IDEAS home Printed from https://ideas.repec.org/p/udt/wpecon/2025_02.html
   My bibliography  Save this paper

Big swings in the data and perceived changes in the risk premia

Author

Listed:
  • Martín Sola
  • Fabio Spagnolo
  • Francisco Terfi

Abstract

Stock markets experience periods where stocks or market returns are consistently higher than their mean and other periods where the individual stocks and markets’ volatility fluctuates from high to low. Since these periods do not necessarily coincide, a related question is whether periods where individual stock markets are higher than their mean, usually identified as αs different from zero in the conditional regressions, disappear once the researcher accounts for changing states of the economy. In this spirit, we develop and estimate a state-dependent version of the CAPM pricing model that accounts for considerable swings in the data. We use U.S. financial data to assess the model’s validity and find support for a state-dependent version of the CAPM for the data under consideration. We show how important it is to consider changes in stock and market returns and changes in their variance-covariances, and that, when not accounting for changes in market conditions, may spuriously yield significant α values. We stress that to assess changes in the risk premium, we should not only focus on βs but also allow for changes in the market premium; otherwise, changes in risk premia may be over- or underestimated. In addition, the classification between investment opportunities may be mistaken for a single regime model, even when rolling regressions are used.

Suggested Citation

  • Martín Sola & Fabio Spagnolo & Francisco Terfi, 2025. "Big swings in the data and perceived changes in the risk premia," Department of Economics Working Papers 2025_02, Universidad Torcuato Di Tella.
  • Handle: RePEc:udt:wpecon:2025_02
    as

    Download full text from publisher

    File URL: https://www.utdt.edu/download.php?fname=_173100612465108000.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
    2. Luca Brugnolini, 2018. "About Local Projection Impulse Response Function Reliability," CEIS Research Paper 440, Tor Vergata University, CEIS, revised 09 Jun 2018.
    3. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    4. Mikkel Plagborg‐Møller & Christian K. Wolf, 2021. "Local Projections and VARs Estimate the Same Impulse Responses," Econometrica, Econometric Society, vol. 89(2), pages 955-980, March.
    5. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zacharias Psaradakis & Martin Sola & Francisco Rapetti & Patricio Yunis, 2024. "The Role of Consumer Sentiment in the Stock Market: A Multivariate Dynamic Mixture Model with Threshold Effects," Department of Economics Working Papers 2024_01, Universidad Torcuato Di Tella.
    2. Robert Adamek & Stephan Smeekes & Ines Wilms, 2024. "Local projection inference in high dimensions," The Econometrics Journal, Royal Economic Society, vol. 27(3), pages 323-342.
    3. Zohar, Osnat, 2024. "Cyclicality of uncertainty and disagreement," Journal of Monetary Economics, Elsevier, vol. 143(C).
    4. Tafuro, Andrea, 2023. "Labour market rigidity and expansionary austerity," Journal of Macroeconomics, Elsevier, vol. 75(C).
    5. De Santis, Roberto A. & Tornese, Tommaso, 2024. "US monetary policy is more powerful in low economic growth regimes," Working Paper Series 2919, European Central Bank.
    6. Bruns, Martin & Lütkepohl, Helmut, 2022. "Comparison of local projection estimators for proxy vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    7. Bonciani, Dario, 2015. "Estimating the effects of uncertainty over the business cycle," MPRA Paper 65921, University Library of Munich, Germany.
    8. Senni, Chiara Colesanti & von Jagow, Adrian, 2023. "Water risks for hydroelectricity generation," LSE Research Online Documents on Economics 119256, London School of Economics and Political Science, LSE Library.
    9. Luisa Corrado & Daniela Fantozzi, 2021. "Micro level data for macro models: the distributional effects of monetary policy," National Institute of Economic and Social Research (NIESR) Discussion Papers 529, National Institute of Economic and Social Research.
    10. Pablo Aguilar Perez, 2024. "Global Spillovers of US Monetary Policy: New Insights from the Remittance Channel," Working Papers hal-04706954, HAL.
    11. Javier J. Perez & Ana Lamo & Enrique Moral-Benito, 2015. "Does Slack Influence Public and Private Labor Market," EcoMod2015 8792, EcoMod.
    12. Atsushi Inoue & `Oscar Jord`a & Guido M. Kuersteiner, 2023. "Inference for Local Projections," Papers 2306.03073, arXiv.org, revised Aug 2024.
    13. Li, Dake & Plagborg-Møller, Mikkel & Wolf, Christian K., 2024. "Local projections vs. VARs: Lessons from thousands of DGPs," Journal of Econometrics, Elsevier, vol. 244(2).
    14. Pascal Goemans, 2022. "Historical evidence for larger government spending multipliers in uncertain times than in slumps," Economic Inquiry, Western Economic Association International, vol. 60(3), pages 1164-1185, July.
    15. Jonas E. Arias & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2021. "Bayesian Estimation of Epidemiological Models: Methods, Causality, and Policy Trade-Offs," CESifo Working Paper Series 8977, CESifo.
    16. Wataru Miyamoto & Thuy Lan Nguyen & Dmitriy Sergeyev, 2018. "Government Spending Multipliers under the Zero Lower Bound: Evidence from Japan," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(3), pages 247-277, July.
    17. Alexander Chudik & Georgios Georgiadis, 2022. "Estimation of Impulse Response Functions When Shocks Are Observed at a Higher Frequency Than Outcome Variables," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 965-979, June.
    18. Clements, Michael P & Smith, Jeremy, 1999. "A Monte Carlo Study of the Forecasting Performance of Empirical SETAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 123-141, March-Apr.
    19. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87, September.
    20. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.

    More about this item

    Keywords

    Non-diversifiable Risk Premium; Markov Chain; Structural Breaks.;
    All these keywords.

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:udt:wpecon:2025_02. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: María Cecilia Lafuente (email available below). General contact details of provider: https://edirc.repec.org/data/deutdar.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.