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Moments of cross‐sectional stock market returns and the German business cycle

Author

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  • Jörg Döpke
  • Karsten Müller
  • Lars Tegtmeier

Abstract

Based on monthly data covering the period from 1987 to 2021, we analyse whether cross‐sectional moments of stock market returns may provide information about the future position of the German business cycle. We apply in‐sample forecasting regressions with and without leading indicators as control variables, pseudo‐out‐of‐sample exercises, autoregressive distributed lag models, and impulse‐response functions estimated by local projections. We find in‐sample predictive power of the first and third cross‐section moments for the future growth of industrial production, even if one controls for well‐established leading indicators for the German business cycle. Out‐of‐sample tests show that these variables reduce the relative mean squared error compared with benchmark models. We do not find a long‐run relation between the moment series and industrial production. The dynamic response of industrial production to a shock on the cross‐section moments is in line with the other results.

Suggested Citation

  • Jörg Döpke & Karsten Müller & Lars Tegtmeier, 2023. "Moments of cross‐sectional stock market returns and the German business cycle," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 52(2), July.
    • Handle: RePEc:bla:ecnote:v:52:y:2023:i:2:n:e12219
    DOI: 10.1111/ecno.12219
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    as
    1. Kozeniauskas, Nicholas & Orlik, Anna & Veldkamp, Laura, 2018. "What are uncertainty shocks?," Journal of Monetary Economics, Elsevier, vol. 100(C), pages 1-15.
    2. Elisabeth Mueller & Alexandra Spitz‐Oener, 2006. "Managerial Ownership and Company Performance in German Small and Medium‐Sized Private Enterprises," German Economic Review, Verein für Socialpolitik, vol. 7(2), pages 233-247, May.
    3. Elisabeth Mueller & Alexandra Spitz‐Oener, 2006. "Managerial Ownership and Company Performance in German Small and Medium‐Sized Private Enterprises," German Economic Review, Verein für Socialpolitik, vol. 7(2), pages 233-247, May.
    4. Francis X. Diebold, 2015. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 1-1, January.
    5. R?diger Bachmann & Steffen Elstner & Eric R. Sims, 2013. "Uncertainty and Economic Activity: Evidence from Business Survey Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 217-249, April.
    6. Lilien, David M, 1982. "Sectoral Shifts and Cyclical Unemployment," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 777-793, August.
    7. Tim Bollerslev & Viktor Todorov, 2011. "Tails, Fears, and Risk Premia," Journal of Finance, American Finance Association, vol. 66(6), pages 2165-2211, December.
    8. Francois Gourio, 2012. "Disaster Risk and Business Cycles," American Economic Review, American Economic Association, vol. 102(6), pages 2734-2766, October.
    9. Emeka Nkoro & Aham Kelvin Uko, 2016. "Autoregressive Distributed Lag (ARDL) cointegration technique: application and interpretation," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 5(4), pages 1-3.
    10. Robert J. Barro, 2006. "Rare Disasters and Asset Markets in the Twentieth Century," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(3), pages 823-866.
    11. David G. McMillan, 2021. "Predicting GDP growth with stock and bond markets: Do they contain different information?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3651-3675, July.
    12. Jay Choi, Jongmoo & Hauser, Shmuel & Kopecky, Kenneth J., 1999. "Does the stock market predict real activity? Time series evidence from the G-7 countries," Journal of Banking & Finance, Elsevier, vol. 23(12), pages 1771-1792, December.
    13. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    14. Audretsch, David B. & Elston, Julie Ann, 2002. "Does firm size matter? Evidence on the impact of liquidity constraints on firm investment behavior in Germany," International Journal of Industrial Organization, Elsevier, vol. 20(1), pages 1-17, January.
    15. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    16. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    17. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    18. Marques, Luís Miguel & Fuinhas, José Alberto & Marques, António Cardoso, 2013. "Does the stock market cause economic growth? Portuguese evidence of economic regime change," Economic Modelling, Elsevier, vol. 32(C), pages 316-324.
    19. Uwe Hassler & Jürgen Wolters, 2006. "Autoregressive Distributed Lag Models and Cointegration," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 5, pages 57-72, Springer.
    20. Jennifer Conrad & Robert F. Dittmar & Eric Ghysels, 2013. "Ex Ante Skewness and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 68(1), pages 85-124, February.
    21. Fama, Eugene F, 1990. "Stock Returns, Expected Returns, and Real Activity," Journal of Finance, American Finance Association, vol. 45(4), pages 1089-1108, September.
    22. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    23. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    24. José Vicente & Gustavo Araujo, 2018. "What does the tail of the distribution of current stock prices tell us about future economic activity?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(4), pages 506-516, July.
    25. Jörg Breitung & Malte Knüppel, 2021. "How far can we forecast? Statistical tests of the predictive content," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 369-392, June.
    26. Paresh Kumar Narayan, 2005. "The saving and investment nexus for China: evidence from cointegration tests," Applied Economics, Taylor & Francis Journals, vol. 37(17), pages 1979-1990.
    27. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    28. Audretsch, David B. & Elston, Julie Ann, 2002. "Does firm size matter? Evidence on the impact of liquidity constraints on firm investment behavior in Germany," International Journal of Industrial Organization, Elsevier, vol. 20(1), pages 1-17, January.
    29. Laurence Ball & N. Gregory Mankiw, 1995. "Relative-Price Changes as Aggregate Supply Shocks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 161-193.
    30. Angelidis, Timotheos & Sakkas, Athanasios & Tessaromatis, Nikolaos, 2015. "Stock market dispersion, the business cycle and expected factor returns," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 265-279.
    31. Xavier Gabaix, 2012. "Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in Macro-Finance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(2), pages 645-700.
    32. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
    33. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    34. Schwert, G William, 1990. "Stock Returns and Real Activity: A Century of Evidence," Journal of Finance, American Finance Association, vol. 45(4), pages 1237-1257, September.
    35. Fabio Panetta, 2002. "The Stability of the Relation Between the Stock Market and Macroeconomic Forces," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 31(3), pages 417-450, November.
    36. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    37. Kitlinski, Tobias, 2015. "With or without you: Do financial data help to forecast industrial production?," Ruhr Economic Papers 558, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    38. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
    39. Loungani, Prakash & Rush, Mark & Tave, William, 1990. "Stock market dispersion and unemployment," Journal of Monetary Economics, Elsevier, vol. 25(3), pages 367-388, June.
    40. Tsouma, Ekaterini, 2009. "Stock returns and economic activity in mature and emerging markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(2), pages 668-685, May.
    41. Elena Andreou & Denise R. Osborn & Marianne Sensier, 2000. "A Comparison of the Statistical Properties of Financial Variables in the USA, UK and Germany over the Business Cycle," Manchester School, University of Manchester, vol. 68(4), pages 396-418, June.
    42. Prakash Loungani & Mark Rush & William Tave, 1991. "Stock market dispersion and business cycles," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 15(Jan), pages 2-8.
    43. Vu, Nam T., 2015. "Stock market volatility and international business cycle dynamics: Evidence from OECD economies," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 1-15.
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