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From |
"kelly johnson" <econometrics@hotmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
RE: st: Re: seasonality |

Date |
Sat, 02 Apr 2005 11:55:07 -0500 |

thank you for your reply. can you please elaborate a bit more on the additive method to use for actual retruns. i've generated the required dummy variables. and i've regressed my return series on the 11 dummy variables. how do i proceed from here? where do i add teh original mean (because as it is i'm using the original series in the regression). any help would be appreciated. also, is there any test for significance that can be done to test the seasonality? a chi square test of some sort?

thanks

From: Kit Baum <baum@bc.edu>_________________________________________________________________

Reply-To: statalist@hsphsun2.harvard.edu

To: statalist@hsphsun2.harvard.edu

Subject: st: Re: seasonality

Date: Sat, 2 Apr 2005 09:14:14 -0500

The textbook treatment of seasonality in economic and financial time series involves creating a set of seasonal dummies (you need 3 for Q, 11 for M) and then regressing your series on that set of dummies. Add the original mean back into the series and you have a deseasonalized series of stock returns.

One can deal with additive seasonality (which would be more appropriate for your returns series) or multiplicative seasonality (which would be more appropriate for levels series, such as stock prices). The latter is achieved by regressing log(Y) on the dummies, exponentiating the residuals, and adding back the mean of the original series.

Kit Baum, Boston College Economics

http://ideas.repec.org/e/pba1.html

On Apr 2, 2005, at 2:33 AM, Kelly wrote:

thank you for your reply. i express my seasonality question a bit clearer.

suppose we are looking at five years of stock retruns data. how can we test

for teh presence of seasonality in specific months?

if i were to do the typical adjustment, i'd first calculated the average

over teh entire time period, and divide my returns by that average. call the

new variable rtn_adj. then i would have to average, by month, to get the

seasonl adjsutement indices for each month (which should sum up to 12). i

can then retruns and multiply teh original data by each of the appropriate

seasonal adjsutemtn factor. My question: is there a simpler was to do this?

also, how can i do f-test to test teh presence of seasonality? to give youa

better idea, i'm attaching a sample of the data to give you an idea what i'm

looking at.

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**References**:**st: Re: seasonality***From:*Kit Baum <baum@bc.edu>

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