A high-order Markov-switching model for risk measurement

T. K. Siu, W. K. Ching, E. Fung, M. Ng, Xun Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)

Abstract

In this paper, we introduce a High-order Markov-Switching (HMS) model for measuring the risk of a portfolio. We suppose that the rate of return from a risky portfolio follows an HMS model with the drift and the volatility modulated by a discrete-time weak Markov chain. The states of the weak Markov chain are interpreted as observable states of an economy. We adopt the Value-at-Risk (VaR) as a metric for market risk quantification and examine the high-order effect of the underlying Markov chain on the risk measures via backtesting.
Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalComputers and Mathematics with Applications
Volume58
Issue number1
DOIs
Publication statusPublished - 1 Jul 2009

Keywords

  • Higher-order Markov chain process
  • Portfolio
  • Regime-switching
  • Risk management
  • Value-at-Risk
  • Weak Markov chain process

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics

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