穩定分配模型的風險值計算 -以台灣指數與外匯市場之資料為佐證

Abstract

本文參考I. Khindanova, S. Rachev and E. Schwartz (2001)所提出的論點：認為金融市場的資料序列普遍存在厚尾的現象。因此，在傳統的高斯分配的假設之下，極端事件發生的機率容易被低估，亦造成風險值 (Value-at-Risk, VaR)的估算過於樂觀。本文驗證台灣的金融市場亦普遍存在厚尾的現象，並參考I. Khindanova, S. Rachev and E. Schwartz (2001)中所述的α-穩定分配模型配適台灣金融市場的實際資料，期望能解決錯估尾端機率而造成的資產價值損失。

The value-at-risk measurement (VaR) is an important indicator when a financial institution wishes to evaluate its exposure to market risks. Referring to I. Khindanova, S. Rachev and E. Schwartz (2001), the traditional Gaussian estimation of VaR generally overlooks the heavy-tailed properties exhibited financial data series, thereby incurring unexpected losses under extreme circumstances. This paper follows I. Khindanova, S. Rachev and E. Schwartz (2001) to show that heavy-tailed properties exist for Taiwan’s financial market as well and aims to prove that this issue can be effectively solved by fitting the financial data to an α-stable distribution.