IDEAS home Printed from https://ideas.repec.org/p/cem/doctra/659.html
   My bibliography  Save this paper

Measuring and trading volatility on the US stock market: A regime switching approach

Author

Listed:
  • José P. Dapena
  • Juan A. Serur
  • Julián R. Siri

Abstract

The volatility premium is a well-documented phenomenon, which can be approximated by the difference between the previous month level of the VIX Index and the rolling 30-day close-to-close volatility. Along with the literature, we show evidence that VIX is generally above the 30-day rolling volatility giving rise to the volatility premium, so selling volatility can become a profitable trading strategy as long as proper risk management is under place. As a contribution, we introduced the implementation of a Hidden Markov Model (HMM), identifying two states of the nature and showing that the volatility premium undergoes temporal breaks in its behavior. Based on this, we formulate a trading strategy by selling volatility and switching to medium-term U.S. Treasury Bills when appropriated. We test the performance of the strategy using the conventional Carhart four-factor model showing a positive and statistically significant alpha.

Suggested Citation

  • José P. Dapena & Juan A. Serur & Julián R. Siri, 2018. "Measuring and trading volatility on the US stock market: A regime switching approach," CEMA Working Papers: Serie Documentos de Trabajo. 659, Universidad del CEMA.
    • Handle: RePEc:cem:doctra:659
    as

    Download full text from publisher

    File URL: https://ucema.edu.ar/publicaciones/download/documentos/659.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. José P. Dapena & Julian R. Siri, 2015. "Index options realized returns distributions from passive investment strategies," CEMA Working Papers: Serie Documentos de Trabajo. 580, Universidad del CEMA.
    2. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    3. Psaradakis, Zacharias & Sola, Martin, 1998. "Finite-sample properties of the maximum likelihood estimator in autoregressive models with Markov switching," Journal of Econometrics, Elsevier, vol. 86(2), pages 369-386, June.
    4. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor, 2015. "The risk premia embedded in index options," Journal of Financial Economics, Elsevier, vol. 117(3), pages 558-584.
    5. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. "Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
    6. Fama, Eugene F. & French, Kenneth R., 2012. "Size, value, and momentum in international stock returns," Journal of Financial Economics, Elsevier, vol. 105(3), pages 457-472.
    7. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    8. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    9. Kraus, Alan & Litzenberger, Robert H, 1976. "Skewness Preference and the Valuation of Risk Assets," Journal of Finance, American Finance Association, vol. 31(4), pages 1085-1100, September.
    10. Roman Kozhan & Anthony Neuberger & Paul Schneider, 2013. "The Skew Risk Premium in the Equity Index Market," Review of Financial Studies, Society for Financial Studies, vol. 26(9), pages 2174-2203.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. José P. Dapena & Juan A. Serur & Julián R. Siri, 2019. "Risk on-Risk off: A regime switching model for active portfolio management," CEMA Working Papers: Serie Documentos de Trabajo. 706, Universidad del CEMA.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Paul Schneider & Christian Wagner & Josef Zechner, 2020. "Low‐Risk Anomalies?," Journal of Finance, American Finance Association, vol. 75(5), pages 2673-2718, October.
    2. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, June.
    3. Scott Condie & Lars Stentoft & Marie-Louise Vierø, 2023. "Unawareness Premia," Economics Working Papers 2023-09, Department of Economics and Business Economics, Aarhus University.
    4. Victoria Dobrynskaya, 2017. "Dynamic Momentum and Contrarian Trading," HSE Working papers WP BRP 61/FE/2017, National Research University Higher School of Economics.
    5. Bressan, Silvia & Weissensteiner, Alex, 2021. "The financial conglomerate discount: Insights from stock return skewness," International Review of Financial Analysis, Elsevier, vol. 74(C).
    6. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2018. "Crash Sensitivity and the Cross Section of Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1059-1100, June.
    7. Dobrynskaya, Victoria, 2019. "Avoiding momentum crashes: Dynamic momentum and contrarian trading," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    8. Christoffersen, Peter & Fournier, Mathieu & Jacobs, Kris & Karoui, Mehdi, 2021. "Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(1), pages 65-91, February.
    9. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    10. Langlois, Hugues, 2020. "Measuring skewness premia," Journal of Financial Economics, Elsevier, vol. 135(2), pages 399-424.
    11. Lin, Chaonan & Chen, Hong-Yi & Ko, Kuan-Cheng & Yang, Nien-Tzu, 2021. "Time-dependent lottery preference and the cross-section of stock returns," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 272-294.
    12. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    13. Elyasiani, Elyas & Gambarelli, Luca & Muzzioli, Silvia, 2020. "Moment risk premia and the cross-section of stock returns in the European stock market," Journal of Banking & Finance, Elsevier, vol. 111(C).
    14. Harris, Richard D.F. & Nguyen, Linh H. & Stoja, Evarist, 2019. "Systematic extreme downside risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 128-142.
    15. Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "International tail risk and World Fear," Journal of International Money and Finance, Elsevier, vol. 93(C), pages 244-259.
    16. DeMiguel, Victor & Plyakha, Yuliya & Uppal, Raman & Vilkov, Grigory, 2013. "Improving Portfolio Selection Using Option-Implied Volatility and Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(6), pages 1813-1845, December.
    17. Sangwon Suh & Eungyu Yoo & Sun‐Joong Yoon, 2021. "Stock market tail risk, tail risk premia, and return predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1569-1596, October.
    18. Ayadi, Mohamed A. & Cao, Xu & Lazrak, Skander & Wang, Yan, 2019. "Do idiosyncratic skewness and kurtosis really matter?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    19. Sirio Aramonte & Mohammad R. Jahan-Parvar & Samuel Rosen & John W. Schindler, 2022. "Firm-Specific Risk-Neutral Distributions with Options and CDS," Management Science, INFORMS, vol. 68(9), pages 7018-7033, September.
    20. Reboredo, Juan C. & Ugolini, Andrea, 2022. "Climate transition risk, profitability and stock prices," International Review of Financial Analysis, Elsevier, vol. 83(C).

    More about this item

    Keywords

    Realized volatility; expected volatility; volatility premium; regime switching; excess returns; hidden Markov model; VIX.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • N2 - Economic History - - Financial Markets and Institutions
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cem:doctra:659. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Valeria Dowding (email available below). General contact details of provider: https://edirc.repec.org/data/cemaaar.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.