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Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach

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  • Kaijian He

    () (Business School, Hunan University of Science and Technology, Xiangtan, Hunan 411201, China
    Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong)

  • Kin Keung Lai

    () (Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong)

  • Guocheng Xiang

    () (Business School, Hunan University of Science and Technology, Xiangtan, Hunan 411201, China)

Abstract

In the increasingly globalized economy these days, the major crude oil markets worldwide are seeing higher level of integration, which results in higher level of dependency and transmission of risks among different markets. Thus the risk of the typical multi-asset crude oil portfolio is influenced by dynamic correlation among different assets, which has both normal and transient behaviors. This paper proposes a novel multivariate wavelet denoising based approach for estimating Portfolio Value at Risk (PVaR). The multivariate wavelet analysis is introduced to analyze the multi-scale behaviors of the correlation among different markets and the portfolio volatility behavior in the higher dimensional time scale domain. The heterogeneous data and noise behavior are addressed in the proposed multi-scale denoising based PVaR estimation algorithm, which also incorporatesthe mainstream time series to address other well known data features such as autocorrelation and volatility clustering. Empirical studies suggest that the proposed algorithm outperforms the benchmark ExponentialWeighted Moving Average (EWMA) and DCC-GARCH model, in terms of conventional performance evaluation criteria for the model reliability.

Suggested Citation

  • Kaijian He & Kin Keung Lai & Guocheng Xiang, 2012. "Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach," Energies, MDPI, Open Access Journal, vol. 5(4), pages 1-26, April.
  • Handle: RePEc:gam:jeners:v:5:y:2012:i:4:p:1018-1043:d:17268
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    2. repec:taf:applec:v:49:y:2017:i:9:p:929-939 is not listed on IDEAS
    3. Zhi-Fu Mi & Yi-Ming Wei & Bao-Jun Tang & Rong-Gang Cong & Hao Yu & Hong Cao & Dabo Guan, 2017. "Risk assessment of oil price from static and dynamic modelling approaches," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 929-939, February.
    4. Yu, Lean & Zhao, Yang & Tang, Ling, 2014. "A compressed sensing based AI learning paradigm for crude oil price forecasting," Energy Economics, Elsevier, vol. 46(C), pages 236-245.
    5. Kaijian He & Hongqian Wang & Jiangze Du & Yingchao Zou, 2016. "Forecasting Electricity Market Risk Using Empirical Mode Decomposition (EMD)—Based Multiscale Methodology," Energies, MDPI, Open Access Journal, vol. 9(11), pages 1-11, November.
    6. He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.

    More about this item

    Keywords

    Portfolio Value at Risk; multivariate wavelet analysis; Exponential Weighted Moving Average (EWMA) model; DCC-GARCH model; multivariate time series model; heterogeneous market hypothesis;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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