A high-order Markov-switching model for risk measurement

T. K. Siu; W. K. Ching; E. Fung; Kwok Po NG; X. Li

doi:10.1016/j.camwa.2008.10.099

A high-order Markov-switching model for risk measurement

T. K. Siu
, W. K. Ching^*
, E. Fung
, Kwok Po NG
, X. Li

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Journal article › peer-review

19 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 language	English
Pages (from-to)	1-10
Number of pages	10
Journal	Computers and Mathematics with Applications
Volume	58
Issue number	1
DOIs	https://doi.org/10.1016/j.camwa.2008.10.099
Publication status	Published - Jul 2009

User-Defined Keywords

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

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10.1016/j.camwa.2008.10.099

Cite this

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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.",

keywords = "Higher-order Markov chain process, Portfolio, Regime-switching, Risk management, Value-at-Risk, Weak Markov chain process",

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note = "Funding Information: The authors would like to thank the anonymous referee for many helpful and constructive comments, suggestions and corrections. Research supported in part by RGC Grant 7017/07P and HKU Strategic Theme on Computational Sciences and HKU CRGC Grant, and in part by HKU Hung Hing Ying Physical Science Research Grant. ",

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AU - Siu, T. K.

AU - Ching, W. K.

AU - Fung, E.

AU - NG, Kwok Po

AU - Li, X.

N1 - Funding Information: The authors would like to thank the anonymous referee for many helpful and constructive comments, suggestions and corrections. Research supported in part by RGC Grant 7017/07P and HKU Strategic Theme on Computational Sciences and HKU CRGC Grant, and in part by HKU Hung Hing Ying Physical Science Research Grant.

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N2 - 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.

AB - 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.

KW - Higher-order Markov chain process

KW - Portfolio

KW - Regime-switching

KW - Risk management

KW - Value-at-Risk

KW - Weak Markov chain process

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DO - 10.1016/j.camwa.2008.10.099

M3 - Journal article

AN - SCOPUS:67349216804

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JO - Computers and Mathematics with Applications

JF - Computers and Mathematics with Applications

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ER -

A high-order Markov-switching model for risk measurement

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