epic-strategy

bySheda Tali

import pandas as pd import ta # ===================== # SETTINGS FOR $50 ACCOUNT # ===================== RISK_PERCENT = 0.01 # 1% risk FAST_EMA = 9 SLOW_EMA = 21 RSI_PERIOD = 14 ATR_PERIOD = 14 # ===================== # INDICATORS # ===================== def apply_strategy(df): df['ema_fast'] = ta.trend.ema_indicator(df['close'], window=FAST_EMA) df['ema_slow'] = ta.trend.ema_indicator(df['close'], window=SLOW_EMA) df['rsi'] = ta.momentum.rsi(df['close'], window=RSI_PERIOD) df['atr'] = ta.volatility.average_true_range( df['high'], df['low'], df['close'], window=ATR_PERIOD ) return df # ===================== # POSITION SIZE CALCULATION # ===================== def position_size(balance, stop_loss_distance): risk_amount = balance * RISK_PERCENT size = risk_amount / stop_loss_distance return size # ===================== # TRADE SIGNAL # ===================== def check_signal(df, balance): latest = df.iloc[-1] if latest['ema_fast'] > latest['ema_slow'] and latest['rsi'] < 70: entry = latest['close'] stop_loss = entry - latest['atr'] take_profit = entry + (latest['atr'] * 1.5) size = position_size(balance, entry - stop_loss) print("BUY SIGNAL") print("Position Size:", size) print("SL:", stop_loss) print("TP:", take_profit) elif latest['ema_fast'] < latest['ema_slow'] and latest['rsi'] > 30: entry = latest['close'] stop_loss = entry + latest['atr'] take_profit = entry - (latest['atr'] * 1.5) size = position_size(balance, stop_loss - entry) print("SELL SIGNAL") print("Position Size:", size) print("SL:", stop_loss) print("TP:", take_profit) # ===================== # RUN # ===================== df = pd.read_csv("market_data.csv") df = apply_strategy(df) account_balance = 50 check_signal(df, account_balance)