預測金融市場波動性

Forecasting Financial Market Volatility

柯宗漢(Tsung-Han Ke)

指導教授 ： 胡毓彬

國立暨南國際大學/管理學院/國際企業學系/博士(2014年)

https://doi.org/10.6837/NCNU.2014.00004

摘要

本文的研究目的為利用GARCH(1,1)-X 模型預測金融市場的波動性，並且提出由多變量變數當中，建構有效的預測變數之新方法，以改善GARCH(1,1)模型的預測績效，其推導的過程為極大化被預測目標變數的平方與多變量變數之線性組合平方的共變異。為了驗證所提出的方法之優越性，本研究除了透過數值模擬，在實證分析方面，包括美國S&P 500指數、美國聯邦資金利率、日幣兌換美金匯率，和台灣股市加權指數的波動性預測，以及美國S&P 500指數風險值的預測。研究結果顯示，本研究所提出的新方法，有效提升波動性的預測能力，為未來在資料的分析，提供新的觀點。

關鍵字

條件異質變異效果 ； 線性轉換 ； 波動性預測

並列摘要

The purpose of this research uses the GARCH(1,1)-X model to forecast the volatility of a financial market, and to constructs a proper predictor from a multivariate variable to improve the forecasting performance of the GARCH(1,1) model. This research derives the method by maximising the covariance between the squared series of the target variable and that of the linear combination combined by the multivariate variables. This research demonstrates the advantages of the proposed method through simulation studies and empirical studies on forecasting the volatility and the Value-at-Risk of the S&P 500 Index, the US Effective Federal Funds Rate, the exchange rate of the Japanese yen against the US dollar, and Taiwan Weighted Stock Index. The findings confirm the utility of the proposed method in volatility forecasting, and provide some insights of the data.

並列關鍵字

Conditional heteroskedastic effect ； Linear transformation ； Forecasting volatility

參考文獻

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