Risk Evaluation for ARCH-GARCH vs.RBF NN Forecasting Models: Application to High-Frequency Time Series

摘要：

Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we consider the accuracy of forecasting models based on statistical (stochastic) methods sometimes called as hard computing and a soft methodology based on soft or granular computing. It is found that the risk estimation process based on soft methods is simplified and less critical to the question whether the data is true crisp or white noise.

关键词： Risk in decision making forecasting accuracy time series ARCH-GARCH models soft neural networks granular computing

作者: Milan Marcek Dusan Marcek

作者单位: MEDIS Nitra, Ltd., Pri Dobrotke 659/81, Slovak Republic Institute of Computer Science, Silesian University, Bezruc Square 13, Opava, 746 01,Czech Republic F

会议类型: 国际会议

会议名称: The 2nd International Conference on Risk Analysis and Crisis Response(第二届风险分析与危机反应国际学术研讨会)

会议地点: 北京

会议语种:英文

页码: 150-156

在线出版日期: 2009-10-19（万方平台首次上网日期，不代表论文的发表时间）