import yfinance as yf import pandas as pd def process_dataframe(df): def get_rsi(close, lookback): ret = close.diff() up = [] down = [] for i in range(len(ret)): if ret[i] < 0: up.append(0) down.append(ret[i]) else: up.append(ret[i]) down.append(0) up_series = pd.Series(up) down_series = pd.Series(down).abs() up_ewm = up_series.ewm(com=lookback - 1, adjust=False).mean() down_ewm = down_series.ewm(com=lookback - 1, adjust=False).mean() rs = up_ewm / down_ewm rsi = 100 - (100 / (1 + rs)) rsi_df = pd.DataFrame(rsi).rename(columns={0: 'RSI'}).set_index(close.index) rsi_df = rsi_df.dropna() return rsi_df[3:] df['RSI'] = get_rsi(df['Close'], 14) df['SMA20'] = df['Close'].rolling(window=20).mean() df.drop(['Adj Close'], axis=1, inplace=True) df = df.dropna() return df def fin_data(ticker, startdate, enddate): df=yf.download(ticker,start=startdate,end=enddate, progress=False) df = process_dataframe(df) df.reset_index(inplace=True) df = df.dropna() df.reset_index(drop=True, inplace=True) df[['Open', 'High', 'Low', 'Close',"RSI"]] = df[['Open', 'High', 'Low', 'Close',"RSI"]].round(2) df = df[200:] df.reset_index(drop=True,inplace=True) return df def eqt(ticker, startdate, enddate, share_qty = 90): df = fin_data(ticker, startdate, enddate) entry = False trading = False shares_held = 0 buy_price = 0 target1 = False target2 = False target3 = False tgt1 = 0 tgt2 = 0 tgt3 = 0 total_profit = 0 profits = [] stop_loss = 0 capital_list = [] start_date = [] end_date = [] for i in range(1, len(df)-1): try: if df.at[i, 'RSI'] > 60 and df.at[i - 1, 'RSI'] < 60 and df.at[i, 'High'] < df.at[i + 1, 'High'] and not entry and not trading: buy_price = df.at[i, 'High'] stop_loss = df.at[i, 'Low'] start_date.append(df.at[i, 'Date']) capital = buy_price * share_qty capital_list.append(round(capital, 2)) shares_held = share_qty entry = True trading = True if trading and not target1: if (df.at[i + 1, 'High'] - buy_price) >= 0.02 * buy_price: stop_loss = buy_price target1 = True tgt1 = 0.02 * buy_price * (share_qty / 3) shares_held -= (share_qty / 3) total_profit = tgt1 if trading and target1 and not target2: if (df.at[i + 1, 'High'] - buy_price) >= 0.04 * buy_price: target2 = True tgt2 = 0.04 * buy_price * (share_qty / 3) total_profit += tgt2 shares_held -= (share_qty / 3) if trading and target2 and not target3: if (df.at[i + 1, 'Open'] < df.at[i + 1, 'SMA20'] < df.at[i + 1, 'Close']) or (df.at[i + 1, 'Open'] > df.at[i + 1, 'SMA20'] > df.at[i + 1, 'Close']): stop_loss = df.at[i + 1, 'Low'] if df.at[i + 2, 'Low'] < stop_loss: target3 = True tgt3 = stop_loss * (share_qty / 3) shares_held -= (share_qty / 3) total_profit += tgt3 if (df.at[i + 1, 'Low'] < stop_loss and trading): profit_loss = (shares_held * stop_loss) - (shares_held * buy_price) total_profit += profit_loss profits.append(total_profit) end_date.append(df.at[i, 'Date']) shares_held = 0 buy_price = 0 entry = False trading = False target1 = target2 = target3 = False tgt1 = tgt2 = tgt3 = 0 total_profit = 0 except IndexError: continue print("\n") print(f"Stock: {ticker} - From {df.at[1, 'Date']} to {df.at[len(df) - 1, 'Date']}") print(f"Required capital Range equity per trade: {round(capital_list[0],2)} ₹ - {round(capital_list[-1],2)} ₹") print("Duration Total Trading Profit:", round(sum(profits), 2),"₹") if profits: if len(start_date) > len(end_date): rr = len(end_date) df = pd.DataFrame({"Start" : start_date[:rr], "End": end_date, "profit" : profits, "Capital" : capital_list[:rr]}) df['percentage'] = (df['profit'] / df['Capital']) * 100 df['percentage'] = df['percentage'].apply(lambda x: f"{x:.2f}%" if x >= 0 else f"-{-x:.2f}%") else: df = pd.DataFrame({"Start" : start_date, "End": end_date, "profit" : profits, "Capital" : capital_list}) df['percentage'] = (df['profit'] / df['Capital']) * 100 df['percentage'] = df['percentage'].apply(lambda x: f"{x:.2f}%" if x >= 0 else f"-{-x:.2f}%") return df else: return 0