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PySDTest: a Python Package for Stochastic Dominance Tests

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  • Kyungho Lee
  • Yoon-Jae Whang

Abstract

We introduce PySDTest, a Python package for statistical tests of stochastic dominance. PySDTest can implement the testing procedures of Barrett and Donald (2003), Linton et al. (2005), Linton et al. (2010), Donald and Hsu (2016), and their extensions. PySDTest provides several options to compute the critical values including bootstrap, subsampling, and numerical delta methods. In addition, PySDTest allows various notions of the stochastic dominance hypothesis, including stochastic maximality among multiple prospects and prospect dominance. We briefly give an overview of the concepts of stochastic dominance and testing methods. We then provide a practical guidance for using PySDTest. For an empirical illustration, we apply PySDTest to the portfolio choice problem between the daily returns of Bitcoin and S&P 500 index. We find that the S&P 500 index returns second-order stochastically dominate the Bitcoin returns.

Suggested Citation

  • Kyungho Lee & Yoon-Jae Whang, 2023. "PySDTest: a Python Package for Stochastic Dominance Tests," Papers 2307.10694, arXiv.org.
    • Handle: RePEc:arx:papers:2307.10694
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    References listed on IDEAS

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    1. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    2. Anderson, Gordon, 1996. "Nonparametric Tests of Stochastic Dominance in Income Distributions," Econometrica, Econometric Society, vol. 64(5), pages 1183-1193, September.
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