Pythonで投資のチャート分析をしよう【ゴールドvsマネーサプライ】

#ライブラリーのインポート

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

yf.pdr_override()

 

#データの期間

start = '2000-01-01'

end = datetime.date.today()

 

#Yahoo!Financeからデータ取得

def yahoo(symbol,start,end):

    df = data.get_data_yahoo(symbol, start, end)

    date = df.index

    price = df['Close']

    return date, price

 

#FREDからデータ取得

def fred(symbol,start,end):

    df = data.FredReader(symbol, start, end)

    date = df.read().index

    value = df.read()[symbol]

    return date, value

 

#ゴールド

gold_date, gold_price = yahoo('GC=F', start, end)

 

#マネーサプライM2、Billions USD単位

m2_date, m2_value = fred('WM2NS', start, end)

 

#マージデータの作成

merge_df = pd.DataFrame()

merge_df['gold'] = gold_price

merge_df['m2'] = m2_value

merge_df.dropna(inplace=True)

 

#金価格をM2で割った指標を作成

merge_df['ratio'] = merge_df['gold'] / merge_df['m2']

merge_df.dropna(inplace=True)

 

#移動平均を計算

merge_df['SMA1'] = merge_df['ratio'].rolling(window=50).mean()

merge_df['SMA2'] = merge_df['ratio'].rolling(window=200).mean()

 

#グラフに使用するデータ

date = merge_df.index

ratio = merge_df['ratio']

ratio_sma1 = merge_df['SMA1']

ratio_sma2 = merge_df['SMA2']

 

#グラフの作成

plt.figure(figsize=(20, 10))

plt.plot(date, ratio, lw=2,label = 'Gold to M2', color='g')

plt.plot(date, ratio_sma1, lw=2, label = 'SMA50', color='b')

plt.plot(date, ratio_sma2, lw=2, label = 'SMA200', color='r')

plt.legend(loc=2, fontsize=18)

plt.xlabel('year', fontsize=18)

plt.ylabel('Gold price(USD)/M2(Billions USD)', fontsize=18)

plt.tick_params(labelsize=18)

plt.savefig("goldm2_ratio20230305.png")