【株価分析】日経平均の曜日別の価格変化率を調べてみた

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<ソースコード>

# 日経平均の曜日別変化率を調べる

import pandas_datareader.data as web
import pandas as pd
import datetime

for i in range(1990, 2021, 1):
    
    # 日経平均株価を取得する
    nikkei = web.DataReader("NIKKEI225", "fred", "1950/5/16")

    print(i)
    year = str(i)
    start = year + '-01-01'
    end = year + '-12-31'
    nikkei['date'] = nikkei.index
    nikkei = nikkei[nikkei['date'] > start]
    nikkei = nikkei[end > nikkei['date']]
    nikkei['dotw'] = nikkei['date'].dt.dayofweek
    nikkei = nikkei.dropna(how='any')
    nikkei['change'] = nikkei['NIKKEI225'].pct_change()
    nikkei['change2'] = nikkei['change'].shift(-1)

    print(nikkei[nikkei['dotw'] == 0]['change2'].mean())
    print(nikkei[nikkei['dotw'] == 1]['change2'].mean())
    print(nikkei[nikkei['dotw'] == 2]['change2'].mean())
    print(nikkei[nikkei['dotw'] == 3]['change2'].mean())
    print(nikkei[nikkei['dotw'] == 4]['change2'].mean())

 

 

1990 0.019545298 -0.34040474 -0.150879601 -0.234566626 -0.150626938
1991 -0.05108079 0.057110046 0.10532893 0.188612597 -0.346324431
1992 -0.312555701 -0.104199725 0.681170016 -0.232691922 -0.604166991
1993 -0.016545164 -0.069862757 0.510365856 0.004013032 -0.317294992
1994 0.148648999 0.034074285 0.134967546 -0.017807491 -0.013071476
1995 0.166654056 0.047240286 0.078334141 -0.075359195 -0.154421392
1996 0.236075702 0.028371386 -0.099575032 -0.04730186 -0.186079671
1997 0.367730813 0.11096995 -0.229975636 -0.504972807 -0.124341782
1998 0.251871983 0.273671057 -0.32604785 -0.303317587 0.011278197
1999 0.101192418 -0.032115378 0.205102864 0.122924067 0.344996843
2000 -0.161242494 -0.090097419 -0.584858314 -0.083105091 0.356733857
2001 0.398834472 -0.305781733 0.11043261 0.070008373 -0.704218869
2002 -0.482387173 -0.190718358 0.317927774 -0.095061033 -0.038087324
2003 0.020047085 0.076581177 -0.099319217 0.147420959 0.318551367
2004 0.030071294 0.102719222 -0.163120496 0.218233 -0.029683064
2005 0.10536214 0.075529146 0.030386862 0.226637127 0.275074889
2006 -0.034277973 -0.161193563 0.389476273 0.164509483 -0.231475876
2007 0.057378399 -0.296477969 0.284927706 -0.253813097 0.00365941
2008 -0.549316967 0.108922053 -0.282162691 -0.597986177 0.434327555
2009 0.033700243 0.221653065 0.066704992 0.22364731 -0.155780905
2010 -0.318953371 0.070774521 0.303752686 -0.227541247 0.091762072
2011 -0.365084139 0.241271629 -0.014843797 -0.01557826 -0.254504841
2012 0.088648112 0.182814655 0.24059582 -0.034030273 -0.065031746
2013 0.227755483 0.096956234 -0.093257902 0.487819241 0.219369549
2014 0.0952604 0.280388705 -0.08514023 0.079346508 -0.113258512
2015 -0.157780412 0.257307903 0.311089359 0.065575619 -0.233793665
2016 -0.031438859 -0.108575541 -0.070137105 -0.131891039 0.485329602
2017 0.034416954 0.087210738 0.041318128 0.099929721 0.052691226
2018 -0.009052744 -0.004050614 -0.087475067 -0.018348836 -0.171580488
2019 0.207064309 -0.037638384 -0.08908817 0.162379124 0.191178103
2020 0.692284799 0.094028064 -0.398285743 -0.167217238 -0.076929702

 

 

 

 

 

火曜日が全体的に期待値高そうな感じですね

 

 

関連記事:ビットコインの曜日別の価格変化率を調べてみた

 

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