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Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction
Liao, Yin - 2012
Recent literature has focuses on realized volatility models to predict financial risk. This paper studies the benefit … volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based … on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility …
Persistent link: https://www.econbiz.de/10013105658
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Large mixed-frequency VARs with a parsimonious time-varying parameter structure
Götz, Thomas B.; Hauzenberger, Klemens - 2018
To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...
Persistent link: https://www.econbiz.de/10011903709
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Estimating the value-at-risk from high-frequency data
Krasnovský, Pavol - In: European financial and accounting journal : EFAJ 10 (2015) 2, pp. 5-11
Persistent link: https://www.econbiz.de/10011471021
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Fat-tails in VAR models
Chiu, Ching Wai Jeremy; Mumtaz, Haroon; Pinter, Gabor - 2014
volatility and Student-t disturbances outperforms restricted alternatives that feature either attributes. The VAR model with …
Persistent link: https://www.econbiz.de/10010339759
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A stochastic dominance approach to the Basel III dilemma : expected shortfall or VaR?
Chang, Chia-Lin; Jiménez-Martín, Juan-Ángel; … - 2015
The Basel Committee on Banking Supervision (BCBS) (2013) recently proposed shifting the quantitative risk metrics system from Value-at-Risk (VaR) to Expected Shortfall (ES). The BCBS (2013) noted that - a number of weaknesses have been identified with using VaR for determining regulatory capital...
Persistent link: https://www.econbiz.de/10010532611
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Score driven exponentially weighted moving average and value-at-risk forecasting
Lucas, André; Zhang, Xin - 2014
dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model … volatility forecasting of stock returns and exchange rates. …
Persistent link: https://www.econbiz.de/10010384110
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Score driven exponentially weighted moving averages and value-at-risk forecasting
Lucas, André; Zhang, Xin - 2015
volatility of individual stock returns and exchange rate returns. …
Persistent link: https://www.econbiz.de/10011332948
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Forecasting value-at-risk with time-varying variance, skewnessn and kurtosis in an exponential weighted moving average framework
Gabrielsen, Alexandros; Zagaglia, Paolo; Kirchner, Axel; … - 2012 - This version: June 6, 2012
by proposing an exponential weighted moving average model that jointly estimates volatility, skewness and kurtosis over …
Persistent link: https://www.econbiz.de/10011731521
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Forecasting Value-at-Risk and Expected Shortfall of Cryptocurrencies using Combinations based on Jump-Robust and Regime-Switching Models
Trucíos, Carlos; Taylor, James W. - 2021
more than a single regime, have performed substantially better than standard methods in terms of volatility and Value …
Persistent link: https://www.econbiz.de/10013242299
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Computation of Portfolio VaRs with GARCH-Type Volatility
Xu, Dinghai - 2013
In this paper, we explore the use of Independent Component Analysis (ICA) from the field of signal processing to model and estimate the dynamics of multivariate volatilities of financial asset returns in the GARCH framework. The resulting ICA-GARCH approach is shown to provide a computationally...
Persistent link: https://www.econbiz.de/10013084060