Testing the Significance of Calendar Effects

Peter Reinhard Hansen, Asger Lunde, and James M. Nason
Working Paper 2005-2
January 2005

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This paper studies tests of calendar effects in equity returns. It is necessary to control for all possible calendar effects to avoid spurious results. The authors contribute to the calendar effects literature and its significance with a test for calendar-specific anomalies that conditions on the nuisance of possible calendar effects. Thus, their approach to test for calendar effects produces robust data-mining results. Unfortunately, attempts to control for a large number of possible calendar effects have the downside of diminishing the power of the test, making it more difficult to detect actual anomalies. The authors show that our test achieves good power properties because it exploits the correlation structure of (excess) returns specific to the calendar effect being studied. We implement the test with bootstrap methods and apply it to stock indices from Denmark, France, Germany, Hong Kong, Italy, Japan, Norway, Sweden, the United Kingdom, and the United States. Bootstrap p-values reveal that calendar effects are significant for returns in most of these equity markets, but end-of-the-year effects are predominant. It also appears that, beginning in the late 1980s, calendar effects have diminished except in small-cap stock indices.

JEL classification: C12, C22, G14

Key words: Phillips curve, calendar effects, data mining, significance test

The authors thank Mark Kamstra and seminar participants at Brown University for valuable comments and Kim Christensen for excellent research assistance. Financial support from the Danish Research Agency, grant number 24-00-0363, and from the Salomon Research Award at Brown University is gratefully acknowledged. The views expressed here are the authors’ and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors’ responsibility.

Please address questions regarding content to Peter Reinhard Hansen, Stanford University, Landau Economics Building, 579 Serra Mall, Stanford, California 94305-6072, peter.hansen@stanford.edu; Asger Lunde, The Aarhus School of Business, Department of Information Science, Fuglesangs Alle 4 DK-8210, Aarhus V, alunde@asb.dk; or James M. Nason, Federal Reserve Bank of Atlanta, Research Department, 1000 Peachtree Street, N.E., Atlanta, Georgia 30309, 404-498-8891, jim.nason@atl.frb.org.