CAPM模型在资本市场的有效性检验

C A P M模型在资本市场的

有效性检验

This model paper was revised by the Standardization Office on December 10, 2020

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 Coefficie

nt Std.Error t-Statistic Prob.

C-0.0086850.002294-3.7860060.0002

X0.6166130.0763248.0788830.0000

R-squared0.214509Meandependentvar-0.024413 AdjustedR-squared0.211223S.D.dependentvar0.021210 S.E.ofregression0.018838Akaikeinfocriterion-5.097652 Sumsquaredresid0.084811Schwarzcriterion-5.068732 Loglikelihood616.2670F-statistic65.26835 Durbin-Watsonstat 1.914885Prob(F-statistic)0.000000

（2）明星电力DependentVariable:Y2 Method:LeastSquares Date:12/26/11Time:16:46 Sample:1241 Includedobservations:241

Variable Coefficie

nt Std.Error t-Statistic Prob.

C-0.0325260.007661-4.2455950.0000

X-0.2159750.254892-0.8473200.3977

R-squared0.002995Meandependentvar-0.027017 AdjustedR-squared-0.001177S.D.dependentvar0.062873 S.E.ofregression0.062910Akaikeinfocriterion-2.685947 Sumsquaredresid0.945894Schwarzcriterion-2.657027 Loglikelihood325.6566F-statistic0.717951 Durbin-Watsonstat 1.196603Prob(F-statistic)0.397665

（3）三峡水利

DependentVariable:Y3

Method:LeastSquares

Date:12/26/11Time:16:48

Sample:1241

Includedobservations:241

Variable Coefficie

nt Std.Error t-Statistic Prob.

C-0.0293980.004289-6.8536140.0000

X-0.1601040.142712-1.1218690.2630

R-squared0.005238Meandependentvar-0.025314 AdjustedR-squared0.001076S.D.dependentvar0.035242 S.E.ofregression0.035223Akaikeinfocriterion-3.845971 Sumsquaredresid0.296518Schwarzcriterion-3.817051 Loglikelihood465.4395F-statistic 1.258591 Durbin-Watsonstat 1.523152Prob(F-statistic)0.263044

（4）九龙电力

DependentVariable:Y4

Method:LeastSquares

Date:12/26/11Time:16:50

Sample:1241

Includedobservations:241

Variable Coefficie

nt Std.Error t-Statistic Prob.

C-0.0237080.004362-5.4346750.0000 X-0.0035840.145136-0.0246930.9803

R-squared0.000003Meandependentvar-0.023616 AdjustedR-squared-0.004182S.D.dependentvar0.035747 S.E.ofregression0.035821Akaikeinfocriterion-3.812283 Sumsquaredresid0.306677Schwarzcriterion-3.783363 Loglikelihood461.3801F-statistic0.000610 Durbin-Watsonstat 1.598474Prob(F-statistic)0.980321

（5）桂东电力

DependentVariable:Y5

Method:LeastSquares

Date:12/26/11Time:16:52

Sample:1241

Includedobservations:241

Variable Coefficie

nt Std.Error t-Statistic Prob.

C-0.0274010.003728-7.3510100.0000

X-0.1745390.124019-1.4073600.1606

R-squared0.008219Meandependentvar-0.022949 AdjustedR-squared0.004069S.D.dependentvar0.030672 S.E.ofregression0.030609Akaikeinfocriterion-4.126758 Sumsquaredresid0.223927Schwarzcriterion-4.097838 Loglikelihood499.2743F-statistic 1.980662 Durbin-Watsonstat 1.567083Prob(F-statistic)0.160620

（6）涪陵电力

DependentVariable:Y6

Method:LeastSquares

Date:12/26/11Time:16:53

Sample:1241

Includedobservations:241

Variable Coefficie

nt Std.Error t-Statistic Prob.

C-0.0275690.009995-2.7582870.0063

X0.0286730.3325370.0862260.9314

R-squared0.000031Meandependentvar-0.028300 AdjustedR-squared-0.004153S.D.dependentvar0.081904 S.E.ofregression0.082074Akaikeinfocriterion-2.154127 Sumsquaredresid 1.609937Schwarzcriterion-2.125208 Loglikelihood261.5723F-statistic0.007435 Durbin-Watsonstat 1.109620Prob(F-statistic)0.931359

（7）西昌电力

DependentVariable:Y7