上证综合指数的肥尾度量和风险值估计及预测*

 

彭作祥12 黎实1 庞皓1   

1西南财经大学统计学院,四川成都,610074; 2西南师范大学数学与财经学院,重庆市北碚,400715

 

内容摘要：基于极值理论和广义Pareto分布方法，本文通过局部拟合金融时序的尾分布，运用尾指数刻画金融时序的肥尾特征，系统地给出了尾指数的估计与检验以及风险值的估计与预测方法，并与常用的ARCH/GARCH类模型进行了沪市综指的一步风险值预测实证比较分析。实证结果显示，使用广义Pareto分布方法进行风险预测相对优于GARCH类模型。

关键词：在险值 尾指数 预测 极值理论 实证分析

中图分类号：F830.9，F224.0 文献标识码：A   文章编号：

 

Fat-tails measurement and Value-at-Risk estimation and prediction of

Composite Index of Shanghai Stock Exchange

Peng Zuo-xiang1 2 Li Shi1 Pang Hao1

(1 School of Statistics, Southwestern University of Finance and Economics, Chengdu, 610074;

2 School of Mathematics and Finance, Southwestern Normal University, Chongqing, 400715)

 

Abstract: Based on extreme value theory and General Pareto Distribution (GPD), this paper analyzes and describes the performance of the thick-tail of the high frequency financial time series data with tail index which fitted by local fitness on tail distribution of the data. Both process, one is procedures of estimating and testing of the tail index, another is estimating and forecasting methods of Value-at-Risk, are given systematically. The one-step forward forecasting results of the Composite Index of Shanghai Stock Exchange by extreme value theory and other well-known modeling techniques, such as ARCH/GARCH models, are empirically compared and contrasted. The empirical results argue that GPD method is superior to GARCH models on estimating and forecasting of Value-at-Risk.

 

Key Words: Value-at-Risk; Tail Index; Forecasting; Extreme Value Theory; Empirical Analysis.

 

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