engine passes realized daily vol to impact model

crypto_eval/engine.py

@@ -18,6 +18,12 @@ import pandas as pd
 from .costs import funding_cost, fee, slippage_cost
 
 
+def _realized_daily_vol_bps(close: pd.Series) -> float:
+    rets = close.pct_change().dropna()
+    ann = rets.std(ddof=1) * np.sqrt(24 * 365)
+    return float(ann / np.sqrt(365) * 1e4)
+
+
 def run_backtest(
     bars: pd.DataFrame,
     positions: pd.Series,
@@ -47,8 +53,10 @@ def run_backtest(
     # turnover: position changes at t fill at bar t's close
     dpos = pos.diff().fillna(pos.iloc[0])
     turnover_notional = (dpos.abs() * close)
+    daily_vol_bps = _realized_daily_vol_bps(close)
     fees = turnover_notional.map(lambda n: fee(n, fill_side))
-    slips = turnover_notional.map(lambda n: slippage_cost(n, adv_notional))
+    slips = turnover_notional.map(
+        lambda n: slippage_cost(n, adv_notional, daily_vol_bps))
 
     fund = funding_cost(pos, funding, close)