Skip to main content

Advertisement

Stock Market’s Reactions to Revelation of Tax Evasion: An Empirical Assessment

  • 277 Accesses

  • 2 Citations

Summary

Additionally to the financial crisis causing a world recession, Liechtenstein’s financial sector has been challenged by the so-called “Zumwinkel-Affair”, when a whistle-blower sold data of hundreds of tax evaders to international tax authorities. This paper investigates the impact of this affair on the daily stock prices of banks from Liechtenstein. An unconventional augmented GARCH-model (labelled as “augmented amalGARCH”), which outperforms conventional models, is introduced and dynamically analyses various influences on risk and returns. Also, an event study framework is applied. The main finding beyond further conclusions is that the Zumwinkel-Affair had an (accumulating) effect on risk, but surprisingly no impact on average stock return could be detected.

References

  1. Akaike, Hirotugu (1974), “A New Look at the Statistical Model Identification”, IEEE Transactions on Automatic Control, 19(6), pp. 716–723.

  2. Asteriou, Dimitrios, and Simon Price (2001), “Political Instability and Economic Growth: UK Time Series Evidence”, Scottish Journal of Political Economy, 48(4), pp. 383–399.

  3. Bollerslev, Tim (1986), “Generalized Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics, 31(3), pp. 307–327.

  4. Bollerslev, Tim (1987), “A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return,” Review of Economics and Statistics, 69, pp. 542–547.

  5. Brunhart, Andreas (2012), “Stock Market’s Reactions to Revelation of Tax Evasion: An Empirical Assessment”, KOFL Working Papers No. 9, Konjunkturforschungsstelle Liechtenstein.

  6. Burren, Daniel, and Klaus Neusser (2010) “The Decline in Volatility of US GDP Growth”, Applied Economics Letters, 17, pp. 1625–1631.

  7. Burnham, Kenneth P., and David R. Anderson (2004), “Multimodel Inference: Understanding AIC and BIC in Model Selection”, Sociological Methods & Research, 33(2), pp. 261–304.

  8. Dickey, David, and Wayne A. Fuller (1979), “Distribution of the Estimators for Autoregressive Time Series with a Unit Root”, Journal of the American Statistical Association, 74, pp. 427–431.

  9. Elyasiani, Elyas, Iqbal Mansur, and Babatunde Odusami (2011), “Oil Price Shocks and Industry Stock Returns”, Energy Economics, (33), pp. 966–974.

  10. Engle, Robert F. (1982), “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U. K. Inflation”, Econometrica, 50(4), pp. 987–1008.

  11. Engle, Robert F., David M. Lilien, and Russel P. Robins (1987), “Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M Model”, Econometrica, 55(2), pp. 391–407.

  12. Fama, Eugene F., Lawrence Fisher, michael C. Jensen, and richard Roll (1969), “The Adjustment of Stock Prices to New Information”, International Economic Review, (10), pp. 1–21.

  13. Glosten, Lawrence R., Ravi Jagannathan, and David E. Runkle (1993), “On the Relation between the Expected Value and Volatility of the Nominal Excess Return on Stocks”, The Journal of Finance, 48(5), pp. 1779–1801.

  14. Hammoudeh, Shawkat, and Yuan Yuan (2008), “Metal Volatility in Presence of Oil and Interest Rate Shocks”, Energy Economics, (30), pp. 606–620.

  15. Hauser, Michael and Robert M. Kunst (1993), “Fractionally Integrated Models With ARCH Errors”, Forschungsbericht No. 322, Institute for Advanced Studies.

  16. Hauser, Michael, and Robert M. Kunst (1998), “Fractionally Integrated Models With ARCH Errors: With an Application to the Swiss 1-Month Euromarket Interest Rate”, Review of Quantitative Finance and Accounting, 10, pp. 95–113.

  17. Kollias, Christos, Stephanos Papadamou, and Costas Siriopoulos (2012), “Terrorism Induced Cross-Market Transmission of Shocks: A Case Study Using Intraday Data”, Economics of Security Working Paper No. 66, EUSECON.

  18. Kothari, S. P., and Jerold B. Warner (2007), “Econometrics of Event Studies”, in Handbook of Corporate Finance, Espen Eckbo, ed., Vol. 1, pp. 3–36, North Holland: Elsevier.

  19. Kunst, Robert M. (1997), “Augmented ARCH Models for Financial Time Series: Stability Conditions and Empirical Evidence”, Applied Financial Economics, 7(6), pp. 575–586.

  20. Kunst, Robert M. (2003), “Testing for Relative Predictive Accuracy: A Critical Viewpoint”, Working Paper, University of Vienna.

  21. Kwiatkowski, Denis, Peter C. B. Phillips, Peter Schmidt, and Yongcheol Shin (1992), “Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We that Economic Time Series Have a Unit Root?”, Journal of Econometrics, 54, pp. 159–178.

  22. Ljung, Greta M., and George E. P. Box (1978), “On a Measure of Lack of Fit in Time Series Models”, Biometrika, 66(2), pp. 265–270.

  23. MacKinlay, A. Craig (1997), “Event Studies in Economics and Finance”, Journal of Economic Literature, 35, pp. 13–39.

  24. Phillips, Peter C. B., and Pierre Perron (1988), “Testing for a Unit Root in Time Series Regression”, Biometrika, 75(2), pp. 335–346.

  25. Pynnönen, Seppo (2005), “On Regression Based Event Study”, in Contributions to Accounting, Finance, and Management Science. Essays in Honor of Professor Timo Salmi, Erkkie K. Laitinen and Teija Latinen, eds., No. 143 of Acta Wasensia, pp. 327–354.

  26. Schwarz, Gideon (1978), “Estimating the Dimension of a Model”, Annals of Statistics, 6(2), pp. 461–464.

  27. Stoica, Petre, Yngve Selén, and Jian Li (2004), “On Information Criteria and the Generalized Likelihood Ratio Test of Model Order Selection”, IEEE Signal Processing Letters, 11(10), pp. 794–797.

  28. Taylor, Stephen J. (1986), Modelling Financial Time Series, Chichester: John Wiley & Sons.

  29. Tsay, Ruey S. (1987), “Conditional Heteroscedastic Time Series Models”, Journal of the American Statistical Association, 82(398), pp. 590–604.

  30. Weiss, Andrew A. (1984), “ARMA Models with ARCH Errors”, Journal of Time Series Analysis, 5(2), pp. 129–143.

  31. Weiss, Andrew A. (1986), “Asymptotic Theory for ARCH Models: Estimation and Testing”, Econometric Theory, 2(1), pp. 107–131.

  32. Zakoian, Jean-Michel (1994), “Threshold Heteroskedastic Models”, Journal of Economic Dynamics and Control, 18(5), pp. 931–955.

Download references

Author information

Correspondence to Andreas Brunhart.

Additional information

The author would like to thank Robert Kunst (University of Vienna), Karl Schlag (University of Vienna), Martin Kocher (Ludwig-Maximilians-University Munich), Carsten-Henning Schlag (University of Liechtenstein), Kersten Kellermann (Konjunkturforschungsstelle Liechtenstein), Berno Buchel (University of Hamburg) and various participants of the “graduate and staff seminar” at the University of Vienna and also an anonymous referee for useful comments.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Brunhart, A. Stock Market’s Reactions to Revelation of Tax Evasion: An Empirical Assessment. Swiss J Economics Statistics 150, 161–190 (2014). https://doi.org/10.1007/BF03399405

Download citation

Keyword

  • Tax Evasion
  • Liechtenstein
  • Zumwinkel
  • Stock Price Volatility
  • Augmented GARCH
  • Event Study

JEL-Classification

  • C01
  • C22
  • G01
  • G14
  • G21