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Applying Exogenous Variables and Regime Switching To Multifactor Models on Equity Indices

Author

Listed:
  • Paweł Sakowski

    (Faculty of Economic Sciences, University of Warsaw)

  • Robert Ślepaczuk

    (Faculty of Economic Sciences, University of Warsaw; Union Investment TFI S.A.)

  • Mateusz Wywiał

    (Faculty of Economic Sciences, University of Warsaw; Quedex Derivatives Exchange)

Abstract

This article aims to extend the evaluation of classic multifactor models of Carhart(1997) for the case of global equity indices and to expand analysis performed in Sakowski, Slepaczuk, and Wywial (2015). Our intention is to test several modifications of these models to take into account different dynamics of equity excess returns between emerging and developed equity indices. Proposed extensions include volatility regime switching mechanism (using dummy variables and the Markov approach) and three new risk factors based on realized volatility of index returns, percentage deviation from nominal GDP trend and capitalisation relative to GDP factor. Additional modifications include introduction of common and country specific variables in order to control for global risk where fluctuations of volatility of various assets, prices of commodities, currencies and rates is really important. Moreover, instead of using data for individual stocks (which is a common approach in the literature), we evaluate the performance of these models for weekly data of 81 world investable equity indices in the period of 2000-2015. Such approach is proposed to estimate equity risk premium for a single country. Empirical evidence from the first part reveals important differences between results for classical models estimated on single stocks (either in international or US-only frame work) and models evaluated for equity indices. Additionally, we observe substantial discrepancies between results for developed countries and emerging markets. The last part of this research helps us to understand results revealed in the first part. Thanks to introduction of new risk factors, and additional common and country specific variables we were able to increase explanatory power of our factor models especially in case of emerging market indices. Finally, using weekly data for the last 15 years we illustrate importance of model risk and data overfitting effects when drawing conclusions upon results of multifactor models.

Suggested Citation

  • Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Applying Exogenous Variables and Regime Switching To Multifactor Models on Equity Indices," Working Papers 2016-10, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2016-10
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    References listed on IDEAS

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    1. Ruzita Abdul Rahim & Abu Hassan Shaari Mohd. Nor, 2006. "A Comparison Between Fama and French Model and Liquidity-Based Three Factor Models in Predicting Portfolio Returns," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 2(2), pages 43-60.
    2. James L. Davis & Eugene F. Fama & Kenneth R. French, 2000. "Characteristics, Covariances, and Average Returns: 1929 to 1997," Journal of Finance, American Finance Association, vol. 55(1), pages 389-406, February.
    3. Frazzini, Andrea & Pedersen, Lasse Heje, 2014. "Betting against beta," Journal of Financial Economics, Elsevier, vol. 111(1), pages 1-25.
    4. John M. Griffin, 2002. "Are the Fama and French Factors Global or Country Specific?," The Review of Financial Studies, Society for Financial Studies, vol. 15(3), pages 783-803.
    5. Michael Donadelli & Lorenzo Prosperi, 2012. "The Equity Risk Premium: Empirical Evidence from Emerging Markets," Working Papers CASMEF 1201, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    6. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    7. Cakici, Nusret & Fabozzi, Frank J. & Tan, Sinan, 2013. "Size, value, and momentum in emerging market stock returns," Emerging Markets Review, Elsevier, vol. 16(C), pages 46-65.
    8. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W, 1994. "Contrarian Investment, Extrapolation, and Risk," Journal of Finance, American Finance Association, vol. 49(5), pages 1541-1578, December.
    9. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    10. Timotheos Angelidis & Nikolaos Tessaromatis, 2014. "Global portfolio management under state dependent multiple risk premia," Proceedings of Economics and Finance Conferences 0400966, International Institute of Social and Economic Sciences.
    11. Fernando M. Duarte & Carlo Rosa, 2015. "The equity risk premium: a review of models," Economic Policy Review, Federal Reserve Bank of New York, issue 2, pages 39-57.
    12. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    13. Wu, Xueping, 2002. "A conditional multifactor analysis of return momentum," Journal of Banking & Finance, Elsevier, vol. 26(8), pages 1675-1696, August.
    14. Kewei Hou & G. Andrew Karolyi & Bong-Chan Kho, 2011. "What Factors Drive Global Stock Returns?," The Review of Financial Studies, Society for Financial Studies, vol. 24(8), pages 2527-2574.
    15. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    16. Connor, Gregory & Sehgal, Sanjay, 2001. "Tests of the Fama and French model in India," LSE Research Online Documents on Economics 25057, London School of Economics and Political Science, LSE Library.
    17. Manuel Ammann & Michael Verhofen, 2006. "The Effect of Market Regimes on Style Allocation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(3), pages 309-337, September.
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    Cited by:

    1. Paweł Sakowski & Robert Ślepaczuk & Mateusz Wywiał, 2016. "Can We Invest Based on Equity Risk Premia and Risk Factors from Multi-Factor Models?," Working Papers 2016-09, Faculty of Economic Sciences, University of Warsaw.

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    More about this item

    Keywords

    multi-factor models; asset pricing models; equity risk premia; equity indices; new risk factors; sensitivity analysis; book to market; momentum; market price of risk; emerging and developed equity indices;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • F30 - International Economics - - International Finance - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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