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

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Business School, Hunan University of Science and Technology, Xiangtan, Hunan 411201, China
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Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong
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Author to whom correspondence should be addressed.
Energies 2012, 5(4), 1018-1043; https://doi.org/10.3390/en5041018
Received: 13 February 2012 / Revised: 5 April 2012 / Accepted: 12 April 2012 / Published: 18 April 2012
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. View Full-Text
Keywords: Portfolio Value at Risk; multivariate wavelet analysis; Exponential Weighted Moving Average (EWMA) model; DCC-GARCH model; multivariate time series model; heterogeneous market hypothesis Portfolio Value at Risk; multivariate wavelet analysis; Exponential Weighted Moving Average (EWMA) model; DCC-GARCH model; multivariate time series model; heterogeneous market hypothesis
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He, K.; Lai, K.K.; Xiang, G. Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach. Energies 2012, 5, 1018-1043.

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