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From |
"felix kreppel" <felix.kreppel@gmx.de> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: Re: st: Regression with different firms |

Date |
Fri, 10 Aug 2012 14:27:55 +0200 |

Thank you for your answer. My original empirical analysis works as follows: I am estimating a 4-Factor Model (with 4 factors: SMB, market_return, HML, WML which are the same for all firms) augmented by a fifth explanatory variable (which influence I want to evaluate) which is calculated as the average weekly standard deviation of excess return 12 months prior to month t for each firm: return_i_t=a*market_return_t+b*SMB_t+c*HML_t+d*WML_t+e*std_i_t where t indicates the month and i indicates the firm over a sample period of 25 years. What I did so far to solve my regression problem was to average all firm returns to an equally weighted index and also averaged all the previous volatilities to an equally weighted index and then estimated the following regression return_t=a*market_return_t+b*SMB_t+c*HML_t+d*WML_t+e*std_t with the command: newey return market_return smb hml wml std, lag(4) to address the serial correlation in the error terms. I do not know, however, if this approach works. Especially averaging all the previous standard deviations to one independent variable. Isn't there a possibility to run a regression for each single firm (say for each year) and then average coefficients, significane levels and standard errors together over the whole time period? > -------- Original-Nachricht -------- > Datum: Fri, 10 Aug 2012 10:42:43 +0000 > Von: Christopher Baum <kit.baum@bc.edu> > An: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> > Betreff: Re: Re: st: Regression with different firms > 
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**Follow-Ups**:**Re: Re: st: Regression with different firms***From:*"felix kreppel" <felix.kreppel@gmx.de>

**References**:**Re: Re: st: Regression with different firms***From:*Christopher Baum <kit.baum@bc.edu>

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