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stratagy/rsi_stratagy.py

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+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