IDEAS home Printed from https://ideas.repec.org/a/bla/manchs/v81y2013ip100-124.html
   My bibliography  Save this article

Equity Returns and the Business Cycle: the Role of Supply and Demand Shocks

Author

Listed:
  • Alfonso Mendoza Velázquez
  • Peter N. Smith

Abstract

The equity premium in the UK appears to have risen significantly since the start of the financial crisis and the associated extended recession. This paper examines the relationship between the business cycle and equity market returns to see how robust this association is. Several classifications of UK business cycle quarters are examined and related to the returns from an investment strategy which buys the market one or more quarters after a business cycle quarter and holds it for one year. Official business cycle dating methods as well as identified structural macroeconomic shocks are examined. The findings are that there is clear evidence for counter-cyclicality in excess returns. Returns are significantly higher in the year following a recession rather than an expansion quarter. There is also a significant difference in the pattern of returns if the downturn in the quarter is the result of a supply or demand shock. Negative supply shocks are found to have an especially large and significant counter cyclical impact on returns. This paper analyses a long period of UK data for determining realised returns using revised data as well as expected returns using a shorter dataset of real-time data. The paper finds similar results for the two datasets suggesting that realsied and expected returns may not be so different from one another. The paper also assesses the ability of the models to forecast outside of their sample period.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Alfonso Mendoza Velázquez & Peter N. Smith, 2013. "Equity Returns and the Business Cycle: the Role of Supply and Demand Shocks," Manchester School, University of Manchester, vol. 81, pages 100-124, September.
    • Handle: RePEc:bla:manchs:v:81:y:2013:i::p:100-124
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/manc.12022
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Thomas J. Sargent & Mark W. Watson, 2007. "ABCs (and Ds) of Understanding VARs," American Economic Review, American Economic Association, vol. 97(3), pages 1021-1026, June.
    4. Ilan Cooper, 2009. "Time-Varying Risk Premiums and the Output Gap," The Review of Financial Studies, Society for Financial Studies, vol. 22(7), pages 2601-2633, July.
    5. Peter N. Smith & Steffen Sorensen & Michael Wickens, 2010. "The equity premium and the business cycle: the role of demand and supply shocks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(2), pages 134-152.
    6. Bullard, James & Keating, John W., 1995. "The long-run relationship between inflation and output in postwar economies," Journal of Monetary Economics, Elsevier, vol. 36(3), pages 477-496, December.
    7. Blanchard, Olivier Jean & Quah, Danny, 1993. "The Dynamic Effects of Aggregate Demand and Supply Disturbances: Reply," American Economic Review, American Economic Association, vol. 83(3), pages 653-658, June.
    8. Rangvid, Jesper, 2006. "Output and expected returns," Journal of Financial Economics, Elsevier, vol. 81(3), pages 595-624, September.
    9. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    10. Clark, Todd E. & McCracken, Michael W., 2009. "Tests of Equal Predictive Ability With Real-Time Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 441-454.
    11. Andrew Ang & Sen Dong & Monika Piazzesi, 2005. "No-arbitrage Taylor rules," Proceedings, Federal Reserve Bank of San Francisco.
    12. Iryna Kaminska, 2013. "A No-Arbitrage Structural Vector Autoregressive Model of the UK Yield Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(5), pages 680-704, October.
    13. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1, National Bureau of Economic Research, Inc.
    14. Rodriguez, Rosa & Restoy, Fernando & Pena, J. Ignacio, 2002. "Can output explain the predictability and volatility of stock returns?," Journal of International Money and Finance, Elsevier, vol. 21(2), pages 163-182, April.
    15. Keating, John W & Nye, John V, 1998. "Permanent and Transitory Shocks in Real Output: Estimates from Nineteenth-Century and Postwar Economies," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 30(2), pages 231-251, May.
    16. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
    17. Lippi, Marco & Reichlin, Lucrezia, 1993. "The Dynamic Effects of Aggregate Demand and Supply Disturbances: Comment," American Economic Review, American Economic Association, vol. 83(3), pages 644-652, June.
    18. Anthony Garratt & Shaun P Vahey, 2006. "UK Real-Time Macro Data Characteristics," Economic Journal, Royal Economic Society, vol. 116(509), pages 119-135, February.
    19. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2010. "Macroeconomic risks and characteristic-based factor models," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1383-1399, June.
    20. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    21. Lustig, Hanno & Verdelhan, Adrien, 2012. "Business cycle variation in the risk-return trade-off," Journal of Monetary Economics, Elsevier, vol. 59(S), pages 35-49.
    22. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    23. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jain, Pawan & Xue, Wenjun, 2017. "Global investigation of return autocorrelation and its determinants," Pacific-Basin Finance Journal, Elsevier, vol. 43(C), pages 200-217.
    2. Banegas Rivero, Roger Alejandro & Vergara González, Reyna, 2019. "Evaluación de escenarios fiscales para Bolivia," Revista Latinoamericana de Desarrollo Economico, Carrera de Economía de la Universidad Católica Boliviana (UCB) "San Pablo", issue 32, pages 132-168, November.

    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. Thierry Aimar & Francis Bismans & Claude Diebolt, 2010. "Le cycle économique : une synthèse," Revue Française d'Économie, Programme National Persée, vol. 24(4), pages 3-65.
    2. John Keating, 2004. "Interpreting Permanent and Transitory Shocks to Output When Aggregate Demand May Not Be Neutral in the Long-run," Econometric Society 2004 North American Summer Meetings 608, Econometric Society.
    3. Keating, John W., 1996. "Structural information in recursive VAR orderings," Journal of Economic Dynamics and Control, Elsevier, vol. 20(9-10), pages 1557-1580.
    4. Xiaochun Jiang & Wei Sun & Peng Su & Ting Wang, 2019. "The Synergy of Financial Volatility between China and the United States and the Risk Conduction Paths," Sustainability, MDPI, vol. 11(15), pages 1-22, August.
    5. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
    6. Grigoraş, Veaceslav & Stanciu, Irina Eusignia, 2016. "New evidence on the (de)synchronisation of business cycles: Reshaping the European business cycle," International Economics, Elsevier, vol. 147(C), pages 27-52.
    7. Rachel Male, 2010. "Developing Country Business Cycles: Characterising the Cycle," Working Papers 663, Queen Mary University of London, School of Economics and Finance.
    8. Avouyi-Dovi, S. & Matheron, J., 2003. "Interactions between business cycles, stock market cycles and interest rates: the stylised facts," Financial Stability Review, Banque de France, issue 3, pages 80-99, November.
    9. German Forero-Laverde, 2016. "Are All Booms and Busts Created Equal? A New Methodology for Understanding Bull and Bear Stock Markets," UB School of Economics Working Papers 2016/339, University of Barcelona School of Economics.
    10. Penelope A. Smith & Peter M. Summers, 2005. "How well do Markov switching models describe actual business cycles? The case of synchronization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 253-274.
    11. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    12. Esser, Andreas, 2014. "A Wavelet Approach to Synchronization of Output Cycles," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100545, Verein für Socialpolitik / German Economic Association.
    13. Mercè Sala-Rios & Teresa Torres-Solé & Mariona Farré-Perdiguer, 2016. "Credit and business cycles’ relationship: evidence from Spain," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 15(3), pages 149-171, December.
    14. Petr Rozmahel & Ladislava Issever Grochová & Marek Litzman, 2014. "The Effect of Asymmetries in Fiscal Policy Conducts on Business Cycle Correlation in the EU. WWWforEurope Working Paper No. 62," WIFO Studies, WIFO, number 47249, August.
    15. Bordo, Michael D. & Haubrich, Joseph G., 2010. "Credit crises, money and contractions: An historical view," Journal of Monetary Economics, Elsevier, vol. 57(1), pages 1-18, January.
    16. Paul Beaudry & Franck Portier, 2014. "News-Driven Business Cycles: Insights and Challenges," Journal of Economic Literature, American Economic Association, vol. 52(4), pages 993-1074, December.
    17. Vivian, Andrew & Wohar, Mark E., 2013. "The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?," International Review of Financial Analysis, Elsevier, vol. 26(C), pages 40-50.
    18. Olivier Darné & Laurent Ferrara, 2011. "Identification of Slowdowns and Accelerations for the Euro Area Economy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(3), pages 335-364, June.
    19. Bertrand Candelon & Jan Piplack & Stefan Straetmans, 2009. "Multivariate Business Cycle Synchronization in Small Samples," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 715-737, October.
    20. Gammadigbé, Vigninou, 2012. "Les cycles économiques des pays de l'UEMOA: synchrones ou déconnectés? [Business cycles in the WAEMU countries: synchronous or disconnected?]," MPRA Paper 39400, University Library of Munich, Germany, revised Jun 2012.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    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:bla:manchs:v:81:y:2013:i::p:100-124. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/semanuk.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.