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Idiosyncratic volatility puzzle: influence of macro-finance factors

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Abstract

We analyze the cross-sectional relation between expected idiosyncratic volatility and stock returns. The expected idiosyncratic volatility is conditioned on macro-finance factors as well as traditional asset pricing factors. The macro-finance factors are constructed from a large set of macroeconomic and financial variables. Our results show that the negative relation between expected idiosyncratic volatility and stock returns reverses to a positive one when accounting for the macro-finance effects. Portfolio analysis shows that the positive relation is economically important. The relation between expected idiosyncratic volatility and returns is not affected by business cycle variations. The empirical results are highly robust.

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Notes

  1. The Fama and French (1993) factors are freely available from Kenneth French’ web page.

  2. Note, however, that Ludvigson and Ng (2007) use quarterly data, while our analysis is based on monthly data.

  3. The macro-finance variables are transformed to be stationary by taking logs and first differences as appropriate.

  4. Not all macro-finance variables are available for the entire sample period, but they are included as they become available.

  5. The factors are not strongly correlated (average correlation coefficients are below 0.71), so there are not problems with multicollinearity.

  6. Similarly, Vidal-García et al. (2016) find the idiosyncratic volatility of mutual fund returns using the Fama and French (1993) 3-factor model.

  7. Cakici et al. (2014) also conduct cross-sectional Fama and MacBeth (1973) regressions when investigating the Taiwanese stock market.

  8. Bali et al. (2011) interpret idiosyncratic skewness as lottery preferences. Hur and Luma (2017) also control for idiosyncratic skewness.

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Acknowledgements

The authors are grateful for helpful comments from an anonymous referee as well as from seminar participants at Rady School of Management, University of California San Diego and at the Conference on Computational and Financial Econometrics (CFE 2015) in London. Aslanidis acknowledges support from the Spanish Ministry of Science and Innovation project grant (Reference No. ECO2013-42884-P). Christiansen acknowledges support from CREATES funded by the Danish National Research Foundation (DNRF78) and from the Danish Council for Independent Research, Social Sciences (DFF – 4003-00022).

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Authors and Affiliations

  1. Department d’Economia, CREIP, Universitat Rovira i Virgili, Avinguda Universitat 1, 43204, Reus, Catalonia, Spain

    Nektarios Aslanidis

  2. CREATES, Department of Economics and Business Economics, School of Business and Social Sciences, Aarhus University, Fuglesangs Alle 4, 8210, Aarhus V, Denmark

    Charlotte Christiansen

  3. Lund University, Lund, Sweden

    Charlotte Christiansen

  4. Department of Commerce, Finance and Shipping, Cyprus University of Technology, PO Box 50329, 3603, Limassol, Cyprus

    Neophytos Lambertides & Christos S. Savva

Authors
  1. Nektarios Aslanidis
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  2. Charlotte Christiansen
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  3. Neophytos Lambertides
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  4. Christos S. Savva
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Corresponding author

Correspondence to Charlotte Christiansen.

Appendix

Appendix

See Tables 8 and 9.

Table 8 Macro-finance variables
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Table 9 Descriptive statistics for macro-finance factors
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Aslanidis, N., Christiansen, C., Lambertides, N. et al. Idiosyncratic volatility puzzle: influence of macro-finance factors. Rev Quant Finan Acc 52, 381–401 (2019). https://doi.org/10.1007/s11156-018-0713-x

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  • DOI: https://doi.org/10.1007/s11156-018-0713-x

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