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Analysis of Equity Beta Components: New Results and Prospectives in a Low Beta Framework

Author

Listed:
  • Antonio Amendola
  • Dennis M. Montagna
  • Mario Maggi

    (University of Pavia
    University of Pavia
    University of Pavia)

Abstract

This work aims to exploit the so-called 'Beta anomaly' regarding the risk-reward relationship, and set up rules and methodologies in order to build new efficient portfolios. It is well known in literature, and among practitioners, that 'Low Beta strategies' generate good performances exploiting alpha opportunities. In this paper, we focus on Beta parameters: we analyze this one and its components (Correlation and Standard Deviation) in order to better understand the drivers and contributions behind the 'Low Beta strategies', and eventually exploit them. We perform an extensive empirical analysis on the S&P500 and the relative sectors, covering more than 10 years. In addition, we follow Long/Short strategies in building portfolios based on Beta and their components where we compare results against the benchmark. We also introduce 'Walking Beta' approach in order to give a deep and innovative view on the market risk/reward relationship, illustrating different time frames and the evolution of risk parameters.

Suggested Citation

  • Antonio Amendola & Dennis M. Montagna & Mario Maggi, 2019. "Analysis of Equity Beta Components: New Results and Prospectives in a Low Beta Framework," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 3(1), pages 1-26.
    • Handle: RePEc:trp:01jefa:jefa0021
    DOI: http://dx.doi.org/10.1991/jefa.v3i1.a21
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    References listed on IDEAS

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    1. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    2. Ang, Andrew & Hodrick, Robert J. & Xing, Yuhang & Zhang, Xiaoyan, 2009. "High idiosyncratic volatility and low returns: International and further U.S. evidence," Journal of Financial Economics, Elsevier, vol. 91(1), pages 1-23, January.
    3. Frazzini, Andrea & Pedersen, Lasse Heje, 2014. "Betting against beta," Journal of Financial Economics, Elsevier, vol. 111(1), pages 1-25.
    4. Malcolm Baker & Mathias F. Hoeyer & Jeffrey Wurgler, 2016. "The Risk Anomaly Tradeoff of Leverage," NBER Working Papers 22116, National Bureau of Economic Research, Inc.
    5. Eugene F. Fama & Kenneth R. French, 2004. "The Capital Asset Pricing Model: Theory and Evidence," Journal of Economic Perspectives, American Economic Association, vol. 18(3), pages 25-46, Summer.
    6. repec:bla:jfinan:v:58:y:2003:i:4:p:1651-1684 is not listed on IDEAS
    7. Blitz, D.C. & van Vliet, P., 2007. "The Volatility Effect: Lower Risk without Lower Return," ERIM Report Series Research in Management ERS-2007-044-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    More about this item

    Keywords

    Asset Allocation; Quantitative Portfolio Management; CAPM; Hedge Funds; Correlation; Beta Anomaly.;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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