TY - GEN
T1 - A Wavelet Based Multi Scale VaR Model for Agricultural Market
AU - He, Kaijian
AU - Keung Lai, Kin
AU - Guu, Sy-Ming
AU - Zhang, Jinlong
PY - 2008
Y1 - 2008
N2 - Participants in the agricultural industries are subject to significant market risks due to long production lags. Traditional methodology analyzes the risk evolution following a time invariant approach. However, this paper analyzes and proposes wavelet analysis to track risk evolution in a time variant fashion. A wavelet-econometric hybrid model is further proposed for VaR estimates. The proposed wavelet decomposed VaR (WDVaR) is ex-ante in nature and is capable of estimating risks that are multi-scale structured. Empirical studies in major agricultural markets are conducted for both the hybrid ARMA-GARCH VaR and the proposed WDVaR. Experiment results confirm significant performance improvement. Besides, incorporation of time variant risks tracking capability offers additional flexibility for adaptability of the proposed hybrid algorithm to different market environments. WDVaR can be tailored to specific market characteristics to capture unique investment styles, time horizons, etc. © Springer-Verlag Berlin Heidelberg 2008.
AB - Participants in the agricultural industries are subject to significant market risks due to long production lags. Traditional methodology analyzes the risk evolution following a time invariant approach. However, this paper analyzes and proposes wavelet analysis to track risk evolution in a time variant fashion. A wavelet-econometric hybrid model is further proposed for VaR estimates. The proposed wavelet decomposed VaR (WDVaR) is ex-ante in nature and is capable of estimating risks that are multi-scale structured. Empirical studies in major agricultural markets are conducted for both the hybrid ARMA-GARCH VaR and the proposed WDVaR. Experiment results confirm significant performance improvement. Besides, incorporation of time variant risks tracking capability offers additional flexibility for adaptability of the proposed hybrid algorithm to different market environments. WDVaR can be tailored to specific market characteristics to capture unique investment styles, time horizons, etc. © Springer-Verlag Berlin Heidelberg 2008.
KW - financial
KW - risk management
KW - time series analysis
KW - Value at Risk
KW - wavelets and fractals
UR - https://www.scopus.com/pages/publications/78650155912
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-78650155912&origin=recordpage
U2 - 10.1007/978-3-540-87477-5_46
DO - 10.1007/978-3-540-87477-5_46
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9783540874768
VL - 14
T3 - Communications in Computer and Information Science
SP - 429
EP - 438
BT - Modelling, Computation and Optimization in Information Systems and Management Sciences
T2 - 2nd International conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, MCO 2008
Y2 - 8 September 2008 through 10 September 2008
ER -