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Un approccio metrico per lo studio dei dati finanziari

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Author Info
Luca Grilli ()

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Abstract

In this paper I present a time series analysis based on a metrical approach. I use a definition of distance which depends on the sample correlation coefficient among bonds. The dataset consists on daily returns of US treasury bonds. By mean of a Linkage-Algorithm bonds are classified according to the distance which show the cluster structure. It is evident how the cluster structure depends strongly on maturity date, bonds are classified in three different clusters, one of them consists on long term bonds. The analysis is focused on long term bonds, introducing a modified time series, I show how is possible to evidentiate a complex cluster structure even in this class of bonds.

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Publisher Info
Paper provided by Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia in its series Quaderni DSEMS with number lg_igr_2004.

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Date of creation: Feb 2004
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Publication status: Published in Metodi Matematici per l'Economia e la Finanza (a cura di Lucia Maddalena), Collana Interdipartimentale di Studi Economici, Volume 4, 2005 ( ISBN: 88-495-1012-8), Edizioni Scientifiche Italiane.
Handle: RePEc:ufg:qdsems:lg_igr_2004

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Postal: Largo Papa Giovanni Paolo II, 1 -71100- Foggia (I)
Phone: +390881753730
Fax: +390881775616
Web page: http://www.dsems.unifg.it
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Related research
Keywords: Fixed income; clustering;

Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
D49 - Microeconomics - - Market Structure and Pricing - - - Other

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This page was last updated on 2009-12-9.

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