プログラミングで投資分析する方法【Pythonで2022年の投資リターンを比較】

from pandas_datareader import data
import pandas as pd
from pylab import mpl, plt
import numpy as np
from datetime import date
plt.style.use('seaborn')
mpl.rcParams['font.family'] = 'serif'
%matplotlib inline

def make_chart(symbol,source,start,end):
    df = data.DataReader(symbol, source, start, end)
    price = df['Close']
    
    ratio = price / price[0] * 100
    date = ratio.index
    return date, ratio

start = '2022-01-01'
end = date.today()

gold_date, gold_ratio = make_chart('GC=F', 'yahoo',start,end)
stock_date, stock_ratio = make_chart('^GSPC', 'yahoo',start,end)
btc_date, btc_ratio = make_chart('BTC-USD', 'yahoo',start,end)
oil_date, oil_ratio = make_chart('CL=F', 'yahoo',start,end)
usdjpy_date, usdjpy_ratio = make_chart('USDJPY=X', 'yahoo',start,end)

plt.figure(figsize=(15, 10))
plt.plot(gold_date, gold_ratio, label = 'Gold', color='y')
plt.plot(stock_date, stock_ratio, label = 'S&P500', color='g')
plt.plot(btc_date, btc_ratio, label = 'Bitcoin', color='r')
plt.plot(oil_date, oil_ratio, label = 'Crude Oil', color='b')
plt.plot(usdjpy_date, usdjpy_ratio, label = 'USD-JPY', color='black')
plt.legend(loc=2, fontsize=18)
plt.xlabel('year', fontsize=18)
plt.ylabel('return', fontsize=18)
plt.tick_params(labelsize=18)
plt.savefig("2022chart.png")