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Variance Premium and Implied Volatility in a Low-Liquidity Option Market

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  • Eduardo Astorino
  • Fernando Chague, Bruno Cara Giovannetti, Marcos Eugênio da Silva

Abstract

We propose an implied volatility index for Brazil that we name "IVol-BR". The index is based on daily market prices of options over IBOVESPA -- an option market with relatively low liquidity and few option strikes. Our methodology combines standard international methodology used in high-liquidity markets with adjustments that take into account the low liquidity in Brazilian option markets. We then do a number of empirical tests to validate the IVol-BR. First, we show that the IVol-BR has significant predictive power over future volatility of equity returns not contained in traditional volatility forecasting variables. Second, we decompose the squared IVol-BR into (i) the expected variance of stock returns and (ii) the equity variance premium. This decomposition is of interest since the equity variance premium directly relates to the representative investor risk aversion. Finally, assuming Bollerslev et al. (2009) functional form, we produce a time-varying risk aversion measure for the Brazilian investor. We empirically show that risk aversion is positively related to expected returns, as theory suggests.

Suggested Citation

  • Eduardo Astorino & Fernando Chague, Bruno Cara Giovannetti, Marcos Eugênio da Silva, 2015. "Variance Premium and Implied Volatility in a Low-Liquidity Option Market," Working Papers, Department of Economics 2015_08, University of São Paulo (FEA-USP).
  • Handle: RePEc:spa:wpaper:2015wpecon8
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    References listed on IDEAS

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    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    2. Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
    3. Havranek, Tomas & Horvath, Roman & Irsova, Zuzana & Rusnak, Marek, 2015. "Cross-country heterogeneity in intertemporal substitution," Journal of International Economics, Elsevier, vol. 96(1), pages 100-118.
    4. José Renato Haas Ornelas & José Santiago Fajardo Barbachan & Aquiles Rocha de Farias, 2012. "Estimating Relative Risk Aversion, Risk-Neutral and Real-World Densities using Brazilian Real Currency Options," Working Papers Series 269, Central Bank of Brazil, Research Department.
    5. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    6. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
    7. Issler, João Victor & Piqueira, Natalia Scotto, 2000. "Estimating Relative Risk Aversion, the Discount Rate, and the Intertemporal Elasticity of Substitution in Consumption for Brazil Using Three Types of Utility Function," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 20(2), November.
    8. Peter Carr & Liuren Wu, 2009. "Variance Risk Premiums," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1311-1341, March.
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    Cited by:

    1. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    2. Fassas, Athanasios P. & Siriopoulos, Costas, 2021. "Implied volatility indices – A review," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 303-329.
    3. Ramos, Henrique P. & Perlin, Marcelo S. & Righi, Marcelo B., 2017. "Mispricing in the odd lots market in Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 618-628.
    4. Fernando Chague & Rodrigo De-Losso, Alan De Genaro, Bruno Giovannetti, 2015. "Why Do Different Short-sellers Pay Different Loan Fees? A Market-wide Analysis," Working Papers, Department of Economics 2015_17, University of São Paulo (FEA-USP).

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    More about this item

    Keywords

    IVol-BR; Variance Risk Premium; Risk-aversion;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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