activity
20062026
most citedRetirement decision with addictive habit persistence in a jump diffusion market

6 citations · 30 across the 63 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

math.OC2023

Equilibrium stochastic control with implicitly defined objective functions

Zongxia Liang, Jianming Xia, Keyu Zhang

This paper considers a class of stochastic control problems with implicitly defined objective functions, which are the sources of time-inconsistency. We study the closed-loop equil…

q-fin.MF2023

Time-inconsistent mean field and n-agent games under relative performance criteria

Zongxia Liang, Keyu Zhang

In this paper we study a time-inconsistent portfolio optimization problem for competitive agents with CARA utilities and non-exponential discounting. The utility of each agent depe…

q-fin.MF2023

Dynamic portfolio selection for nonlinear law-dependent preferences

Zongxia Liang, Jianming Xia, Fengyi Yuan

This paper addresses the portfolio selection problem for nonlinear law-dependent preferences in continuous time, which inherently exhibit time inconsistency. Employing the method o…

math.OC2023

Equilibria for Time-inconsistent Singular Control Problems

Zongxia Liang, Xiaodong Luo, Fengyi Yuan

We study a time-inconsistent singular control problem originating from irreversible reinsurance decisions with non-exponential discount. A novel definition of equilibrium for time-…

q-fin.MF2023

Optimal Mix Among PAYGO, EET and Individual Savings

Lin He, Zongxia Liang, Zhaojie Ren +1

In order to deal with the aging problem, pension system is actively transformed into the funded scheme. However, the funded scheme does not completely replace PAYGO (Pay as You Go)…

q-fin.PM2023

Optimal management of DB pension fund under both underfunded and overfunded cases

Guohui Guan, Zongxia Liang, Yi Xia

This paper investigates the optimal management of an aggregated defined benefit pension plan in a stochastic environment. The interest rate follows the Ornstein-Uhlenbeck model, th…