chartingPosition.py

import os
import pandas as pd
import numpy as np
import yfinance as yf
import datetime as dt
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style = 'ticks', context = 'talk')
plt.style.use("dark_background")

pd.options.mode.chained_assignment = None

def barchart(df):
    ax = sns.barplot(x = 'Year', y = 'Return', data = df)
    vals = ax.get_yticks()
    ax.set_yticklabels(['{:,.1%}'.format(x) for x in vals])

def findReplaceDate(x, dates):
    diffs = (dates - x).days
    diff0 = diffs[ diffs < 0 ].max()
    return dates[ np.where(diffs == diff0)[0][0] ]
    
def singlesDayRet(prices, singlesDays, days, enter = 0):
    returns = prices.pct_change(days)
    dates = returns.index
    datesInd = np.array([ np.where(dates == x)[0][0] + enter + days for x in singlesDays ])
    singlesReturns = returns[ returns.index.isin(dates[datesInd]) ]
    singlesReturns.columns = ['Return']
    singlesReturns['Year'] = singlesReturns.index.year
    
    return singlesReturns
    
if __name__ == '__main__':
    
    ticker = 'BABA' #can change to any ticker
    varName = 'Adj Close'
    
    startDate = dt.datetime(year = 2010, month = 1, day = 1)
    today = dt.datetime.now()
    
    startDate = startDate.strftime('%Y-%m-%d')
    endDate = today.strftime('%Y-%m-%d')
    
    prices = yf.download(ticker, startDate, endDate)[[varName]]
    prices.rename(columns = {varName:ticker}, inplace = True)
    minYear = prices.index.min().year
    maxYear = prices.index.max().year
    if today <= dt.datetime(year = today.year, month = 11, day = 11):
        maxYear -= 1
    
    prices = prices [ prices.index.year <= maxYear ]
    
    dates = prices.index
    
    singlesDays = [ dt.datetime(year = x, month = 11, day = 11) for x in range(minYear,maxYear+1)]
    singlesDaysAdd = [ x for x in singlesDays  if x not in dates ]
    replaceDays = [ findReplaceDate(x, dates) for x in singlesDaysAdd ]
    prices.rename(index = dict(zip(replaceDays, singlesDaysAdd)), inplace = True)
    
    singlesReturns5_0 = singlesDayRet(prices, singlesDays, days = 5, enter = 0)
    barchart(singlesReturns5_0)