事件研究法ppt

2.450e+08 62117810 9.363e+08 1.001e+08 35249351
5. 1. 6. 9. 4.
53120908 53816511 2.827e+08 16577606 76294810
6. 3. 6. 6. 5.
51146894 1.132e+08 5.721e+08 2.785e+08 1.294e+08
tdate 2015-3-10 2015-4-22 2015-4-10 2015-4-23 2015-4-17 2015-3-20 2015-3-31 2015-3-25 2015-3-24 2015-3-27 2015-3-27 2015-4-23 2015-4-28 2015-4-14 2015-3-31 2015-3-18 2015-4-10
对数据进行0.01水平下的缩尾:winsor2 r, replace by( dm) 删除缺失值:drop if varname==.
. sum r np eps Variable r np eps Obs 8468 8468 8468 Mean .0029121 1.85e+08 .2853347 Std. Dev. .0391654 2.24e+08 .2337009 Min -.1 1.66e+07 0 Max .100137 9.36e+08 .82
Result not matched from master from using matched
# of obs. 2,612 0 2,612 8,468 (_merge==1) (_merge==2) (_merge==3)
. forvalues i = 1(1)17 { 2. . l id dm if id== `i' & dif==0 3. . reg r market_return if id==`i' & estimate_window==1 4. . predict p if id== `i' 5. . replace predicted_r=p if id== `i'& event_window==1 6. . drop p 7. . } id 9. 1 dm 546
-> dm = 852, year = 2014 Variable q Obs 167 Mean 84 Std. Dev. 48.35287 Min 1 Max 167
合并股票报酬率和年报披露日数据
merge 1:m dm using "C:\Documents and Settings\Administrator\桌面\stata\Stata11\3\return.dta"
数据清洁（处理缺失值（-997）和剔除极端值）
. sum r np eps Variable r np eps Obs 8468 8468 8468 Mean .0029527 1.85e+08 .2853347 Std. Dev. .0394437 2.24e+08 .2337009 Min -.100559 1.66e+07 0 Max .437788 9.36e+08 .82
mean = mean(AR) Ho: mean = 0 Ha: mean < 0 Pr(T < t) = 0.7222
. ttest CAR_date==0 One-sample t test Variable CAR_date Obs 170 Mean .0071528 Std. Err. .0078767
date 2015-3-10 2015-4-22 2015-4-10 2015-4-23 2015-4-17 2015-3-20 2015-3-31 2015-3-25 2015-3-24 2015-3-27 2015-3-27 2015-4-23 2015-4-28 2015-4-14 2015-3-31 2015-3-18 2015-4-10
count_estimate_obs<100 Freq. 364 400 340 1,104 Percent 32.97 36.23 30.80 100.00 Cum. 32.97 69.20 100.00
用估计窗数据估计市场模型参数和常均值收益
. forvalues i = 1(1)17 { 2. . replace CAR_date=sum( AR) if id== `i' & event_window==1 3. . }
. ttest AR==0 One-sample t test Variable AR Obs 170 Mean .0017832 Std. Err. .0030191 Std. Dev. .0393644 [95% Conf. Interval] -.0041769 .0077432 0.5906 169
Std. Err. .0032399
[95% Conf. Interval] .0003156 .0131728
(option xb assumed; fitted values) (6884 missing values generated) (10 real changes made)
在2015年新上市的wk.baidu.com司, 因此只有股票回报率而 没有年报数据
dm 546 852 961 2165 2366 2401 2438 2478 2526 300032 300048 600435 600780 600850 600973 601016 601101
name ´ðÔ²¹É·Ý ʯ»¯»úе ÖÐÄÏ´¨Éè ºì±¦Àö ̨º£ºËµç Öк£¿Æµµ ´­ËÕÉñͨ ³£±¦¹É·Ý É´¶«¿ó»ú ´ðÁú»úµç ºÏ¿µ±äƵ ±±·´µµº´ ͨ±¦ÄÜÔ´ »ª¶«µçÄÔ ±¦Ê¤¹É·Ý ´ÚÄÜ·çµç ê»»ªÄÜÔ´
mean = mean(CAR_date) Ho: mean = 0 Ha: mean < 0 Pr(T < t) = 0.8174
t = degrees of freedom = Ha: mean != 0 Pr(|T| > |t|) = 0.3651
Ha: mean > 0 Pr(T > t) = 0.1826
Result not matched from master from using matched
# of obs. 2,574 2,574 0 8,468 (_merge==1) (_merge==2) (_merge==3)
merge m:1 dm using "C:\Documents and Settings\Administrator\桌面\stata\Stata11\3\profit.dta"
. sort dm dif . by dm:gen event_w=1 if dif>=-1& dif<=10 (8326 missing values generated) . gen estimate_w=1 if dif>=-110& (7228 missing values generated) . replace event_w=0 if event_w==. (8326 real changes made) . . replace estimate_w=0 if (7228 real changes made) estimate_w==. dif<=-9
. tab dm if ´úÂë 2212 300248 600075 Total . . tab dm if ´úÂë 2212 300248 600075 Total count_event_obs<10 Freq. 364 400 340 1,104 Percent 32.97 36.23 30.80 100.00 Cum. 32.97 69.20 100.00
Chapter 1
LOREM IPSUM DOLOR LOREM
LOREM IPSUM DOLOR LOREM
LOREM IPSUM DOLOR LOREM
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
nd 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31 2014-12-31
事件研究
小组成员：温慧慧，张林娜 蔺娜娜，宋斯奇
利用sample随机选取2014年的20支股票
随机选取20个样本 sample 20，count 随机选取20%的样本 sample 20
. sum r Variable r Obs 8468 Mean .0029527 Std. Dev. .0394437 Min -.100559 Max .437788
t= degrees of freedom = Ha: mean != 0 Pr(|T| > |t|) = 0.5556
Ha: mean > 0 Pr(T > t) = 0.2778
Std. Dev. .1026993
[95% Conf. Interval] -.0083965 .0227022 0.9081 169
date, "YMD")
确定哪些数据没有足够的观测值 egen count_event_obs=count( event_w),by( dm) egen estimate_event_obs=count( estimate_w),by( dm) tab dm if count_event_obs<10 tab dm if estimate_event_obs<100
0. 9.
2.272e+08 1.951e+08
南洋股份
2015-4-27
2015-10-23
临时停牌, 重大事项
将事件日标为0，确定相对估计窗，相对事件窗
. gen td= date( tdate, "YMD") . gen d= date( . sort dm tdate . form td d %td . gen dif= td- d
r -.011416 .005348 -.031122 -.007634 -.018759 .0097 -.028747 -.02814 .068999 .099975 .008352 -.000857 -.065868 -.023943 -.020764 .004202 .022581
np
1. 3. 4. 3. 1.
LOREM IPSUM DOLOR LOREM
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
note: market_return omitted because of collinearity Source Model Residual Total r market_ret~n _cons SS 0 .103917756 .103917756 Coef. (omitted) .0067442 df 0 99 99 MS . .001049674 .001049674 t 2.08 P>|t| 0.040 Number of obs F( 0, 99) Prob > F R-squared Adj R-squared Root MSE = = = = = = 100 0.00 . 0.0000 0.0000 .0324