プログラミングで投資の分析をして気づいた驚きの事実！2022年はコモディティの時代になる

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

stock_df = pd.read_csv('stock.csv')
stock_df['date'] = pd.to_datetime(stock_df['基準日'])
stock_df.index = stock_df['date']
stock_df['stock'] = stock_df['基準価額（円）'].str.replace(',','') .astype(int)


commodity_df = pd.read_csv('commodity.csv', encoding="shift-jis")
commodity_df['基準日'] = commodity_df['基準日'].astype(str)
commodity_df['date'] = pd.to_datetime(commodity_df['基準日'])
commodity_df.index = commodity_df['date']

ratio_df = pd.DataFrame()
ratio_df['stock'] = stock_df['stock']
ratio_df['commodity'] = commodity_df['基準価額']
ratio_df.dropna(inplace=True)
ratio_df['ratio'] = stock_df['stock'] / ratio_df['commodity']

date = ratio_df.index
ratio = ratio_df['ratio']

plt.figure(figsize=(20, 10))
plt.plot(date, ratio, label = 'Stock to Commodity', color='g')
plt.legend(loc=2, fontsize=18)
plt.xlabel('year', fontsize=18)
plt.ylabel('Ratio', fontsize=18)
plt.savefig("stockcommodity_ratio.png")

#単純移動平均の計算
ratio_df['SMA1'] = ratio_df['ratio'].rolling(window=50).mean()
ratio_df['SMA2'] = ratio_df['ratio'].rolling(window=200).mean()

#グラフ用のデータ
ratio_date = ratio_df.index[-10000:]
ratio_close = ratio_df['ratio'][-10000:]
ratio_sma1 = ratio_df['SMA1'][-10000:]
ratio_sma2 = ratio_df['SMA2'][-10000:]

#グラフの表示と保存
plt.figure(figsize=(20, 10))
plt.plot(ratio_date, ratio_close, lw=2, label = 'Stock to Commodity', color='g')
plt.plot(ratio_date, ratio_sma1, lw=2, label = 'SMA50', color='b')
plt.plot(ratio_date, ratio_sma2, lw=2, label = 'SMA200', color='r')
plt.legend(loc=0, fontsize=18)
plt.xlabel('year', fontsize=18)
plt.ylabel('Ratio', fontsize=18)
plt.tick_params(labelsize=18)
plt.savefig("stockcommodity_SMA_ratio.png")