Stock Return calculation problem

[deanhystad]

If you want the percent change for each day I would do this:

import pandas_datareader as web
import pandas as pd

#Enter the stocks you want to use as variables
 
portfolio = {
    "BRK-B":0.2,
    "AMZN":0.3,
    "AAPL":0.1,
    "NFLX":0.2,
    "GOOG":0.2,
}
 
#select start date for correlation window as well as list of tickers
def percent_change(portfolio, start, end):
    pct_change = {}
    for ticker in portfolio:
        stock = web.get_data_yahoo(ticker, start=start, end=end)
        pct_change[ticker] = stock['Adj Close'].pct_change()[1:]
    return pd.DataFrame(pct_change)

pct_change = percent_change(portfolio, "2013-01-01", "2013-01-10")

weighted_change = pct_change * portfolio.values()
weighted_change['Total'] = weighted_change.sum(axis = 1)

countsum = []
cs = 100
for total in weighted_change["Total"]:
    cs *= (1 + total)
    countsum.append(cs)
weighted_change["Countsum"] = countsum

print(weighted_change)

Output:
               BRK-B      AMZN      AAPL      NFLX      GOOG     Total    Countsum
Date
2013-01-03  0.000901  0.001364 -0.001262  0.009955  0.000116  0.011075  101.107477
2013-01-04  0.000491  0.000778 -0.002785 -0.001263  0.003952  0.001173  101.226027
2013-01-07 -0.000852  0.010778 -0.000588  0.006710 -0.000873  0.015174  102.762025
2013-01-08  0.000770 -0.002324  0.000269 -0.004113 -0.000395 -0.005792  102.166791
2013-01-09 -0.001045 -0.000034 -0.001563 -0.002573  0.001315 -0.003900  101.768360
2013-01-10  0.002850 -0.001138  0.001240  0.004358  0.000910  0.008221  102.605005