Classifying the Markets Volatility with ARMA Distance Measures

Edoardo Otranto ()

Econometrics from EconWPA

Abstract: The financial time series are often characterized by similar volatility structures. The selection of series having a similar behavior could be important for the analysis of the transmission mechanisms of volatility and to forecast the time series, using the series with more similar structure. In this paper a metrics is developed in order to measure the distance between two GARCH models, extending well known results developed for the ARMA models. The statistic used to calculate it follows known distributions, so that it can be adopted as a test procedure. These tools can be used to develope an agglomerative algorithm in order to detect clusters of homogeneous series.

Keywords: GARCH models; clusters; agglomerative algorithm (search for similar items in EconPapers)
JEL-codes: C12 C22 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-fin
Date: 2004-02-17, Revised 2004-03-05
Note: Type of Document - pdf; prepared on WinXP; to print on Laser witer II NP; pages: 11; figures: 4 figures in the document. PDF document submitted via ftp
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Persistent link: http://EconPapers.repec.org/RePEc:wpa:wuwpem:0402009

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