Forecasting increases in the VIX: A time-varying long volatility hedge for equities
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Cited by:
- Fernandes, Marcelo & Medeiros, Marcelo C. & Scharth, Marcel, 2014.
"Modeling and predicting the CBOE market volatility index,"
Journal of Banking & Finance, Elsevier, vol. 40(C), pages 1-10.
- Marcelo Fernandes & Marcelo Cunha Medeiros & MArcelo Scharth, 2007. "Modeling and predicting the CBOE market volatility index," Textos para discussão 548, Department of Economics PUC-Rio (Brazil).
- Fernandes, Marcelo & Medeiros, Marcelo C. & Scharth, Marcel, 2013. "Modeling and predicting the CBOE market volatility index," Textos para discussão 342, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
- Psaradellis, Ioannis & Sermpinis, Georgios, 2016. "Modelling and trading the U.S. implied volatility indices. Evidence from the VIX, VXN and VXD indices," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1268-1283.
- João H. Gonçalves Mazzeu & Helena Veiga & Massimo B. Mariti, 2019.
"Modeling and forecasting the oil volatility index,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 773-787, December.
- Mariti, Massimo B., 2017. "Modeling and forecasting the oil volatility index," DES - Working Papers. Statistics and Econometrics. WS 25985, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Qiao, Gaoxiu & Jiang, Gongyue & Yang, Jiyu, 2022. "VIX term structure forecasting: New evidence based on the realized semi-variances," International Review of Financial Analysis, Elsevier, vol. 82(C).
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More about this item
Keywords
Implied volatility; VIX; hedging; semi-parametric; forecasting;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G00 - Financial Economics - - General - - - General
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