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Risk on-Risk off: A regime switching model for active portfolio management

Author

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

Abstract

Unlike passive management, where investors almost do not buy and sell securities, active management involves a set of trading rules that govern investment decisions regarding mainly market timing. In this paper, we take the basics of active management and the two fund separation approach, to exploit the fact that an investor can switch between the market portfolio and the risk free asset according to the perceived state of the nature. Our purpose is to evaluate if there is an active management premium by testing performance with our own non-conventional multifactor model, constructed with a Hidden Markov Model which depending on the market states signaled by the level of volatility spread. We have documented that effectively, there is present a premium for actively manage the strategies, giving evidence against the idea that “active managers” destroy capital. We then propose the volatility spread as the active management factor into the Carhart´s model used to evaluate trading strategies with respect to a benchmark portfolio.

Suggested Citation

  • 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.
    • Handle: RePEc:cem:doctra:706
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    File URL: https://ucema.edu.ar/publicaciones/download/documentos/706.pdf
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    References listed on IDEAS

    as
    1. Kenneth R. French, 2008. "Presidential Address: The Cost of Active Investing," Journal of Finance, American Finance Association, vol. 63(4), pages 1537-1573, August.
    2. 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.
    3. Alexander Dyck & Karl V. Lins & Lukasz Pomorski, 2013. "Does Active Management Pay? New International Evidence," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 3(2), pages 200-228.
    4. 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.
    5. 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.
    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. Eugene F. Fama & Kenneth R. French, 2010. "Luck versus Skill in the Cross‐Section of Mutual Fund Returns," Journal of Finance, American Finance Association, vol. 65(5), pages 1915-1947, October.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Matthew Wang & Yi-Hong Lin & Ilya Mikhelson, 2020. "Regime-Switching Factor Investing with Hidden Markov Models," JRFM, MDPI, vol. 13(12), pages 1-15, December.

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    More about this item

    Keywords

    Regime switching; active investment; two fund separation; 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

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