diff --git a/quants_lab/strategy/experiments/stat_arb.py b/quants_lab/strategy/experiments/stat_arb.py
index 8ec47fd..d528bd0 100644
--- a/quants_lab/strategy/experiments/stat_arb.py
+++ b/quants_lab/strategy/experiments/stat_arb.py
@@ -1,32 +1,38 @@
 import pandas as pd
 import pandas_ta as ta
+from pydantic import BaseModel, Field
+
 from quants_lab.strategy.directional_strategy_base import DirectionalStrategyBase
 
-from quants_lab.utils import data_management
+
+class StatArbConfig(BaseModel):
+    exchange: str = Field(default="binance_perpetual")
+    trading_pair: str = Field(default="ETH-USDT")
+    target_trading_pair: str = Field(default="BTC-USDT")
+    interval: str = Field(default="1h")
+    lookback: int = Field(default=100, ge=2, le=10000)
+    z_score_long: float = Field(default=2, ge=0, le=5)
+    z_score_short: float = Field(default=-2, ge=-5, le=0)
 
 
 class StatArb(DirectionalStrategyBase):
-    def __init__(self,
-                 exchange="binance_perpetual",
-                 trading_pair="DOGE-USDT",
-                 target_trading_pair="BTC-USDT",
-                 interval="1h",
-                 periods=100,
-                 deviation_threshold=1.1):
-        self.exchange = exchange
-        self.trading_pair = trading_pair
-        self.interval = interval
-        self.target_trading_pair = target_trading_pair
-        self.periods = periods
-        self.deviation_threshold = deviation_threshold
+    def __init__(self, config: StatArbConfig):
+        super().__init__(config)
+        self.exchange = config.exchange
+        self.trading_pair = config.trading_pair
+        self.target_trading_pair = config.target_trading_pair
+        self.interval = config.interval
+        self.lookback = config.lookback
+        self.z_score_long = config.z_score_long
+        self.z_score_short = config.z_score_short
 
     def get_raw_data(self):
-        df = data_management.get_dataframe(
+        df = self.get_candles(
             exchange=self.exchange,
             trading_pair=self.trading_pair,
             interval=self.interval,
         )
-        df_target = data_management.get_dataframe(
+        df_target = self.get_candles(
             exchange=self.exchange,
             trading_pair=self.target_trading_pair,
             interval=self.interval,
@@ -38,14 +44,14 @@ class StatArb(DirectionalStrategyBase):
         df["pct_change_original"] = df["close"].pct_change()
         df["pct_change_target"] = df["close_target"].pct_change()
         df["spread"] = df["pct_change_target"] - df["pct_change_original"]
-        df["cum_spread"] = df["spread"].rolling(self.periods).sum()
-        df["z_score"] = ta.zscore(df["cum_spread"], length=self.periods)
+        df["cum_spread"] = df["spread"].rolling(self.lookback).sum()
+        df["z_score"] = ta.zscore(df["cum_spread"], length=self.lookback)
         return df
 
     def predict(self, df):
         df["side"] = 0
-        short_condition = df["z_score"] < - self.deviation_threshold
-        long_condition = df["z_score"] > self.deviation_threshold
+        short_condition = df["z_score"] < - self.z_score_short
+        long_condition = df["z_score"] > self.z_score_long
         df.loc[long_condition, "side"] = 1
         df.loc[short_condition, "side"] = -1
         return df