analysis_ta_volatility_indicator_loop.py

import numpy as np
import pandas as pd
import talib as ta
from talib import MA_Type
import os
import configparser 

parser = configparser.ConfigParser()
parser.read('config.ini')

current_dir = os.path.dirname(os.path.realpath(__file__))

base_dir = parser.get('directory','base_dir')
in_dir = parser.get('directory','company_datalist_prefilter')
in_dir1 = parser.get('directory','company_stock_marketprice_baseprice_prefilter')
out_dir = parser.get('directory','company_stock_marketprice_processed')

comp_datalist = pd.read_csv(current_dir+"/"+base_dir+"/"+in_dir+"/"+in_dir+"_combined.csv")

for i in range(0,comp_datalist['stock_symbol'].count()):
    try:

        # read csv file and transform it to datafeed (df):
        df = pd.read_csv(current_dir+"/"+base_dir+"/"+in_dir1+"/"+in_dir1+'_'+comp_datalist['stock_symbol'][i]+'.csv')

        print("[Status]Processing TA Volatility Indicator for "+comp_datalist['stock_symbol'][i])

        # set numpy datafeed from df:
        df_numpy = {
            'Date': np.array(df['date']),
            'Open': np.array(df['open'], dtype='float'),
            'High': np.array(df['high'], dtype='float'),
            'Low': np.array(df['low'], dtype='float'),
            'Close': np.array(df['close'], dtype='float'),
            'Volume': np.array(df['volume'], dtype='float')
            }

        date = df_numpy['Date']
        openp = df_numpy['Open']
        high = df_numpy['High']
        low = df_numpy['Low']
        close = df_numpy['Close']
        volume = df_numpy['Volume']


        #########################################
        ###  Volatility Indicator Functions  ####
        #########################################




        #ATR - Average True Range
        atr = ta.ATR(high, low, close, timeperiod=14)

        #NATR - Normalized Average True Range
        natr = ta.NATR(high, low, close, timeperiod=14)

        #TRANGE - True Range
        trange = ta.TRANGE(high, low, close)



        
        df_save = pd.DataFrame(data ={
            'date': np.array(df['date']),
            'atr' :atr,
            'natr':natr,
            'trange':trange
        })

        df_save.to_csv(current_dir+"/"+base_dir+"/"+out_dir+'/'+comp_datalist['stock_symbol'][i]+"/"+out_dir+'_ta_volatility_indicator_'+comp_datalist['stock_symbol'][i]+'.csv',index=False)

    except:
        print("[Status]Error fail to processed TA Volatility Indicator for "+comp_datalist['stock_symbol'][i])