Abstract
We test for a relation between football match results and the specific national stock index returns during the period 1990–2006 by means of an event study approach. We employ two different econometric frameworks to cross-check our results and prevent them from being solely model driven: the constant mean model and a two-state Markov-switching market model. Both approaches find no significant results. Consequently, in a modified setup, we control for expectations about probable game results by applying a “surprise” variable, which is computed from betting odds and is integrated into a regression analysis. Again, there does not seem to be a connection between a specific national soccer team’s win or loss and stock index prices. In addition, through a few modifications in our empirical setup, we show how easy it would be to “produce” significant results. Our results are contrary to those of Ashton et al. (Appl Econ Lett 10:783–785, 2003) and Edmans et al. (J Finance 62(4):1967–1998, 2007) and support market efficiency.
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Notes
For a survey of the research on the influence of investor feelings on equity pricing see, e.g., Lucey and Dowling (2005).
Data are only available for Czech Republic from September 1994 onward.
Oddset did not place betting odds for all matches in this time period.
Dorfleitner (2003) demonstrates that with such tiny returns there is virtually no difference between discrete and continuously compounded returns.
Intervals of 250 and 60 days were also tested without much change to the results.
The first implementation of this framework in an empirical event study was by Gurgul and Majdosz (2007), who assessed the profitability of insider trading.
Regime-dependent market betas make sense from both a statistical and economic point of view: In a large part of our estimated models, the regime-dependent betas were respectively extremely different and significant in the two regimes.
The test for statistical significance was done with a binomial test with the hypotheses H 0: P ≤ 0.5 versus H 1: P > 0.5, whereas P is the respective probability of a positive excess return in the case of a win and a negative excess return in the case of a loss. The significance level is 5%.
There are no hints of a strong autocorrelation (the Durbin/Watson test is 1.95). A visual check of the residuals shows no signs of heteroskedasticity or autocorrelation. Furthermore, the distributions of the residuals are unimodal and symmetrical. There seem to be no multicollinear structures because at 12.5 the number of conditions is far from the critical area.
See McQueen et al. (1997), p. 69.
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Klein, C., Zwergel, B. & Heiden, S. On the existence of sports sentiment: the relation between football match results and stock index returns in Europe. Rev Manag Sci 3, 191–208 (2009). https://doi.org/10.1007/s11846-009-0031-8
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DOI: https://doi.org/10.1007/s11846-009-0031-8