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Insights on the global macro-finance interface: Structural sources of risk factors fluctuations and the cross-section of expected stock returns

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  • Claudio Morana

Abstract

This study contributes to the investigation of the macro-finance interface by assessing the economic content and risk based interpretation of widely employed risk factors in the specification of empirical asset pricing models, i.e., Fama-French size and value, and Carhart momentum factors, as well as the more recent Pastor-Stambaugh liquidity and Adrian-Etula-Muir leverage factors. Strong support for their risk based interpretation, encompassing evidence on causes, persistence and direction of the size, value and momentum effects, and new insights on the specification of systematic risk, are provided.

Suggested Citation

  • Claudio Morana, 2013. "Insights on the global macro-finance interface: Structural sources of risk factors fluctuations and the cross-section of expected stock returns," Working Papers 264, University of Milano-Bicocca, Department of Economics, revised Dec 2013.
    • Handle: RePEc:mib:wpaper:264
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    Cited by:

    1. Kim, Kun Ho, 2014. "Counter-cyclical risk aversion," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 384-401.
    2. Claudio, Morana, 2015. "The US$/€ exchange rate: Structural modeling and forecasting during the recent financial crises," Working Papers 321, University of Milano-Bicocca, Department of Economics, revised 28 Dec 2015.
    3. Nuno Cassola & Claudio Morana & Elisa Ossola, 2023. "Green risk in Europe," Working Paper series 23-14, Rimini Centre for Economic Analysis.
    4. Massimo Guidolin & Erwin Hansen & Martín Lozano-Banda, 2018. "Portfolio performance of linear SDF models: an out-of-sample assessment," Quantitative Finance, Taylor & Francis Journals, vol. 18(8), pages 1425-1436, August.
    5. Nuno Cassola & Claudio Morana & Elisa Ossola, 2023. "Green risk in Europe," Working Paper series 23-14, Rimini Centre for Economic Analysis.
    6. Kim, Jae H. & Ji, Philip Inyeob, 2015. "Significance testing in empirical finance: A critical review and assessment," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 1-14.
    7. Morana, Claudio, 2017. "Macroeconomic and financial effects of oil price shocks: Evidence for the euro area," Economic Modelling, Elsevier, vol. 64(C), pages 82-96.
    8. Zaafri A. Husodo & M. Budi Prasetyo & Rizky Luxianto & Theresia Silitonga & Januar Hafidz & M. Harris Muhajir & Inna Firindra, 2018. "Mispricing And Risk Taking In The Indonesian Stock Market," Working Papers WP/28/2018, Bank Indonesia.
    9. Wickens, Michael R., 2014. "How did we get to where we are now? Reflections on 50 years of macroeconomic and financial econometrics," CEPR Discussion Papers 10197, C.E.P.R. Discussion Papers.
    10. Jardine A. Husman & Ali Sakti & Dahnila Dahlan & Imam Wahyudi Indrawan & Zaäfri A. Husodo & Nur Dhani Hendranastiti & Muhammad Budi Prasetyo & Wahyu Jatmiko, 2022. "On The Development Of The Islamic Benchmark Rate: An Indonesian Case," Working Papers WP/04/2022, Bank Indonesia.
    11. Michael Wickens, 2015. "How Did We Get to Where We Are Now? Reflections on 50 Years of Macroeconomic and Financial Econometrics," Manchester School, University of Manchester, vol. 83, pages 60-82, December.
    12. Filippo Lechthaler & Lisa Leinert, 2019. "Moody oil: What is driving the crude oil price?," Empirical Economics, Springer, vol. 57(5), pages 1547-1578, November.

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    More about this item

    Keywords

    macro-…nance interface; risk factors; size; value; momentum liquidity and leverage effects; factor vector autoregressive model;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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