DocumentCode
2771113
Title
Market Risk Measurement for Crude Oil: A Wavelet Based VaR Approach
Author
Lai, Kin Keung ; He, Kaijian ; Xie, Chi ; Chen, Shou
fYear
0
fDate
0-0 0
Firstpage
2129
Lastpage
2136
Abstract
With the development of technology and financial engineering tools, oil markets are more competitive and volatile than ever before. This places the accurate and reliable measurement of market risks in the crucial position for both investment decision and hedging strategy designs. This paper tackles the measurement of risks from a Value at Risk (VaR) perspective. Since traditional ARMA-GARCH approach doesn´t suffice, this paper proposes ex-ante based approach for hybrid algorithm design and further applies this methodology with a wavelet approach to VaR estimates. Empirical studies of the proposed Wavelet Decomposed Value at Risk (WDVaR) have been conducted on two major oil markets (I.e. WTI & Brent). Experiment results suggest that the performance of WDVaR improves upon ARMA-GARCH model at higher confidence levels. Meanwhile, WDVaR offer considerable flexibility during modeling process. WDVaR can be tailored to specific market characteristics and its performance can be further improved with more careful parameter tuning.
Keywords
crude oil; marketing; risk management; wavelet transforms; ARMA-GARCH approach; crude oil; hedging strategy designs; investment decision; market risk measurement; market risks; value at risk; wavelet approach; wavelet based VaR approach; Econometrics; Educational institutions; Environmental economics; Helium; Investments; Petroleum; Power generation economics; Reactive power; Reliability engineering; Risk management;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9490-9
Type
conf
DOI
10.1109/IJCNN.2006.246984
Filename
1716374
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