
Summary: \textit{H. Levy} and \textit{M. Levy} [``Prospect theory: much ado about nothing?'', Manage. Sci. 48, 1334--1349 (2002); ``Prospect theory and mean-variance analysis'', Rev. Financ. Stud. 17, 1015--1041 (2004)] extend the stochastic dominance (SD) theory for risk averters and risk seekers by developing the prospect SD (PSD) and Markowitz SD (MSD) theory for investors with S-shaped and reverse S-shaped (RS-shaped) utility functions, respectively. Davidson and Duclos (2000) develop SD tests for risk averters whereas \textit{S. Sriboonchitta, W.-K. Wong, S. Dhompongsa} and \textit{H. T. Nguyen} [Stochastic dominance and applications to finance, risk and economics. Boca Raton, FL: CRC Press (2010; Zbl 1180.91010)] modify their statistics to obtain SD tests for risk seekers. In this paper, we extend their work by developing new statistics for both PSD and MSD of the first three orders. These statistics provide a tool to examine the preferences of investors with S-shaped utility functions proposed by \textit{D. Kahneman} and \textit{A. Tversky} [Econometrica 47, 263--291 (1979; Zbl 0411.90012)] in their prospect theory and investors with RS-shaped investors proposed by \textit{H. M. Markowitz} [``The utility of wealth'', J. Polit. Econ. 60, 151--156 (1952)]. We also derive the limiting distributions of the test statistics to be stochastic processes. In addition, we propose a bootstrap method to decide the critical points of the tests and prove the consistency of the bootstrap tests. To illustrate the applicability of our proposed statistics, we apply them to study the preferences of investors with the corresponding S-shaped and RS-shaped utility functions\ vis-à-vis\ returns on iShares and\ vis-à-vis\ returns of traditional stocks and Internet stocks before and after the Internet bubble.
Applications of statistics to actuarial sciences and financial mathematics, S-shaped utility function, risk seeking, RS-shaped utility function, test statistics, 330, prospect stochastic dominance, Risk seeking, Prospect stochastic dominance, Hypothesis testing, Risk averse, Markowitz stochastic dominance, Test statistics, hypothesis testing, Inequalities; stochastic orderings, risk averse, Statistical methods; risk measures
Applications of statistics to actuarial sciences and financial mathematics, S-shaped utility function, risk seeking, RS-shaped utility function, test statistics, 330, prospect stochastic dominance, Risk seeking, Prospect stochastic dominance, Hypothesis testing, Risk averse, Markowitz stochastic dominance, Test statistics, hypothesis testing, Inequalities; stochastic orderings, risk averse, Statistical methods; risk measures
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