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This paper proposes an improved procedure for stochastic volatility model estimation with an application to Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) estimation. This improved procedure is composed of the following instrumental components: Fourier transform method for volatility...
Persistent link: https://ebvufind01.dmz1.zbw.eu/10013088465
This paper proposes an improved procedure for stochastic volatility model estimation with an application to Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) estimation. This improved procedure is composed of the following instrumental components: Fourier transform method for volatility...
Persistent link: https://ebvufind01.dmz1.zbw.eu/10010883198
Persistent link: https://ebvufind01.dmz1.zbw.eu/10008810127
Persistent link: https://ebvufind01.dmz1.zbw.eu/10003871156
Persistent link: https://ebvufind01.dmz1.zbw.eu/10011685673
Persistent link: https://ebvufind01.dmz1.zbw.eu/10011573571
Persistent link: https://ebvufind01.dmz1.zbw.eu/10014324852
Persistent link: https://ebvufind01.dmz1.zbw.eu/10015047448
Tail risk is a classic topic in stressed portfolio optimization to treat unprecedented risks, while the traditional mean-variance approach may fail to perform well. This study proposes an innovative semiparametric method consisting of two modeling components: the nonparametric estimation and...
Persistent link: https://ebvufind01.dmz1.zbw.eu/10013170237
Persistent link: https://ebvufind01.dmz1.zbw.eu/10006417758