やりたいこと

片対数グラフを作りたい

参考サイト

[Pythonによる科学・技術計算] 対数グラフ，可視化，matplotlib - Qiita

コード

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from dateutil.relativedelta import relativedelta

def get_asset_return(file_path : 'str') -> pd.DataFrame:

    df_price = pd.read_csv(file_path, header=0)

    df_price['date'] = pd.to_datetime(df_price['date'], format='%Y-%m-%d')
    df_price['date'] = df_price['date'].dt.date
    df_price = df_price.set_index('date')

    eight_asset = ['TP1', 'ES1', 'CF1', 'JB1', 'TY1', 'RX1', 'GC1', 'CL1']
    df_price = df_price[eight_asset]

    df_return = df_price.pct_change().dropna()

    return df_return

def getSFE(tested_cov : np.array, actual_cov : np.array) -> 'scalar':

    tested_cov_tril = np.tril(tested_cov)
    actual_cov_tril = np.tril(actual_cov)

    diff = actual_cov_tril - tested_cov_tril
    SFE = np.sum(np.square(diff))

    return SFE

#  メイン処理
if __name__ == '__main__':

    #  パラメータ等設定
    file_path = 'input/mktdata.csv'
    renew_freq = 1  # 最適比率更新頻度
    calc_period = 36  # bootstrap抽出元データ期間

    #  収益率データ作成
    df_return = get_asset_return(file_path)


    first_index = df_return.index[0]
    last_index = df_return.index[-1]
    target_index = first_index + relativedelta(months=60)  # 適宜修正
    SFE_Series = pd.Series()

    while target_index <= last_index:

        #  データフレーム作成
        pre_data_frame = df_return[target_index - relativedelta(months=calc_period): target_index]
        data_frame = df_return[target_index: target_index + relativedelta(months=renew_freq) - relativedelta(days=1)]

        #  分散共分散行列作成
        tested_cov = pre_data_frame.cov().values
        actual_cov = data_frame.cov().values

        #  SFE取得
        SFE = getSFE(tested_cov, actual_cov)
        SFE_Series[target_index] = SFE

        #  target_index更新
        target_index += relativedelta(months=renew_freq)


    #  グラフ作成
    fig = plt.figure(figsize = (12, 8))
    ax = fig.add_subplot(1, 1, 1)

    ax.plot(SFE_Series)
    ax.set_yscale('log')
    ax.grid(which = 'both', color = 'black', lw = 0.2)

    fig.savefig('output/SFE' + str(calc_period) + '.png')