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How common are common return factors across the NYSE and Nasdaq?

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  • Goyal, Amit
  • Pérignon, Christophe
  • Villa, Christophe

Abstract

We entertain the possibility of pervasive factors that are not common across two (or more) groups of securities. We propose and implement a general procedure to estimate the space spanned by common and group-specific pervasive factors. In our empirical analysis, we study the factor structure of excess returns on stocks traded on the NYSE and Nasdaq using our methodology. We find that there are only two common pervasive factors that govern the returns for both NYSE and Nasdaq. At the same time, the NYSE and Nasdaq each have one more group-specific factor that is not the same across the two exchanges. Our results point to the absence of complete similarity between the factors driving the returns on these exchanges.

Suggested Citation

  • Goyal, Amit & Pérignon, Christophe & Villa, Christophe, 2008. "How common are common return factors across the NYSE and Nasdaq?," Journal of Financial Economics, Elsevier, vol. 90(3), pages 252-271, December.
  • Handle: RePEc:eee:jfinec:v:90:y:2008:i:3:p:252-271
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    References listed on IDEAS

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    Cited by:

    1. Zura Kakushadze, 2015. "Heterotic Risk Models," Papers 1508.04883, arXiv.org, revised Jan 2016.
    2. Bai, Jushan & Ando, Tomohiro, 2013. "Multifactor asset pricing with a large number of observable risk factors and unobservable common and group-specific factors," MPRA Paper 52785, University Library of Munich, Germany, revised Dec 2013.
    3. Don H Kim & Mico Loretan & Eli M Remolona, 2010. "Contagion and risk premia in the amplification of crisis: evidence from Asian names in the global CDS market," BIS Papers chapters,in: Bank for International Settlements (ed.), The international financial crisis and policy challenges in Asia and the Pacific, volume 52, pages 318-339 Bank for International Settlements.
    4. Juneja, Januj, 2012. "Common factors, principal components analysis, and the term structure of interest rates," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 48-56.
    5. Lin, Jianhao & Wang, Meijin & Cai, Lingfeng, 2012. "Are the Fama–French factors good proxies for latent risk factors? Evidence from the data of SHSE in China," Economics Letters, Elsevier, vol. 116(2), pages 265-268.
    6. Zura Kakushadze & Willie Yu, 2016. "Statistical Risk Models," Papers 1602.08070, arXiv.org, revised Jan 2017.
    7. Heaton, Chris & Solo, Victor, 2012. "Estimation of high-dimensional linear factor models with grouped variables," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 348-367.
    8. Chen, Pu, 2010. "A Grouped Factor Model," MPRA Paper 28083, University Library of Munich, Germany, revised 11 Jan 2011.
    9. Zura Kakushadze & Willie Yu, 2016. "Multifactor Risk Models and Heterotic CAPM," Papers 1602.04902, arXiv.org, revised Mar 2016.

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