Classifying the Markets Volatility with ARMA Distance Measures

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Classifying the Markets Volatility with ARMA Distance Measures

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Edoardo Otranto (DEIR, Sassari)

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Edoardo Otranto

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.

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Paper provided by EconWPA in its series Econometrics with number 0402009.

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Length: 11 pages
Date of creation: 17 Feb 2004
Date of revision: 05 Mar 2004
Handle: RePEc:wpa:wuwpem:0402009

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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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions

This paper has been announced in the following NEP Reports:

NEP-ALL-2004-02-23 (All new papers)
NEP-ECM-2004-02-23 (Econometrics)
NEP-ETS-2004-02-23 (Econometric Time Series)
NEP-FIN-2004-02-23 (Finance)

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59. [Downloadable!] (restricted)
Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)

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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

Edoardo Otranto, 2008. "Clustering Heteroskedastic Time Series by Model-Based Procedures," Working Paper CRENoS 200801, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia. [Downloadable!]
Other versions:
- Otranto, Edoardo, 2008. "Clustering heteroskedastic time series by model-based procedures," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4685-4698, June. [Downloadable!] (restricted)

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