7-supertrend_indicator.py

# -*- coding: utf-8 -*-
"""
Created on Tue May 28 15:17:04 2024

@author: Yunus
"""

"""
This Python script fetches stock data from the Istanbul Stock Exchange (BIST) using the tvDatafeed library, 
applies the Supertrend indicator, and identifies stocks that generate entry and exit signals based on this indicator.
"""

# !pip install pandas_ta
# !pip install mplcyberpunk
# !pip install git+https://github.com/rongardF/tvdatafeed
# !pip install tradingview-screener
# !pip install backtesting


import pandas as pd
import pandas_ta as ta
import numpy as np
import matplotlib.pyplot as plt
from tvDatafeed import TvDatafeed, Interval
from backtesting import Backtest, Strategy
from tradingview_screener import get_all_symbols
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)


def Supertrend(data,SENSITIVITY = 3,ATR_PERIOD = 14):
    df=data.copy()
    df['xATR'] = ta.atr(data['High'], data['Low'], data['Close'], timeperiod=ATR_PERIOD) # Average True Range (ATR)
    df['nLoss'] = SENSITIVITY * df['xATR']
    # Filling ATRTrailing Variable
    df['ATRTrailing'] = [0.0] + [np.nan for i in range(len(df) - 1)]

    for i in range(1, len(df)):
        if (df.loc[i, 'Close'] > df.loc[i - 1, 'ATRTrailing']) and (df.loc[i - 1, 'Close'] > df.loc[i - 1, 'ATRTrailing']):
            df.loc[i, 'ATRTrailing'] = max(df.loc[i - 1, 'ATRTrailing'],df.loc[i, 'Close']-df.loc[i,'nLoss'])

        elif (df.loc[i, 'Close'] < df.loc[i - 1, 'ATRTrailing']) and (df.loc[i - 1, 'Close'] < df.loc[i - 1, 'ATRTrailing']):
            df.loc[i, 'ATRTrailing'] = min(df.loc[i - 1, 'ATRTrailing'],df.loc[i, 'Close']+df.loc[i,'nLoss'])

        elif df.loc[i, 'Close'] > df.loc[i - 1, 'ATRTrailing']:
            df.loc[i, 'ATRTrailing']=df.loc[i, 'Close']-df.loc[i,'nLoss']
        else:
            df.loc[i, 'ATRTrailing']=df.loc[i, 'Close']+df.loc[i,'nLoss']

    # Calculating signals
    ema = ta.ema(df['Close'], 1)
    df['Above'] = ema > (df['ATRTrailing'])
    df['Below'] = ema < (df['ATRTrailing'])
    df['Entry'] = (df['Close'] > df['ATRTrailing']) & (df['Above']==True)
    df['Exit'] = (df['Close'] < df['ATRTrailing']) & (df['Below']==True)
    return df


#Backtest için gerekli class yapısı
class Strategy(Strategy):
    def init(self):
        pass
    def next(self):
        if self.data['Entry'] == True and not self.position:
            self.buy()

        elif self.data['Exit'] == True:
            self.position.close()

tv = TvDatafeed()
Hisseler = get_all_symbols(market='turkey')
Hisseler = [symbol.replace('BIST:', '') for symbol in Hisseler]
Hisseler = sorted(Hisseler)

#Raporlama için kullanılacak başlıklar
Titles = ['Hisse Adı', 'Son Fiyat','Kazanma Oranı','Giriş Sinyali', 'Çıkış Sinyali']

df_signals = pd.DataFrame(columns=Titles)

for i in range(0,len(Hisseler)):
    #print(Hisseler[i])
    try:
        S=3
        ATR=14
        data = tv.get_hist(symbol=Hisseler[i], exchange='BIST', interval=Interval.in_1_hour, n_bars=500)
        data.rename(columns={'open': 'Open', 'high': 'High', 'low': 'Low', 'close': 'Close', 'volume': 'Volume'}, inplace=True)
        data = data.reset_index()
        Supert = Supertrend(data,S,ATR)
        Supert['datetime'] = pd.to_datetime(Supert['datetime'])
        Supert.set_index('datetime', inplace=True)
        bt = Backtest(Supert, Strategy, cash=100000, commission=0.002)
        Stats = bt.run()
        Buy = False
        Sell = False
        Signals = Supert.tail(2)
        Signals = Signals.reset_index()
        Buy = Signals.loc[0, 'Entry'] == False and Signals.loc[1, 'Entry'] ==True
        Sell = Signals.loc[0, 'Exit'] == False and Signals.loc[1, 'Exit'] == True
        Last_Price = Signals.loc[1, 'Close']
        L1 = [Hisseler[i],Last_Price, round(Stats.loc['Win Rate [%]'], 2), str(Buy), str(Sell)]
        df_signals.loc[len(df_signals)] = L1
        print(L1)
    except:
        pass

df_True = df_signals[(df_signals['Giriş Sinyali'] == 'True')]
print(df_True)