匯率避險策略應用風險值之探討

Abstract

論文摘要 隨著金融商品的多樣化，使得資產報酬愈來愈難以估計，因此風險管理受到極大的重視，眾多的風險指標之中，風險值以損失比例或實際金額將風險量化，明確並具體表達出資產的風險。 近年相關研究逐漸增加，衡量風險值模型不斷更新，目前常用的包括變異數-共變異數法(Delta-Normal Method)，蒙地卡羅模擬法(Monte-Carlo Simulation Method)，歷史模擬法(Historical Simulation Method)。 雖然風險值的評估日益重要，然而許多避險基金的策略，還是使用傳統的最小化變異數避險策略，與是本文將風險值引入，作為避險策略的指標之ㄧ，因此本文將介紹風險值及資產波動性評估計算的方法，實證研究方面，以已開發國家匯率市場做為研究資料，利用匯率的投資，比較最小化變異數避險策略與最小化風險值避險策略下的避險比率，以及日報酬分配特性及績效，並以靜態避險作為樣本內資料，以動態避險作為樣本外資料加以比較。

Abstract With trend of various derivatives financial markets, it is more difficult then before to estimate the assets return. Value at Risk（VaR）is an emerging tool of risk management. In several risk indicators, VaR show the probability loss of asset by money or return rate to quantify risk. It makes risk simply and clearly to understand. With more and more research about VaR, there are several model for estimating VaR including Delta-Normal Method, Monte Carlo Simulation Method, Historical Simulation Method. Although the estimate of VaR become more important, there are still many hedge found managers use standard deviation to measure risk, and use the minimize-variance strategy to hedge. In this paper, the method of taking VaR into hedge strategy will be introduced, and the model which is used to estimate VaR and the volatility of assets will also be discussed. In the sample test, the data comes out from 11 developed countries’ monetary history. They are compared with method of the hedge ratio, performance and statistic of daily return by minimize-variance, minimize-CVaR and minimize-VaR hedgy strategy. The static hedge method for in the sample data and dynamic hedge method for out of sample data are two methods adopted to come out conclusions.