Copy# StratLab - Strategy Engine - Auto-Generated # Compatible: Alpaca, Interactive Brokers, Binance, CCXT # Data: Yahoo Finance (yfinance) - edit CONFIG only import pandas as pd, numpy as np, yfinance as yf from dataclasses import dataclass from typing import List import warnings; warnings.filterwarnings("ignore") CONFIG = { "tickers": ["SPY", "QQQ", "AAPL"], "start": "2018-01-01", "end": "2024-12-31", "interval": "1d", "capital": 100_000, "position_pct": 0.10, "stop_loss_pct": 0.02, "take_profit_pct": 0.04, "commission_bps": 2, "max_dd_halt": 0.20, "ema_fast": 9, "ema_slow": 21, "rsi_period": 14, "rsi_entry": 50, "rsi_exit": 70, } @dataclass class Trade: ticker: str; direction: str; entry_date: str; exit_date: str entry_price: float; exit_price: float; pnl: float; pnl_pct: float; reason: str class Engine: def __init__(self, cfg): self.cfg=cfg; self.equity=cfg["capital"]; self.peak=self.equity self.trades: List[Trade]=[]; self.curve=[self.equity]; self.halted=False def ema(self,s,n): return s.ewm(span=n,adjust=False).mean() def rsi(self,s,n=14): d=s.diff(); g=d.clip(0).rolling(n).mean(); l=(-d).clip(0).rolling(n).mean() return 100-100/(1+g/l.replace(0,np.nan)) def run(self,ticker): df=yf.download(ticker,start=self.cfg["start"],end=self.cfg["end"], interval=self.cfg["interval"],progress=False,auto_adjust=True) if df.empty: return [] c=self.cfg df["ef"]=self.ema(df["Close"],c["ema_fast"]); df["es"]=self.ema(df["Close"],c["ema_slow"]) df["rsi"]=self.rsi(df["Close"],c["rsi_period"]); df.dropna(inplace=True) in_trade=False; entry=None for i in range(1,len(df)): row,prev=df.iloc[i],df.iloc[i-1] if self.halted: break if not in_trade: if prev["ef"]<prev["es"] and row["ef"]>=row["es"] and row["rsi"]>c["rsi_entry"]: entry,in_trade=row,True else: pct=(row["Close"]-entry["Close"])/entry["Close"]; reason="" if pct<=-c["stop_loss_pct"]: reason="Stop Loss" elif pct>=c["take_profit_pct"]: reason="Take Profit" elif row["rsi"]>=c["rsi_exit"]: reason="RSI Exit" if reason: net=(pct-2*c["commission_bps"]/10000)*self.equity*c["position_pct"] self.equity+=net if self.equity>self.peak: self.peak=self.equity if 1-self.equity/self.peak>=c["max_dd_halt"]: self.halted=True self.trades.append(Trade(ticker,"LONG",str(entry.name)[:10],str(row.name)[:10], float(entry["Close"]),float(row["Close"]),net,pct*100,reason)) self.curve.append(self.equity); in_trade=False return self.trades class AlpacaBroker: def connect(self,key,secret,base="https://paper-api.alpaca.markets"): pass def order(self,sym,qty,side="buy"): pass class IBKRBroker: def connect(self,host="127.0.0.1",port=7497): pass def order(self,sym,qty,side="BUY"): pass if __name__=="__main__": engine=Engine(CONFIG) for t in CONFIG["tickers"]: trades=engine.run(t); wr=sum(1 for x in trades if x.pnl>0)/max(len(trades),1) print(f"{t}: {len(trades)} trades | WR {wr:.1%} | ${engine.equity:,.0f}")