scholarly journals Representation of Homothetic Forward Performance Processes in Stochastic Factor Models Via Ergodic and Infinite Horizon BSDE

2016 ◽  
Author(s):  
Gechun Liang ◽  
Thaleia Zariphopoulou
Keyword(s):  
Infinite Horizon ◽  
Factor Models ◽  
Stochastic Factor ◽  
Forward Performance

scholarly journals An optimal portfolio problem in a defaultable market

2010 ◽  
Vol 42 (03) ◽  
pp. 689-705 ◽  
Author(s):  
Lijun Bo ◽  
Yongjin Wang ◽  
Xuewei Yang
Keyword(s):  
Risk Premium ◽  
Default Risk ◽  
Infinite Horizon ◽  
Control Policy ◽  
Dynamic Programming Principle ◽  
Defaultable Bond ◽  
Portfolio Problem ◽  
Stochastic Factor ◽  
Hamilton Jacobi Bellman ◽  
Portfolio Optimization Problem

We consider a portfolio optimization problem in a defaultable market. The investor can dynamically choose a consumption rate and allocate his/her wealth among three financial securities: a defaultable perpetual bond, a default-free risky asset, and a money market account. Both the default risk premium and the default intensity of the defaultable bond are assumed to rely on some stochastic factor which is described by a diffusion process. The goal is to maximize the infinite-horizon expected discounted log utility of consumption. We apply the dynamic programming principle to deduce a Hamilton-Jacobi-Bellman equation. Then an optimal Markov control policy and the optimal value function is explicitly presented in a verification theorem. Finally, a numerical analysis is presented for illustration.

An optimal portfolio problem in a defaultable market

2010 ◽  
Vol 42 (3) ◽  
pp. 689-705 ◽  
Author(s):  
Lijun Bo ◽  
Yongjin Wang ◽  
Xuewei Yang
Keyword(s):  
Risk Premium ◽  
Default Risk ◽  
Infinite Horizon ◽  
Control Policy ◽  
Dynamic Programming Principle ◽  
Defaultable Bond ◽  
Portfolio Problem ◽  
Stochastic Factor ◽  
Hamilton Jacobi Bellman ◽  
Portfolio Optimization Problem

We consider a portfolio optimization problem in a defaultable market. The investor can dynamically choose a consumption rate and allocate his/her wealth among three financial securities: a defaultable perpetual bond, a default-free risky asset, and a money market account. Both the default risk premium and the default intensity of the defaultable bond are assumed to rely on some stochastic factor which is described by a diffusion process. The goal is to maximize the infinite-horizon expected discounted log utility of consumption. We apply the dynamic programming principle to deduce a Hamilton-Jacobi-Bellman equation. Then an optimal Markov control policy and the optimal value function is explicitly presented in a verification theorem. Finally, a numerical analysis is presented for illustration.

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