capm模型檢驗(yàn)(電子表格-版-含推導(dǎo)-分析-數(shù)據(jù)-結(jié)論)

"CAPM模型其實(shí)質(zhì)是討論風(fēng)險(xiǎn)與收益的關(guān)系,其基本的驗(yàn)證思路是考察是否只有股票的系統(tǒng)風(fēng)險(xiǎn)(用β系數(shù)代表)與其收益有關(guān),而且這兩者為線性正相關(guān)。它是對(duì)股票收益率的事前預(yù)測(cè)，把其變成類似計(jì)量經(jīng)濟(jì)學(xué)回歸的表達(dá)式也就是CAPM模型的事后形式，本次通過EVIEWS進(jìn)行回歸分析驗(yàn)證CAPM模型在此股票上是否有效。見下式：

E(Rj)-Rf=(E(Rm)-Rf)βj(1)//這是CAPM的原本模型

Rj-Rf=C+(Rm-Rf)βj+μ(2)//對(duì)CAPM模型的變換式子，在本分析中，Rj-Rf用因變量Y表示，Rm-Rf用自變量X表示，C代表截距項(xiàng),μ代表殘差項(xiàng)。

則模型最終變?yōu)椋篩=C+Xβj+μ

若（2）要接受CAPM,則應(yīng)在回歸方程顯著的條件下同時(shí)接受如下的兩個(gè)假設(shè):

(1)接受H0:C=0的假設(shè);

(2)拒絕H1:βj=0的假設(shè).

變量說明：

Rf為無風(fēng)險(xiǎn)收益率，用t時(shí)期3個(gè)月的銀行定期存款利率表示；

Rm為市場(chǎng)組合的期望收益率，用t時(shí)刻的上證指數(shù)日回報(bào)率表示；

Rj為個(gè)股回報(bào)率，計(jì)算公式如下：Rjt=(Pjt-Pjt–1)/Pjit-1；

βj是股票j的收益率對(duì)市場(chǎng)組合收益率的回歸方程的斜率，常被稱為“β系數(shù)”。

本文的數(shù)據(jù)取自上證A股2013年4月1日到2013年5月22日的十支股票。

",,,,,,

股票名稱：,股票代碼：,Variable,Coefficient,Std.Error,t-Statistic,Prob.

1.三一重工,600031,X,-2.447954,3.243226,-0.75479,0.4553

,,C,-0.194291,0.15955,-1.217745,0.2312

,,,,,,,

,,R-squared,0.015579,Meandependentvar,,-0.075549

,,AdjustedR-squared,-0.011766,S.D.dependentvar,,0.162949

,,S.E.ofregression,0.163904,Akaikeinfocriterion,,-0.727871

,,Sumsquaredresid,0.967127,Schwarzcriterion,,-0.641682

,,Loglikelihood,15.82955,F-statistic,,0.569708

,,Durbin-Watsonstat,1.012855,Prob(F-statistic),,0.455285

,,,,,,,

,,,,,,,

,,Variable,Coefficient,Std.Error,t-Statistic,Prob.

2.航天機(jī)電,600152,X,-2.268172,3.287982,-0.689837,0.4947

,,C,-0.176194,0.161752,-1.089285,0.2833

,,,,,,,

,,R-squared,0.013046,Meandependentvar,,-0.066172

,,AdjustedR-squared,-0.014369,S.D.dependentvar,,0.164985

,,S.E.ofregression,0.166166,Akaikeinfocriterion,,-0.70046

,,Sumsquaredresid,0.994004,Schwarzcriterion,,-0.614271

,,Loglikelihood,15.30874,F-statistic,,0.475875

,,Durbin-Watsonstat,1.060726,Prob(F-statistic),,0.49472

,,,,,,,

,,,,,,,

3.四川路橋,600039,Variable,Coefficient,Std.Error,t-Statistic,Prob.

,,X,-2.139265,3.276311,-0.652949,0.5179

,,C,-0.177371,0.161178,-1.100471,0.2784

,,,,,,,

,,R-squared,0.011704,Meandependentvar,,-0.073602

,,AdjustedR-squared,-0.015748,S.D.dependentvar,,0.164288

,,S.E.ofregression,0.165576,Akaikeinfocriterion,,-0.707572

,,Sumsquaredresid,0.98696,Schwarzcriterion,,-0.621383

,,Loglikelihood,15.44387,F-statistic,,0.426343

,,Durbin-Watsonstat,1.044981,Prob(F-statistic),,0.517937

,,,,,,,

4.鳳凰光學(xué),600071,Variable,Coefficient,Std.Error,t-Statistic,Prob.

,,X,-2.135465,3.263153,-0.654417,0.517

,,C,-0.179289,0.16053,-1.116856,0.2715

,,,,,,,

,,R-squared,0.011756,Meandependentvar,,-0.075704

,,AdjustedR-squared,-0.015695,S.D.dependentvar,,0.163632

,,S.E.ofregression,0.164911,Akaikeinfocriterion,,-0.71562

,,Sumsquaredresid,0.979048,Schwarzcriterion,,-0.629431

,,Loglikelihood,15.59678,F-statistic,,0.428262

,,Durbin-Watsonstat,1.050367,Prob(F-statistic),,0.517002

,,,,,,,

5.中金黃金,600489,Variable,Coefficient,Std.Error,t-Statistic,Prob.

,,X,-2.892332,3.228677,-0.895826,0.3763

,,C,-0.217314,0.158834,-1.368183,0.1797

,,,,,,,

,,R-squared,0.021806,Meandependentvar,,-0.077016

,,AdjustedR-squared,-0.005366,S.D.dependentvar,,0.162733

,,S.E.ofregression,0.163169,Akaikeinfocriterion,,-0.736863

,,Sumsquaredresid,0.95847,Schwarzcriterion,,-0.650674

,,Loglikelihood,16.0004,F-statistic,,0.802504

,,Durbin-Watsonstat,1.029506,Prob(F-statistic),,0.376297

,,,,,,,

,,,,,,,

6.方興科技,600552,Variable,Coefficient,Std.Error,t-Statistic,Prob.

,,X,-2.436679,3.288756,-0.740912,0.4636

,,C,-0.19188,0.16179,-1.185982,0.2434

,,,,,,,

,,R-squared,0.01502,Meandependentvar,,-0.073684

,,AdjustedR-squared,-0.012341,S.D.dependentvar,,0.165189

,,S.E.ofregression,0.166205,Akaikeinfocriterion,,-0.699989

,,Sumsquaredresid,0.994472,Schwarzcriterion,,-0.613801

,,Loglikelihood,15.2998,F-statistic,,0.548951

,,Durbin-Watsonstat,1.115256,Prob(F-statistic),,0.463552

,,,,,,,

,,,,,,,

7.江蘇舜天,600827,Variable,Coefficient,Std.Error,t-Statistic,Prob.

,,X,-2.552558,3.254945,-0.784209,0.438

,,C,-0.194703,0.160127,-1.215933,0.2319

,,,,,,,

,,R-squared,0.016796,Meandependentvar,,-0.070886

,,AdjustedR-squared,-0.010515,S.D.dependentvar,,0.163639

,,S.E.ofregression,0.164497,Akaikeinfocriterion,,-0.720657

,,Sumsquaredresid,0.974129,Schwarzcriterion,,-0.634469

,,Loglikelihood,15.69249,F-statistic,,0.614984

,,Durbin-Watsonstat,1.018081,Prob(F-statistic),,0.438047

,,,,,,,

,,,,,,,

8.凱樂科技,600260,Variable,Coefficient,Std.Error,t-Statistic,Prob.

,,X,-3.110213,3.242644,-0.95916,0.3439

,,C,-0.223097,0.159521,-1.398538,0.1705

,,,,,,,

,,R-squared,0.024918,Meandependentvar,,-0.07223

,,AdjustedR-squared,-0.002167,S.D.dependentvar,,0.163698

,,S.E.ofregression,0.163875,Akaikeinfocriterion,,-0.72823

,,Sumsquaredresid,0.966781,Schwarzcriterion,,-0.642041

,,Loglikelihood,15.83636,F-statistic,,0.919987

,,Durbin-Watsonstat,1.045083,Prob(F-statistic),,0.343876

,,,,,,,

,,,,,,,

9.古越龍山,600059,Variable,Coefficient,Std.Error,t-Statistic,Prob.

,,X,-2.535157,3.252968,-0.779336,0.4409

,,C,-0.196876,0.160029,-1.230249,0.2266

,,,,,,,

,,R-squared,0.016591,Meandependentvar,,-0.073903

,,AdjustedR-squared,-0.010726,S.D.dependentvar,,0.163522

,,S.E.ofregression,0.164397,Akaikeinfocriterion,,-0.721873

,,Sumsquaredresid,0.972946,Schwarzcriterion,,-0.635684

,,Loglikelihood,15.71558,F-statistic,,0.607365

,,Durbin-Watsonstat,1.012261,Prob(F-statistic),,0.440875

,,,,,,,

,,,,,,,

10.鄂爾多斯,600295,Variable,Coefficient,Std.Error,t-Statistic,Prob.

,,X,-2.574677,3.241956,-0.794174,0.4323

,,C,-0.197685,0.159488,-1.239498,0.2232

,,,,,,,

,,R-squared,0.017218,Meandependentvar,,-0.072795

,,AdjustedR-square