Efficient Algorithms for Stochastic Dominance Tests Based on Financial Market Data

Although a wide array of stochastic dominance tests exist for poverty measurement and identification, they assume the income distributions have independent poverty lines or a common absolute (fixed) poverty line. We propose a stochastic dominance test for comparing income distributions up to a common relative poverty line (i.e., some fraction of the pooled median). A Monte Carlo study demonstrates its superior performance over existing methods in terms of power. The test is then applied to some Canadian household survey data for illustration.

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Distributional Characteristics And Stochastic Dominance versus Parametric Analysis In Testing Anomalies In The Emerging Market: Evidence From Jordan

Journal of Business & Economics Research (JBER) ◽

10.19030/jber.v1i10.3062 ◽

2011 ◽

Vol 1 (10) ◽

Author(s):

Osamah Al-Khazali

Keyword(s):

Seasonal Variation ◽

Emerging Markets ◽

Stock Returns ◽

Financial Market ◽

Stochastic Dominance ◽

Parametric Analysis ◽

Emerging Market ◽

Market Returns ◽

Parametric Analyses ◽

Mean Variance

Virtually all previous studies of seasonal variation in stock returns have used mean/variance analysis despite it being well documented that stock returns in developed and emerging markets are non-normally distributed. This paper details the distributional characteristics of emerging Amman financial market returns. Further more, it uses stochastic dominance and parametric analyses to investigate the turn-of-the-year and the-week effects from 1978 to 2001. Results indicate that returns of Amman financial market exhibit substantial deviation from normality. And parametric analysis tests show there is January and week effects. However, stochastic dominance results indicate that January and week effects are not exist in the AFM. This implies that the results of parametric analysis are being driven by violations of parametric assumptions.

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Financial Market Data Versus Accounting Data: Which Better Explains Stock Returns?

International Advances in Economic Research ◽

10.1007/s11294-020-09774-4 ◽

2020 ◽

Vol 26 (1) ◽

pp. 59-72 ◽

Cited By ~ 1

Author(s):

Nicholas Belesis ◽

John Sorros ◽

Alkiviadis Karagiorgos

Keyword(s):

Stock Returns ◽

Financial Market ◽

Accounting Data ◽

Market Data

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Assessing Deprivation with an Ordinal Variable: Theory and Application to Sanitation Deprivation in Bangladesh

The World Bank Economic Review ◽

10.1093/wber/lhz051 ◽

2020 ◽

Author(s):

Suman Seth ◽

Gaston Yalonetzky

Keyword(s):

Stochastic Dominance ◽

Poverty Alleviation ◽

Poverty Measurement ◽

Variable Theory ◽

The Past ◽

The Poor ◽

Ordinal Variable ◽

Poverty Measures ◽

Dominance Tests ◽

Empirical Illustration

Abstract The challenges associated with poverty measurement using a cardinal variable have received much attention over the past four decades, but there is a dearth of literature on how to meaningfully assess poverty with an ordinal variable. This article proposes a class of simple, intuitive, and policy-relevant poverty measures for ordinal variables. The measures are sensitive to the depth of deprivations, unlike the headcount ratio. Moreover, under appropriate restrictions, the measures ensure that priority is given to the poorest among the poor when targeting, monitoring, and evaluating poverty alleviation programs. To assess the robustness of poverty comparisons to alternative choices of parameters, the article develops various stochastic dominance tests (some of which are novel contributions to the stochastic dominance literature). The empirical illustration documenting changes in sanitation deprivation in Bangladesh showcases the measures’ ability to identify instances in which overall sanitation deprivation improved while leaving the poorest behind.

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