8-tillson_t3_indicator.py

# -*- coding: utf-8 -*-
"""
Created on Tue May 28 15:22:58 2024

@author: Yunus
"""

"""
This Python script is designed to fetch stock data from the Istanbul Stock Exchange (BIST) using the tvDatafeed library, 
calculate the Tillson T3 indicator, and identify buy and sell signals based on the 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)

# Tillson onay için sinyal 2 bar gecikmeli
def TillsonT3(data, Length=14, vf=0.7,app=2):
    df = data.copy()

    ema_first_input = (df['High'] + df['Low'] + 2 * df['Close']) / 4
    e1 = ta.ema(ema_first_input, Length)
    e2 = ta.ema(e1, Length)
    e3 = ta.ema(e2, Length)
    e4 = ta.ema(e3, Length)
    e5 = ta.ema(e4, Length)
    e6 = ta.ema(e5, Length)

    c1 = -1 * vf * vf * vf
    c2 = 3 * vf * vf + 3 * vf * vf * vf
    c3 = -6 * vf * vf - 3 * vf - 3 * vf * vf * vf
    c4 = 1 + 3 * vf + vf * vf * vf + 3 * vf * vf
    df['T3'] = c1 * e6 + c2 * e5 + c3 * e4 + c4 * e3
    df['Entry'] = False
    df['Exit'] = False
    df['Entry']=df['T3'] > df['T3'].shift(1)
    df['Exit']=df['T3'] < df['T3'].shift(1)

    df['Entry']=(df['Entry'] & df['Entry'].shift(app))
    df['Exit']=(df['Exit'] & df['Exit'].shift(app))
    return df


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)

#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()

for i in range(0,len(Hisseler)):
    #print(Hisseler[i])
    try:
        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()
        Tillson=TillsonT3(data,2,14,2)    #Sondaki 2 Gecikmeli sinyal sayısı Tillson Onayı için önemli
        Tillson['datetime'] = pd.to_datetime(Tillson['datetime'])
        Tillson.set_index('datetime', inplace=True)
        bt = Backtest(Tillson, Strategy, cash=100000, commission=0.002)
        Stats = bt.run()
        Buy = False
        Sell = False
        Signals = Tillson.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)