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Asymmetry of Information Flow Between Volatilities Across Time Scales

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Author Info
Ramazan Gencay () ( Department of Economics, Simon Fraser University)
Nikola Gradojevic () ( Faculty of Business Administration, Lakehead University)
Faruk Selcuk ( Department of Economics, Bilkent University)
Brandon Whitcher ( GlaxoSmithKline Clinical Imaging Centre, Hammersmith Hospital London, United Kingdom)

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Abstract

Conventional time series analysis, focusing exclusively on a time series at a given scale, lacks the ability to explain the nature of the data generating process. A process equation that successfully explains daily price changes, for example, is unable to characterize the nature of hourly price changes. On the other hand, statistical properties of monthly price changes are often not fully covered by a model based on daily price changes. In this paper, we simultaneously model regimes of volatilities at multiple time scales through wavelet-domain hidden Markov models. We establish an important stylized property of volatility across different time scales. We call this property asymmetric vertical dependence. It is asymmetric in the sense that a low volatility state (regime) at a long time horizon is most likely followed by low volatility states at shorter time horizons. On the other hand, a high volatility state at long time horizons does not necessarily imply a high volatility state at shorter time horizons. Our analysis provides evidence that volatility is a mixture of high and low volatility regimes, resulting in a distribution that is non-Gaussian. This result has important implications regarding the scaling behavior of volatility, and consequently, the calculation of risk at different time scales

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Publisher Info
Paper provided by Rimini Centre for Economic Analysis in its series Working Paper Series with number wp27_09.

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Date of creation: Jan 2009
Date of revision: Jan 2009
Handle: RePEc:rim:rimwps:wp27_09

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Related research
Keywords: Discrete wavelet transform; wavelet-domain hidden Markov trees; foreign exchange markets; stock markets; multiresolution analysis; scaling;

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Find related papers by JEL classification:
G0 - Financial Economics - - General
G1 - Financial Economics - - General Financial Markets
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General

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This page was last updated on 2009-11-4.


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