arXiv subjects

Liulei Sun

Publications and source records attributed to Liulei Sun.

2 recordsLinked to original sources

arXiv2026

Asymptotic fractional-order stochastic dominance with bounded relative risk aversion

In this paper, we propose a novel asymptotic fractional-order stochastic dominance rule for ranking prospects over a sufficiently long investment horizon. The new rule formulates the consensus of decision makers whose relative risk aversion has a negative lower bound. Under the assumption that returns are lognormally distributed, we establish equivalent conditions for the proposed rule without imposing the non-negativity constraint on the mean of log-return, a restriction usually required by the existing asymptotic stochastic dominance rules. Furthermore, to enhance the tractability of this asymptotic fractional-order stochastic dominance, we propose a variant of asymptotic fractional-order stochastic dominance with bounded relative risk aversion, referred to as general asymptotic fractional-order stochastic dominance, under an additional condition on decision makers' marginal utilities. We derive its corresponding equivalent distributional characterizations. The (general) asymptotic fractional-order stochastic dominance with bounded relative risk aversion overcomes the shortcomings of the existing asymptotic fractional-order criterion that the fractional-order parameter has no influence on the equivalent distributional conditions. Empirical examples further show the advantages of the newly proposed rules for asset selection in long-term investment decisions.

q-fin.RM↗

arXiv2026

Admissibility and Complete Classes for False Discovery Rate Control with E-values

The false discovery rate (FDR) is the most widely used error metric in modern multiple testing. We provide a comprehensive analysis of the admissibility of e-value-based procedures with FDR control. We consider both simultaneous and point procedures and introduce strong and weak notions of dominance. Every simultaneous procedure is strongly, and hence weakly, dominated by an admissible weighted-mean closed e-Benjamini--Hochberg ($\overline{\mathrm{eBH}}$) procedure, and thus weighted-mean $\overline{\mathrm{eBH}}$ procedures form a complete class. Every constant-free weighted-mean $\overline{\mathrm{eBH}}$ procedure is admissible at every level, and we propose two ways for choosing constant-free weights based on side information, such as pre-screening data. Within the symmetric class, the usual mean $\overline{\mathrm{eBH}}$ procedure is the largest element if and only if the FDR level is small enough; otherwise this class has no largest element. We also obtain results on the admissibility of symmetric weighted-mean $\overline{\mathrm{eBH}}$ procedures with non-zero constant terms. Point e-testing procedures have a parallel theory of admissibility. These results highlight the central role of weighted-mean $\overline{\mathrm{eBH}}$ procedures in multiple testing.

stat.ME↗