This paper studies the portfolio optimization of mean-variance utility with state-dependent risk aversion, where the stock asset is driven by a stochastic process. The sub-game perfect Nash equilibrium strategies and the extended Hamilton-Jacobi-Bellman equations have been used to derive the system of non-linear partial differential equations. From the economic point of view, we demonstrate the numerical evaluation of the suggested solution for a special case where the risk aversion rate is proportional to the wealth value. Our results show that the asset driven by the stochastic volatility process is more general and reasonable than the process with a constant volatility
We develop a model of optimal asset allocation based on a utility framework. This applies to a more ...
We investigate some portfolio problems that consist of maximizing expected terminal wealth under the...
We develop a model of optimal asset allocation based on a utility framework. This applies to a more ...
In order to tackle the problem of how investors in financial markets allocate wealth to stochastic i...
© 2017, Copyright © Society of Actuaries.This article investigates the asset liability management pr...
In this paper we examine the effect of stochastic volatility on optimal portfolio choice in both par...
In this paper we examine the effect of stochastic volatility on optimal portfolio choice in both par...
AbstractThe objective of this article is the research of optimal portfolio strategy under a probabil...
Assuming that the wealth process Xu is generated self-financially from the given initial wealth by h...
Assuming that the wealth process Xu is generated self-financially from the given initial wealth by h...
AbstractWe consider a portfolio optimization problem under stochastic volatility as well as stochast...
The author proposes a new algorithm using a stochastic flow technique to solve an optimal portfolio ...
In this work, we study the equilibrium reinsurance/ new business and investment strategy for mean-va...
In this paper, we consider the asset-liability management under the mean-variance criterion. The fin...
Abstract. The author proposes a new algorithm using a stochas-tic flow technique to solve an optimal...
We develop a model of optimal asset allocation based on a utility framework. This applies to a more ...
We investigate some portfolio problems that consist of maximizing expected terminal wealth under the...
We develop a model of optimal asset allocation based on a utility framework. This applies to a more ...
In order to tackle the problem of how investors in financial markets allocate wealth to stochastic i...
© 2017, Copyright © Society of Actuaries.This article investigates the asset liability management pr...
In this paper we examine the effect of stochastic volatility on optimal portfolio choice in both par...
In this paper we examine the effect of stochastic volatility on optimal portfolio choice in both par...
AbstractThe objective of this article is the research of optimal portfolio strategy under a probabil...
Assuming that the wealth process Xu is generated self-financially from the given initial wealth by h...
Assuming that the wealth process Xu is generated self-financially from the given initial wealth by h...
AbstractWe consider a portfolio optimization problem under stochastic volatility as well as stochast...
The author proposes a new algorithm using a stochastic flow technique to solve an optimal portfolio ...
In this work, we study the equilibrium reinsurance/ new business and investment strategy for mean-va...
In this paper, we consider the asset-liability management under the mean-variance criterion. The fin...
Abstract. The author proposes a new algorithm using a stochas-tic flow technique to solve an optimal...
We develop a model of optimal asset allocation based on a utility framework. This applies to a more ...
We investigate some portfolio problems that consist of maximizing expected terminal wealth under the...
We develop a model of optimal asset allocation based on a utility framework. This applies to a more ...