1、 where stkcd=199512 and stkcd=199712;4,用1995年1月至1997年12月期间的超额月收益率对每一股票进行时间序列回归,来分别估计各股票在这一期间的贝塔值。 proc reg data=finance.rtndata outest=finance.betas97; model y1-y100=mr2/noint;求出的值为:Y10.70435y210.91586Y410.896054y610.851652y811.212801Y20.637881y220.905357Y420.518481y621.004974y820.729579Y30.949051y2
2、30.932471Y431.204833y630.866777y831.894588Y41.878588y240.977102Y440.722664y640.562924y841.480132Y51.317656y250.634488Y451.884002y650.661701y851.393397Y60.67436y260.595003Y460.741601y660.734313y860.695886Y70.732708y270.867965Y470.615389y670.856492y871.228562Y80.586665y280.35689Y481.171069y680.667569y
3、880.529807Y90.965397y290.769648Y490.846387y691.098579y890.52415Y100.718133y301.196381Y501.175787y701.456532y900.42185Y110.917436y310.781798Y510.839937y711.152561y910.724734Y120.884156y321.693313Y520.758086y721.03661y921.037979Y130.943795y330.90575Y531.802377y731.083311y931.40598Y140.994425y340.76529
4、2Y540.944545y740.610862y941.365702Y150.704337y351.191723Y551.096838y751.379289y950.833917Y160.821038y361.525602Y561.146742y760.843295y961.050583Y171.593844y371.529935Y570.632544y771.266977y971.278623Y181.058723y381.073508Y580.720895y781.060654y981.330587Y190.443705y391.286248Y590.87356y790.905822y99
5、1.418177Y200.643277y401.77932Y600.541877y800.798854y1001.745139采用类似的程序,算出1996年1月至1998年12月、1997年至1999年,1998年至2000年中各股票分别在这一期间的贝塔值,存为数据集finance.betas98、 finance.betas99和finance.betas00。5,用CAPM模型对1998年的超额月收益率数据逐月进行横截面回归。data finance.beta97; set finance.betas97; keep _DEPVAR_ mr2;data finance.data98; se
6、t finance.rtndata;=199801 and stkcd=199812;/*transpose finance.data98 into finance.trdata98 with SAS-Analyst*/data finance.forgama98; merge finance.beta97 finance.trdata98;proc reg data=finance.forgama98 outest=finance.gama98;model month1-month12=mr2; quit;得到1998年12个1的值:Monthgama1monthGama1month1 -0
7、.00688month4 0.010825Month7 -0.0211month10 -0.03461month2 -0.00043month5 -0.05118Month8 -0.05573month11 0.001571month3 -0.04984month6 -0.00631Month9 0.029071month12 0.0069874,重复上面的步骤,分别得到1998年至2001年间的48个1值,如下:1998011999010.0156082000010.094483200101-0.01626199802199902-0.02949200002-0.06926200102-0.
8、00681998031999030.023094200003-0.06399200103-0.027411998041999040.010991200004-0.065082001040.008069199805199905-0.04009200005-0.00462200105-0.096841998061999060.015307200006-0.021042001060.012047199807199907-0.011842000070.013977200107-0.04051998081999080.007718200008-0.00401200108-0.03077199809199
9、909-0.000422000090.0084332001090.037281199810199910-0.00275200010-0.00679200110-0.03481998111999110.026066200011-0.049512001110.000509199812199912-0.03851200012-0.023982001120.0234935,对这48个估计值进行下列假设检验:应用SAS/Analyst/Statistics/Hypothesis Test/One-sample t-test for a Mean过程,得到以下结果:mean值-0.01,t统计量-2.440,p值0.0185,所以
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