risk = account_equity * risk_fraction
units = dollar_risk / stop_distance
notional = units * entry_price
return notional
def compute_risk_fraction(
vol_ratio: float,
regime_score: float,
base_risk: float = MAX_RISK_PER_TRADE,
) -> float:
risk = base_risk
if vol_ratio > HIGH_VOLATILITY_THRESHOLD:
risk *= REDUCED_RISK_FACTOR
if regime_score < 0.4:
risk *= REDUCED_RISK_FACTOR
elif regime_score < 0.6:
risk *= 0.75
return float(np.clip(risk, 0.001, base_risk))
def evaluate_risk(
df_last_close: float,
atr: float,
atr_pct: float,
regime_score: float,
vol_ratio: float,
account_equity: float = 10000.0,
stop_multiplier: float = 2.0,
) -> Dict[str, Any]:
stop_distance = compute_stop_distance(atr, stop_multiplier)
risk_fraction = compute_risk_fraction(vol_ratio, regime_score)
position_notional = compute_position_size(
account_equity, df_last_close, stop_distance, risk_fraction
)
stop_price_long = df_last_close - stop_distance
stop_price_short = df_last_close + stop_distance
risk_reward_target = stop_distance * 2.0
target_long = df_last_close + risk_reward_target
target_short = df_last_close - risk_reward_target
return {
"entry_price": df_last_close,
"atr": atr,
"atr_pct": atr_pct,
"stop_distance": stop_distance,
"stop_price_long": stop_price_long,
"stop_price_short": stop_price_short,
"target_long": target_long,
"target_short": target_short,
"risk_fraction": risk_fraction,
"position_notional": position_notional,
"vol_ratio": vol_ratio,
"regime_score": regime_score,
}
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