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Open AccessArticle

Does the Assumption on Innovation Process Play an Important Role for Filtered Historical Simulation Model?

1
Department of Statistics, Hacettepe University, 06800 Ankara, Turkey
2
School of Mathematics, University of Manchester, Manchester M13 9PL, UK
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Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2018, 11(1), 7; https://doi.org/10.3390/jrfm11010007
Received: 30 November 2017 / Revised: 17 January 2018 / Accepted: 22 January 2018 / Published: 23 January 2018
(This article belongs to the Special Issue Extreme Values and Financial Risk)
Most of the financial institutions compute the Value-at-Risk (VaR) of their trading portfolios using historical simulation-based methods. In this paper, we examine the Filtered Historical Simulation (FHS) model introduced by Barone-Adesi et al. (1999) theoretically and empirically. The main goal of this study is to find an answer for the following question: “Does the assumption on innovation process play an important role for the Filtered Historical Simulation model?”. For this goal, we investigate the performance of FHS model with skewed and fat-tailed innovations distributions such as normal, skew normal, Student’s-t, skew-T, generalized error, and skewed generalized error distributions. The performances of FHS models are evaluated by means of unconditional and conditional likelihood ratio tests and loss functions. Based on the empirical results, we conclude that the FHS models with generalized error and skew-T distributions produce more accurate VaR forecasts. View Full-Text
Keywords: Filtered Historical Simulation Model; Value-at-Risk; volatility; backtesting Filtered Historical Simulation Model; Value-at-Risk; volatility; backtesting
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Altun, E.; Tatlidil, H.; Ozel, G.; Nadarajah, S. Does the Assumption on Innovation Process Play an Important Role for Filtered Historical Simulation Model? J. Risk Financial Manag. 2018, 11, 7.

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