• About
  • Policies
  • What is openaccess
  • Library
  • Contact
Advanced search
      View Item 
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Economics, Administrative And Social Sciences
      • Department of Economics
      • View Item
      •   BUIR Home
      • Scholarly Publications
      • Faculty of Economics, Administrative And Social Sciences
      • Department of Economics
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Asymmetry of information flow between volatilities across time scales

      Thumbnail
      View / Download
      1.9 Mb
      Author
      Gençay, R.
      Gradojevic, N.
      Selçuk F.
      Whitcher, B.
      Date
      2010
      Source Title
      Quantitative Finance
      Print ISSN
      14697688
      Volume
      10
      Issue
      8
      Pages
      895 - 915
      Language
      English
      Type
      Article
      Item Usage Stats
      110
      views
      97
      downloads
      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. © 2010 Taylor & Francis.
      Keywords
      Advanced econometrics
      Anomalies in prices
      Applied econometrics
      Applied finance
      Permalink
      http://hdl.handle.net/11693/22210
      Published Version (Please cite this version)
      http://dx.doi.org/10.1080/14697680903460143
      Collections
      • Department of Economics 649
      Show full item record

      Browse

      All of BUIRCommunities & CollectionsTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartmentsThis CollectionTitlesAuthorsAdvisorsBy Issue DateKeywordsTypeDepartments

      My Account

      Login

      Statistics

      View Usage StatisticsView Google Analytics Statistics

      Bilkent University

      If you have trouble accessing this page and need to request an alternate format, contact the site administrator. Phone: (312) 290 1771
      Copyright © Bilkent University - Library IT

      Contact Us | Send Feedback | Off-Campus Access | Admin | Privacy