Kalaichelvan, Mohandass and Lim Kai Jie, Shawn (2012): A Critical Evaluation of the Significance of Round Numbers in European Equity Markets in Light of the Predictions from Benford’s Law. Published in: International Research Journal of Finance and Economics No. 95 : pp. 196-210.
Download (1MB) | Preview
In this study, we test the hypothesis that psychological barriers exist in 5 European Equity Market indices [ATX, CAC, DAX, FTSE, SMI]. We employ both a traditional methodology that assumes a uniform distribution of M-Values and a modified approach that accounts for the fact that the digits of stock prices may be distributed in accordance with Benford’s law. In addition, we test the validity of the various assumptions employed in these tests using a Monte Carlo Simulation and Kuiper’s Modified Kolmogorov-Smirnov Goodness of Fit Test. We find evidence for barriers in 1 index [SMI] at the 1000 level under the assumption of uniformity but no significant evidence of barriers at the 100 level or at the 1000 level in the remaining indices. We also find evidence that substantiates the criticism of the use of the uniformity assumption for tests at the 1000 level in favour of a distribution consistent with Benford’s Law. However, we do not reach a different conclusion on the presence of psychological barriers when tests are performed without the implicit use of that uniformity assumption. In addition, we find possible evidence of price clustering around round numbers at the 1000 level in 2 indices [CAC, DAX] even after adjusting for the expected concentration within the region due to Benford-specific effects.
|Item Type:||MPRA Paper|
|Original Title:||A Critical Evaluation of the Significance of Round Numbers in European Equity Markets in Light of the Predictions from Benford’s Law|
|Keywords:||Benford’s Law; psychological barriers in stock prices; significance of round numbers in stock prices;|
|Subjects:||G - Financial Economics > G1 - General Financial Markets
G - Financial Economics > G2 - Financial Institutions and Services
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General
G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: General
|Depositing User:||Mohandass Kalaichelvan|
|Date Deposited:||30. Aug 2012 11:23|
|Last Modified:||22. Aug 2015 00:06|
 Benford, F. (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, 78, 551-572.
 Bertola, G., & Caballero, R. (1992). Target zones and realignments. American Economics Review, 82, 520-536.
 Cohen, D. (1976). An explanation of the first digit phenomenon. Journal of Combinatorial Theory, 20, 367-370.
 De Ceuster, M. K. J., Dhaene, J., & Schatteman, T. (1998). On the hypothesis of psychological barriers in stock markets and benford’s law. Journal of Empirical Finance, 5, 263-279.
 Donaldson, R. G., & Kim, H. Y. (1993). Price barriers in the dow jones industrial average. Journal of Financial and Quantitative Analysis, 28(3), 313-330.
 Dorfleitner, G., & Klein, C. (2009). Psychological barriers in european stock markets: where are they?. Global Finance Journal, 268-285.
 Edwards, R. D., Magee, J., & Bassetti, W. H. C. (2007). Technical analysis of stock trends. 9th ed., 245.
 Giles, D. E. (2007). Benford’s law and naturally occurring prices in certain ebay auctions. Applied Economics Letters, 14, 157-161.
 Harris, L. (1991). Stock price clustering and discreteness. Review of Financial Studies 4, 389- 415.
 Hill, T. P. (1995). A statistical derivation of the significant-digit law. Statistical Science, 10, 354-363.
 Hill, T. P. (1995). Base-invariance implies benford’s law. Proceedings of the American Mathematical Society, 123, 887-895.
 Judge, G., & Schechter, L. (2009). Detecting problems in survey data using benford’s law. Journal of Human Resources, 44, 1-24.
 Koedijk, K. G., & Stork, P. A. (1994). Should we care? Psychological barriers in stock markets. Economics Letters, 427-432.
 Ley, E., & Varian, H.R. (1994). Are there psychological barriers in the Dow-Jones index? Applied Financial Economics, 4, 217-224.
 Murphy, J. J. (1999), Technical analysis of the financial markets: a comprehensive guide to trading methods and applications. 2nd ed, 55.
 Morrow, J. (2010). Benford’s law, families of distributions and a test basis.
 Nigrini, M. (1996). A taxpayer compliance application of benford’s law. Journal of the American Taxation Association, 18, 72-91.
 Pinkham, R. S. (1961). On the distribution of the first significant digits. Annals of Mathematical Statistics, 32, 1223-1230.
 Schindler, R. M., & Kirby, P. N. (1997). Patterns of rightmost digits used in advertised prices: implications for nine-ending effects. The Journal of Consumer Research, 24:2, 192-201.
 Sonnemans, J. (2006). Price clustering and natural resistance points in the dutch stock market: a natural experiment. European Economic Review, 1937-1950.
 Stephens, M. A. (1970). Use of the kolmogorov-smirnov, cramer-von-mises and related statistics without extensive tables. Journal of the Royal Statistical Society. Series B (Methodological), 32, 115-122.