Jian-Hsin Chou

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This study present a hybrid method of estimating VAR, combining Neural Network and ARMA. Empirical results demonstrate that the hybrid method obtained superior results to the conventional method in estimating VAR. When applied to the Shanghai stock market both the conventional and hybrid methods performed well in terms of accuracy, with the only poorly(More)
This paper employs the Kalman filter procedure to explore the impact of yield curve factors on the hedging of Japanese government bond (JGB) using treasury futures. Three parameters (i.e., level parameter, slope parameter, and curvature parameter) embedded in Nelson and Siegel (1987) are used to be the proxies of interest rate risk. The out-of-sample(More)
Conventional VAR (Value at Risk) estimation includes historical simulation, variance/covariance, and the Monte Carlo simulation method. This study is the first to present a hybrid method of estimating VAR, combining ARMA and Neural Network. Empirical results demonstrate that the hybrid method obtained superior results to the conventional method in(More)
Multiple Attribute Decision Making (MADM) problems are commonly encountered in everyday aspect of life. They aim at selecting the optimal alternative among some courses of action in the presence of multiple, usually conflicting, attributes. It is not surprising that, at times, the performance rating cannot be assessed precisely. It may be represent the(More)
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