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This paper proposes a novel and simple approach to compute daily Value at Risk (VaR) and Expected Shortfall (ES … assumption that allows for a simple computation of daily VaR and ES by scaling up their intraday counterparts computed from data … VaR and ES estimates and show that our method outperforms standard ones in accurately estimating and forecasting VaR and …
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these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …-data models at 5% and 1% VaR level. Specifically, independently from the data frequency, allowing for jumps in price (or providing … fat-tails) and leverage effects translates in more accurate VaR measure. …
Persistent link: https://www.econbiz.de/10011674479
forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping … prices and leverage effects for volatility. Findings suggest that GARJI model provides more accurate VaR measures for the S … accurate risk measures even if jump contribution is provided. More sophisticated models might address this issue, improving VaR …
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The aim of this paper is to empirically investigate the in sample and out of sample forecasting performance of several GARCH-type models such as GARCH, EGARCH and APARCH model with Gaussian, student-t, Generalized error distribution (GED), student-t with fixed DOF 10 and GED with fixed parameter...
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