CAPM模型在中国资本市场的有效性检验

证券投资分析作业
CAPM模型在中国资本市场的有效性检验
1、数据选取
此次实验主要考察CAPM模型在中国电力行业是否适用，因此随机抽取了电力行业的十只股票（时间段为2010年1月1日—2010年12月31日），分别为
选取沪深300指数为综合指数，选取2010年的国债的利率作为无风险资产的收益率（0.025）。

2、β系数的确定
CAPM模型中，β系数可以表述为：Ri–Rf=αi+βi(Rm-Rf)+εi，其中Ri为每一种证券的收益率，Rf为无风险收益率，Rm为市场收益率。

使用Eviews软件对每只股票每日风险溢价与市场组合风险溢价进行回归，得到每只股票的β值。

如下：
（1）黔源电力
DependentVariable:Y
Method:LeastSquares
Date:12/26/11Time:16:35
Sample:1241
Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.00868
50.002294-3.7860060.0002
X 0.61661
30.0763248.0788830.0000
R-squared 0.21450
9Meandependentvar
-
0.02441
3
AdjustedR-squared 0.21122
3S.D.dependentvar
0.02121
S.E.ofregression 0.01883
8Akaikeinfocriterion
-
5.09765
2
Sumsquaredresid 0.08481
1Schwarzcriterion
-
5.06873
2
Loglikelihood 616.267
0F-statistic
65.2683
5
Durbin-Watsonstat 1.91488
5Prob(F-statistic)
0.00000
（2）明星电力DependentVariable:Y2 Method:LeastSquares Date:12/26/11Time:16:46 Sample:1241 Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.03252
60.007661-4.2455950.0000
X
-
0.21597
50.254892-0.8473200.3977
R-squared 0.00299
5Meandependentvar
-
0.02701
7
AdjustedR-squared
-
0.00117
7S.D.dependentvar
0.06287
3
S.E.ofregression 0.06291
0Akaikeinfocriterion
-
2.68594
7
Sumsquaredresid 0.94589
4Schwarzcriterion
-
2.65702
7
Loglikelihood 325.656
6F-statistic
0.71795
1
Durbin-Watsonstat 1.19660
3Prob(F-statistic)
0.39766
5
（3）三峡水利DependentVariable:Y3 Method:LeastSquares Date:12/26/11Time:16:48 Sample:1241 Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.02939
80.004289-6.8536140.0000
X
-
0.16010
40.142712-1.1218690.2630
R-squared 0.00523
8Meandependentvar
-
0.02531
4
AdjustedR-squared 0.00107
6S.D.dependentvar
0.03524
2
S.E.ofregression 0.03522
3Akaikeinfocriterion
-
3.84597
1
Sumsquaredresid 0.29651
8Schwarzcriterion
-
3.81705
1
Loglikelihood 465.439
5F-statistic
1.25859
1
Durbin-Watsonstat 1.52315
2Prob(F-statistic)
0.26304
4
（4）九龙电力DependentVariable:Y4 Method:LeastSquares Date:12/26/11Time:16:50 Sample:1241 Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.02370
80.004362-5.4346750.0000
X
-
0.00358
40.145136-0.0246930.9803
R-squared 0.00000
3Meandependentvar
-
0.02361
6
AdjustedR-squared
-
0.00418
2S.D.dependentvar
0.03574
7
S.E.ofregression 0.03582
1Akaikeinfocriterion
-
3.81228
3
Sumsquaredresid 0.30667
7Schwarzcriterion
-
3.78336
3
Loglikelihood 461.380
1F-statistic
0.00061
Durbin-Watsonstat 1.59847
4Prob(F-statistic)
0.98032
1
（5）桂东电力
DependentVariable:Y5 Method:LeastSquares Date:12/26/11Time:16:52 Sample:1241 Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.02740
10.003728-7.3510100.0000
X
-
0.17453
90.124019-1.4073600.1606
R-squared 0.00821
9Meandependentvar
-
0.02294
9
AdjustedR-squared 0.00406
9S.D.dependentvar
0.03067
2
S.E.ofregression 0.03060
9Akaikeinfocriterion
-
4.12675
8
Sumsquaredresid 0.22392
7Schwarzcriterion
-
4.09783
8
Loglikelihood 499.274
3F-statistic
1.98066
2
Durbin-Watsonstat 1.56708
3Prob(F-statistic)
0.16062
（6）涪陵电力DependentVariable:Y6 Method:LeastSquares Date:12/26/11Time:16:53 Sample:1241
Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.02756
90.009995-2.7582870.0063
X 0.02867
30.3325370.0862260.9314
R-squared 0.00003
1Meandependentvar
-
0.02830
AdjustedR-squared
-
0.00415
3S.D.dependentvar
0.08190
4
S.E.ofregression 0.08207
4Akaikeinfocriterion
-
2.15412
7
Sumsquaredresid 1.60993
7Schwarzcriterion
-
2.12520
8
Loglikelihood 261.572
3F-statistic
0.00743
5
Durbin-Watsonstat 1.10962
0Prob(F-statistic)
0.93135
9
（7）西昌电力DependentVariable:Y7 Method:LeastSquares Date:12/26/11Time:16:55 Sample:1241 Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C 0.02643
40.004241-6.2330430.0000
X 0.01624
10.1410980.1151070.9085
R-squared 0.00005
5Meandependentvar
-
0.02684
8
AdjustedR-squared
-
0.00412
8S.D.dependentvar
0.03475
3
S.E.ofregression 0.03482
5Akaikeinfocriterion
-
3.86871
7
Sumsquaredresid 0.28984
9Schwarzcriterion
-
3.83979
8
Loglikelihood 468.180
4F-statistic
0.01325
Durbin-Watsonstat 1.45245
7Prob(F-statistic)
0.90845
7
（8）乐山电力DependentVariable:Y8 Method:LeastSquares Date:12/26/11Time:16:56 Sample:1241 Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.02817
40.003964-7.1072560.0000
X
-
0.171910.131888-1.3035030.1937
R-squared 0.00705
9Meandependentvar
-
0.02378
9
AdjustedR-squared 0.00290
5S.D.dependentvar
0.03259
9
S.E.ofregression 0.03255
2Akaikeinfocriterion
-
4.00372
1
Sumsquaredresid 0.25324
5Schwarzcriterion
-
3.97480
2
Loglikelihood 484.448
4F-statistic
1.69911
9
Durbin-Watsonstat 1.73361
9Prob(F-statistic)
0.19365
7
（9）川投能源DependentVariable:Y9 Method:LeastSquares Date:12/26/11Time:16:58 Sample:1241 Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.02857
90.003039-9.4027250.0000
X
-
0.14415
60.101126-1.4255140.1553
R-squared 0.00843
1Meandependentvar
-
0.02490
2
AdjustedR-squared 0.00428
2S.D.dependentvar
0.02501
3
S.E.ofregression 0.02495
9Akaikeinfocriterion
-
4.53490
3
Sumsquaredresid 0.14888
5Schwarzcriterion
-
4.50598
4
Loglikelihood 548.455
8F-statistic
2.03209
Durbin-Watsonstat 1.71035
2Prob(F-statistic)
0.15531
3
（10）郴电国际DependentVariable:Y10 Method:LeastSquares Date:12/26/11Time:16:59 Sample:1241 Includedobservations:241
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C
-
0.02296
90.003915-5.8662170.0000
X 0.07240
80.1302680.5558350.5788
R-squared 0.00129
1Meandependentvar
-
0.02481
6
AdjustedR-squared
-
0.00288
8S.D.dependentvar
0.03210
5
S.E.ofregression 0.03215
2Akaikeinfocriterion
-
4.02844
Sumsquaredresid0.24706Schwarzcriterion-
2 3.99952
Loglikelihood 487.427
0F-statistic
0.30895
2
Durbin-Watsonstat 1.75651
0Prob(F-statistic)
0.57884
4
3、用求出的10只股票的β值与十只股票的平均收益率进行回归，如下：DependentVariable:YY
Method:LeastSquares
Date:12/26/11Time:17:27
Sample:110
Includedobservations:10
Variable Coeffic
ient Std.Error
t-
Statistic Prob.
C -5.47E-
050.000603-0.0906850.9300
XX 1.30E-
050.0025980.0050220.9961
R-squared 0.00000
3Meandependentvar
-5.49E-
05
AdjustedR-squared
-
0.12499
6S.D.dependentvar
0.00179
6
S.E.ofregression 0.00190
5Akaikeinfocriterion
-
9.51188
5
Sumsquaredresid 2.90E-
05Schwarzcriterion
-
9.45136
8
Loglikelihood 49.5594
2F-statistic
2.52E-
05
Durbin-Watsonstat 2.04284
0Prob(F-statistic)
0.99611
6
即样本回归方程为
Yt=-5.47E-05+1.30E-05+εi
4、统计检验
r2=0.000003，说明仅有总离差平方和的0.003%被样本回归直线解释，回归直线对样本点的拟合优度非常低。

给出显着性水平α=0.05，P>α，t检验不能通过；F检验也不能通过。

从以上的检验可以看出，此模型没有通过各种检验，拟合不好，不能代表x 与y的关系。

5、结论
通过分析可以看出，CAPM模型对我国资本市场上的电力行业不适用，通过更多的分析可以得出，CAPM模型对我国资本市场是无效的。

我国资本市场是政策导向型市场，采用核准制度，是计划经济的产物，资本市场还没有实现市场完全控制，资本未达到自由流动，还存在信息不对称、经济发展程度落后于发达国家、国际金融环境恶化等现象，加之CAPM模型的假设条件比较苛刻，因此在中国资本市场上应用这一模型极为困难。