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Infinite Density at the Median and the Typical Shape of Stock Return Distributions

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Abstract

Statistics are developed to test for the presence of an asymptotic discontinuity (or infinite density or peakedness) in a probability density at the median. The approach makes use of work by Knight (1998) on L_1 estimation asymptotics in conjunction with non-parametric kernel density estimation methods. The size and power of the tests are assessed, and conditions under which the tests have good performance are explored in simulations. The new methods are applied to stock returns of leading companies across major U.S. industry groups. The results confirm the presence of infinite density at the median as a new significant empirical evidence for stock return distributions.

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Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1701.

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Length: 32 pages
Date of creation: Jun 2009
Date of revision:
Publication status: Published in Journal of Business and Economic Statistics (April 2011), 29(2): 282-294
Handle: RePEc:cwl:cwldpp:1701
Note: CFP 1338.
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Keywords: Asymptotic leptokurtosis; Infinite density at the median; Least absolute deviations; Kernel density estimation; Stock returns; Stylized facts;

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Find related papers by JEL classification:
  • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
  • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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  14. repec:cup:etheor:v:23:y:2007:i:03:p:501-517 is not listed on IDEAS
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Cited by:

  1. Jin Seo Cho & Tae-Hwan Kim & Yongcheol Shin, 2014. "Quantile Cointegration in the Autoregressive Distributed-Lag Modelling Framework," Working papers 2014rwp-69, Yonsei University, Yonsei Economics Research Institute.
  2. Jin Seo Cho & Chirok Han & Peter C.B. Phillips, 2009. "LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities," Cowles Foundation Discussion Papers 1703, Cowles Foundation for Research in Economics, Yale University.

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