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A Statistical Neural Network Approach for Value-at-Risk Analysis

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3 Author(s)
Xiaoliang Chen ; Dept. of Manage. Sci., City Univ. of Hong Kong, Kowloon, China ; Kin Keung Lai ; Yen, J.

This study develops a new methodology based on ANN for Value-at-Risk (VaR) modeling. Specifically, we propose a statistical procedure for ANN model selection. The statistical ANN deals with each layer individually and estimates the weights of subsequent layer with those of preceding layers fixed. This allows the derivation of statistical theory for model selection, which reduces the need to fit a comprehensive set of models. Experiment results show that the statistical ANN approach performs well on stock index return series compared to traditional forecasting methods.

Published in:

Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on  (Volume:2 )

Date of Conference:

24-26 April 2009