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Do fear indices help predict stock returns?

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  • G. Rubbaniy
  • Robel Asmerom
  • Syed Kumail Abbas Rizvi
  • Bushra Naqvi

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  • G. Rubbaniy & Robel Asmerom & Syed Kumail Abbas Rizvi & Bushra Naqvi, 2014. "Do fear indices help predict stock returns?," Quantitative Finance, Taylor & Francis Journals, vol. 14(5), pages 831-847, May.
    • Handle: RePEc:taf:quantf:v:14:y:2014:i:5:p:831-847
    DOI: 10.1080/14697688.2014.884722
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    Citations

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    Cited by:

    1. Ding, Wenjie & Mazouz, Khelifa & Wang, Qingwei, 2021. "Volatility timing, sentiment, and the short-term profitability of VIX-based cross-sectional trading strategies," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 42-56.
    2. Haase, Felix & Neuenkirch, Matthias, 2023. "Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US," International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
    3. Elyas Elyasani & Luca Gambarelli & Silvia Muzzioli, 2016. "The risk asymmetry index," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0061, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    4. Just, Małgorzata & Echaust, Krzysztof, 2020. "Stock market returns, volatility, correlation and liquidity during the COVID-19 crisis: Evidence from the Markov switching approach," Finance Research Letters, Elsevier, vol. 37(C).
    5. Fabio Bellini & Edit Rroji & Carlo Sala, 2022. "Implicit quantiles and expectiles," Annals of Operations Research, Springer, vol. 313(2), pages 733-753, June.
    6. Emmanuel Anoruo & Vasudeva N. R. Murthy, 2017. "An examination of the REIT return–implied volatility relation: a frequency domain approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(3), pages 581-594, July.
    7. Campisi, Giovanni & Muzzioli, Silvia & De Baets, Bernard, 2024. "A comparison of machine learning methods for predicting the direction of the US stock market on the basis of volatility indices," International Journal of Forecasting, Elsevier, vol. 40(3), pages 869-880.
    8. Luca Gambarelli & Silvia Muzzioli, 2019. "Risk-asymmetry indices in Europe," Department of Economics 0157, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    9. Elyas Elyasiani & Luca Gambarelli & Silvia Muzzioli, 2018. "The Risk-Asymmetry Index as a new Measure of Risk," Multinational Finance Journal, Multinational Finance Journal, vol. 22(3-4), pages 173-210, September.
    10. Jia‐Yen Huang & Jin‐Hao Liu, 2020. "Using social media mining technology to improve stock price forecast accuracy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 104-116, January.
    11. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    12. Elyas Elyasani & Luca Gambarelli & Silvia Muzzioli, 2016. "The risk asymmetry index," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 16212, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    13. Escobar, Marcos & Fang, Lin, 2020. "Stochastic volatility models for the implied correlation index," Finance Research Letters, Elsevier, vol. 35(C).
    14. Giovanni Campisi & Silvia Muzzioli, 2021. "Designing volatility indices for Austria, Finland and Spain," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 369-455, September.
    15. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.
    16. John Griffith & Mohammad Najand & Jiancheng Shen, 2020. "Emotions in the Stock Market," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 21(1), pages 42-56, January.

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