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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