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Title: Essay on Tail Risk Measure with Application in Volatility Forecast
Authors: ZHAO, YUPEI (趙雨培)
Department: Department of Finance and Business Economics
Faculty: Faculty of Business Administration
Keywords: Tail risk
Hill estimator
Extreme value theory
Composite Pareto-Nomal model
Volatility forecast
Issue Date: 2016
Citation: ZHAO, Y. P. (2016). Essay on Tail Risk Measure with Application in Volatility Forecast (Outstanding Academic Papers by Students (OAPS)). Retrieved from University of Macau, Outstanding Academic Papers by Students Repository.
Abstract: In this paper, we study the tail risk measure in financial market. Recently, Kelly and Jiang (2014) propose a measure based on Hill (1975)'s method. They arbitrarily estimate the Hill tail risk by fixing the threshold at the 0.05 empirical quantile level. We show by various simulation experiments that their measure is very sensitive to the choice of thresholds. To endogenize the threshold choice, we propose a novel composite Pareto-Normal model for tail risk measure. Using the variance decomposition, our tail risk measure natually maps to the overall volatility. We show that the induced total volatility from our estimated tail risk measure matches the market volatility well, whereas that of Kelly and Jiang's Hill estimate deviates substantially from the market volatility. Finally, we investigate the predictive power of tail risk on realized volatility. The results show that our proposed method outperform the Hill estimate in volatility forecast
Instructor: Dr. KO, IAT MENG
Programme: Master of Science in Finance Degree
Appears in Collections:FBA OAPS 2016

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