Contents

  • Souece:日本取引所グループ、日本経済新聞社

業種別空売り集計

  • 2019年07月18日
  • 「空売り合計:比率」は100から「実注文:比率」を減じた数値としています。

空売り比率の時系列推移

  • 2019-01-18 ~ 2019-07-18

時系列推移

  • 2019-01-18 ~ 2019-07-18
Date 日経平均株価:終値 空売り合計:比率
2019-01-18 20,666.07 42.4
2019-01-21 20,719.33 43.9
2019-01-22 20,622.91 47.3
2019-01-23 20,593.72 47.3
2019-01-24 20,574.63 43.3
2019-01-25 20,773.56 41.2
2019-01-28 20,649 46.7
2019-01-29 20,664.64 47.4
2019-01-30 20,556.54 47
2019-01-31 20,773.49 42.8
2019-02-01 20,788.39 45.3
2019-02-04 20,883.77 42.7
2019-02-05 20,844.45 43.3
2019-02-06 20,874.06 45.1
2019-02-07 20,751.28 45.7
2019-02-08 20,333.17 48.7
2019-02-12 20,864.21 43
2019-02-13 21,144.48 41.4
2019-02-14 21,139.71 42.5
2019-02-15 20,900.63 44.8
2019-02-18 21,281.85 41.5
2019-02-19 21,302.65 43
2019-02-20 21,431.49 41
2019-02-21 21,464.23 42.7
2019-02-22 21,425.51 42.5
2019-02-25 21,528.23 42.9
2019-02-26 21,449.39 41.5
2019-02-27 21,556.51 42.8
2019-02-28 21,385.16 41.1
2019-03-01 21,602.69 40.6
2019-03-04 21,822.04 39.9
2019-03-05 21,726.28 41.4
2019-03-06 21,596.81 44.1
2019-03-07 21,456.01 47
2019-03-08 21,025.56 50.3
2019-03-11 21,125.09 45.7
2019-03-12 21,503.69 40.3
2019-03-13 21,290.24 45
2019-03-14 21,287.02 43.9
2019-03-15 21,450.85 42.3
2019-03-18 21,584.5 41.4
2019-03-19 21,566.85 41.9
2019-03-20 21,608.92 41.6
2019-03-22 21,627.34 41.1
2019-03-25 20,977.11 44.9
2019-03-26 21,428.39 42.8
2019-03-27 21,378.73 41.3
2019-03-28 21,033.76 46.5
2019-03-29 21,205.81 42.8
2019-04-01 21,509.03 41.4
2019-04-02 21,505.31 43.8
2019-04-03 21,713.21 43.7
2019-04-04 21,724.95 43.1
2019-04-05 21,807.5 41.9
2019-04-08 21,761.65 42.9
2019-04-09 21,802.59 42.3
2019-04-10 21,687.57 44
2019-04-11 21,711.38 43.4
2019-04-12 21,870.56 45.7
2019-04-15 22,169.11 41.2
2019-04-16 22,221.66 41.1
2019-04-17 22,277.97 40.7
2019-04-18 22,090.12 44.6
2019-04-19 22,200.56 43.5
2019-04-22 22,217.9 44.8
2019-04-23 22,259.74 43.1
2019-04-24 22,200 45.7
2019-04-25 22,307.58 46.1
2019-04-26 22,258.73 45
2019-05-07 21,923.72 44.9
2019-05-08 21,602.59 46.1
2019-05-09 21,402.13 47.5
2019-05-10 21,344.92 49.2
2019-05-13 21,191.28 48.8
2019-05-14 21,067.23 45.6
2019-05-15 21,188.56 46
2019-05-16 21,062.98 48.8
2019-05-17 21,250.09 45.2
2019-05-20 21,301.73 46.8
2019-05-21 21,272.45 44.8
2019-05-22 21,283.37 46.2
2019-05-23 21,151.14 48
2019-05-24 21,117.22 46.9
2019-05-27 21,182.58 44.3
2019-05-28 21,260.14 45
2019-05-29 21,003.37 46.9
2019-05-30 20,942.53 47.8
2019-05-31 20,601.19 47.1
2019-06-03 20,410.88 48.5
2019-06-04 20,408.54 47.3
2019-06-05 20,776.1 43.6
2019-06-06 20,774.04 44
2019-06-07 20,884.71 43.5
2019-06-10 21,134.42 40.6
2019-06-11 21,204.28 41.7
2019-06-12 21,129.72 46.8
2019-06-13 21,032 48
2019-06-14 21,116.89 48
2019-06-17 21,124 45.7
2019-06-18 20,972.71 46.8
2019-06-19 21,333.87 43.3
2019-06-20 21,462.86 43.5
2019-06-21 21,258.64 47.3
2019-06-24 21,285.99 44.3
2019-06-25 21,193.81 47.1
2019-06-26 21,086.59 45.3
2019-06-27 21,338.17 44.9
2019-06-28 21,275.92 49.3
2019-07-01 21,729.97 41.9
2019-07-02 21,754.27 43.5
2019-07-03 21,638.16 45.3
2019-07-04 21,702.45 41.3
2019-07-05 21,746.38 43.3
2019-07-08 21,534.35 49.7
2019-07-09 21,565.15 46.7
2019-07-10 21,533.48 49.4
2019-07-11 21,643.53 41.3
2019-07-12 21,685.9 42.9
2019-07-16 21,535.25 44.1
2019-07-17 21,469.18 43.4
2019-07-18 21,046.24 51.2

単位根検定/共和分検定
  • CADFtest {CADFtest}
  • ca.po {urca}
### 単位根検定 ###

Analysis period: 2019-03-05 ~ 2019-07-18,90days

$NIKKEI225.close

    ADF test

data:  x
ADF(0) = -2.197, p-value = 0.485
alternative hypothesis: true delta is less than 0
sample estimates:
     delta 
-0.1099199 


$ShortSalerRatio

    ADF test

data:  x
ADF(0) = -6.365, p-value = 0.000002991
alternative hypothesis: true delta is less than 0
sample estimates:
     delta 
-0.6655731 


$NIKKEI225.close_change

    ADF test

data:  x
ADF(0) = -9.1923, p-value = 0.000000000058
alternative hypothesis: true delta is less than 0
sample estimates:
    delta 
-1.027683 


$ShortSalerRatio_change

    ADF test

data:  x
ADF(1) = -9.5666, p-value = 0.00000000001642
alternative hypothesis: true delta is less than 0
sample estimates:
    delta 
-1.700544 
### 共和分検定 ###

Analysis period: 2019-03-05 ~ 2019-07-18,90days


######################################## 
# Phillips and Ouliaris Unit Root Test # 
######################################## 

Test of type Pu 
detrending of series none 


Call:
lm(formula = z[, 1] ~ z[, -1] - 1)

Residuals:
    Min      1Q  Median      3Q     Max 
-3361.4 -1102.1   157.7  1220.9  2875.8 

Coefficients:
        Estimate Std. Error t value            Pr(>|t|)    
z[, -1]  476.711      3.422   139.3 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1457 on 89 degrees of freedom
Multiple R-squared:  0.9954,    Adjusted R-squared:  0.9954 
F-statistic: 1.941e+04 on 1 and 89 DF,  p-value: < 0.00000000000000022


Value of test-statistic is: 0.8052 

Critical values of Pu are:
                  10pct    5pct    1pct
critical values 20.3933 25.9711 38.3413

最小二乗法
  • lm {stats}
  • dwtest {lmtest}
  • ks.test {stats}
  • confint {stats}
  • Box.test {stats}
### 切片項≠0 ###

Analysis period: 2019-03-05 ~ 2019-07-18,90days


Call:
lm(formula = NIKKEI225.close_change ~ ShortSalerRatio_change, 
    data = datadf)

Residuals:
    Min      1Q  Median      3Q     Max 
-475.18  -93.94    3.27   97.20  359.10 

Coefficients:
                       Estimate Std. Error t value         Pr(>|t|)    
(Intercept)              -2.933     15.164  -0.193            0.847    
ShortSalerRatio_change  -45.293      5.452  -8.307 0.00000000000109 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 143.7 on 88 degrees of freedom
Multiple R-squared:  0.4395,    Adjusted R-squared:  0.4331 
F-statistic: 69.01 on 1 and 88 DF,  p-value: 0.000000000001091


-----------------------------------------------------------------------------

    Durbin-Watson test

data:  OLS_Model
DW = 1.9413, p-value = 0.4005
alternative hypothesis: true autocorrelation is greater than 0


-----------------------------------------------------------------------------

    One-sample Kolmogorov-Smirnov test

data:  ResidualsOLS
D = 0.073274, p-value = 0.6915
alternative hypothesis: two-sided


-----------------------------------------------------------------------------
                           2.5 %    97.5 %
(Intercept)            -33.06929  27.20286
ShortSalerRatio_change -56.12854 -34.45748

-----------------------------------------------------------------------------

    Box-Ljung test

data:  ResidualsOLS
X-squared = 0.072667, df = 1, p-value = 0.7875
### 切片項=0 ###

Analysis period: 2019-03-05 ~ 2019-07-18,90days


Call:
lm(formula = NIKKEI225.close_change ~ ShortSalerRatio_change - 
    1, data = datadf)

Residuals:
    Min      1Q  Median      3Q     Max 
-477.94  -96.94    0.51   94.10  356.06 

Coefficients:
                       Estimate Std. Error t value          Pr(>|t|)    
ShortSalerRatio_change  -45.341      5.417   -8.37 0.000000000000755 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 142.9 on 89 degrees of freedom
Multiple R-squared:  0.4404,    Adjusted R-squared:  0.4341 
F-statistic: 70.05 on 1 and 89 DF,  p-value: 0.0000000000007549


-----------------------------------------------------------------------------

    Durbin-Watson test

data:  OLS_Model_no_intercept
DW = 1.9409, p-value = 0.4414
alternative hypothesis: true autocorrelation is greater than 0


-----------------------------------------------------------------------------

    One-sample Kolmogorov-Smirnov test

data:  ResidualsOLS_no_intercept
D = 0.073072, p-value = 0.6947
alternative hypothesis: two-sided


-----------------------------------------------------------------------------
                           2.5 %    97.5 %
ShortSalerRatio_change -56.10472 -34.57651

-----------------------------------------------------------------------------

    Box-Ljung test

data:  ResidualsOLS_no_intercept
X-squared = 0.071745, df = 1, p-value = 0.7888

一般化最小二乗法
### 切片項≠0 ###

Analysis period: 2019-03-05 ~ 2019-07-18,90days

Generalized least squares fit by REML
  Model: NIKKEI225.close_change ~ ShortSalerRatio_change 
  Data: datadf 
       AIC      BIC    logLik
  1141.116 1148.548 -567.5578

Coefficients:
                           Value Std.Error   t-value p-value
(Intercept)             -2.93321 15.164408 -0.193427  0.8471
ShortSalerRatio_change -45.29301  5.452417 -8.306960  0.0000

 Correlation: 
                       (Intr)
ShortSalerRatio_change -0.045

Standardized residuals:
        Min          Q1         Med          Q3         Max 
-3.30641605 -0.65364767  0.02278757  0.67635958  2.49867135 

Residual standard error: 143.7155 
Degrees of freedom: 90 total; 88 residual

-----------------------------------------------------------------------------

    One-sample Kolmogorov-Smirnov test

data:  ResidualsGLS
D = 0.073274, p-value = 0.6915
alternative hypothesis: two-sided


-----------------------------------------------------------------------------
                           2.5 %    97.5 %
(Intercept)            -32.65490  26.78848
ShortSalerRatio_change -55.97955 -34.60647

-----------------------------------------------------------------------------

    Box-Ljung test

data:  ResidualsGLS
X-squared = 0.072667, df = 1, p-value = 0.7875
### 切片項=0 ###

Analysis period: 2019-03-05 ~ 2019-07-18,90days

Generalized least squares fit by REML
  Model: NIKKEI225.close_change ~ ShortSalerRatio_change - 1 
  Data: datadf 
       AIC      BIC    logLik
  1146.424 1151.401 -571.2118

Coefficients:
                           Value Std.Error   t-value p-value
ShortSalerRatio_change -45.34062  5.417323 -8.369562       0

Standardized residuals:
         Min           Q1          Med           Q3          Max 
-3.343698163 -0.678207164  0.003584274  0.658326884  2.491073620 

Residual standard error: 142.9362 
Degrees of freedom: 90 total; 89 residual

-----------------------------------------------------------------------------

    One-sample Kolmogorov-Smirnov test

data:  ResidualsGLS_no_intercept
D = 0.073072, p-value = 0.6947
alternative hypothesis: two-sided


-----------------------------------------------------------------------------
                           2.5 %    97.5 %
ShortSalerRatio_change -55.95838 -34.72286

-----------------------------------------------------------------------------

    Box-Ljung test

data:  ResidualsGLS_no_intercept
X-squared = 0.071745, df = 1, p-value = 0.7888