風險值的觀念近年來逐漸被金融機構級投資人所接受，目前已是眾所皆知的風險控管工具。極值理論(EVT)的運用非常廣泛，財務風險的衡量亦是其中一項。極值理論主要分為Block Maxima模型，即一般化極值理論(generalized extreme value, GEV)，和POT (peak-over-threshold) 模型。Jorino (1996)指出極值理論的優點在於評估厚尾現象的風險值。
本篇論文主要選取100家股票依流動性高低排序，分成10組投資組合，利用極值理論估計風險值。並與歷史模擬法...等其他衡量風險值模型相比較，探討流動性對於風險值評估的影響，預期極值理論在高流動性與低流動性的投資組合中，評估風險值最為精準。
關鍵字：風險值(Value at Risk)，極值理論(extreme value theory)，流動性(liquidity)
Within these few years, the concept of Value-at-Risk (VaR) has been accepted by financial institutions even investors, and it become a very famous risk control tool. And Extreme Value Theory (EVT) by Gnedenko is the very popular evaluation to calcu-late financial risk in the world.
There are two methods of Extreme Value Theory to calculate VaR, one is Block Maxima model, i.e. Generalized Extreme Value (GEV); the other is Peak-Over-Threshold (POT). Even, the Extreme Value Theory is the best way to eval-uate the risk of fat-tail phenomenon was proved by Jorino in 1996.
You will find 10 parties of portfolio selected from 100 stocks of financial market have been chosen based on different liquidity from low to high per this paper. They are evaluated by quite different ways of Value-at-Risk, of course Extreme Value Theory (EVT) included. Believe, Extreme Value Theory will be the best choice of evaluated VaR in the extreme events, and explore the impact of liquidity on VaR estimation as well.
Key Words: Value at Risk, extreme value theory, liquidity
