[R-SIG-Finance] how to smooth timeseries without the lagging?

[Eric Zivot]

"smoothing" is not a well defined term. In the Kalman filter literature, smoothing refers to state extraction at time t using all available information (before and after t) and typically results in two-sided moving average type algorithms. The whole point of smoothing is to reduce the noise in the data and extract a "smooth" component. This invariably involves some kind of averaging of the observation both before and after the observation. So it doesn't make sense to have a "smoother" that does not involve some lagging effect. Otherwise, you couldn't smooth. See


Harvey, A. C. and Koopman, S. J. (2000). Signal extraction and the formulation of unobserved components
models. Econometrics Journal, Vol. 3, pp. 84-107.

for a nice discussion.

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*  Eric Zivot                  			               *
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On Sat, 25 Jul 2009 michael.sankowski at gmail.com wrote:

> Also try MESA. I was suppposed to do this for josh but have been on other projects.
> Sent via BlackBerry from T-Mobile
>
> -----Original Message-----
> From: Sean Carmody <seancarmody at gmail.com>
>
> Date: Sat, 25 Jul 2009 19:56:59
> To: Josuah Rechtsteiner<rechtsteiner at bgki.net>
> Cc: <r-sig-finance at stat.math.ethz.ch>
> Subject: Re: [R-SIG-Finance] how to smooth timeseries without the lagging?
>
>
> Or a Henderson filter. If you have a filter that looks forward as well as
> back, it will not have the lag effect. Then it'll need special treatment at
> the end of the series.
>
> (Sorry for the double email Josuah).
>
> Sean.
>
> On Sat, Jul 25, 2009 at 7:12 PM, Josuah Rechtsteiner
> <rechtsteiner at bgki.net>wrote:
>
>> maybe kalman filter is what you are looking for.
>>
>>
>>
>> Am 25.07.2009 um 05:44 schrieb Michael:
>>
>>
>>  Hi all,
>>>
>>> If I use a moving average, it will smooth the choppy time series, but
>>> it will lead to lagging...
>>>
>>> How do I smooth timeseries without the lagging effect?
>>>
>>> Thanks!
>>>
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>
>
> --
> Sean Carmody
>
> The Stubborn Mule
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