Dynamic Mean-Downside Risk Portfolio Selection Problem with Stochastic Interest Rate in Continuous-Time

2021 ◽  
Author(s):  
weiping wu ◽  
Ke Zhou ◽  
Zhicheng Li ◽  
zhenpeng tang
2004 ◽  
Vol 09 (01) ◽  
Author(s):  
Teresa León ◽  
Vicente Liern ◽  
Paulina Marco ◽  
Enriqueta Vercher ◽  
José Vicente Segura

2017 ◽  
Author(s):  
SYAHRIL

This paper discusses an optimal transaction interval for a consumption and investment decision problemfor an~individual who has available a~risklessasset paying fixed interest rate and a~risky asset driven byBrownian motion price fluctuations.The individual observes current wealth when making transactions, that transactions incur costs,and that decisions to transact can be made at any time based on all current information.The transactions costs is fixed for every transaction, regardless of amount transacted. In addition, the investor is charged a fixed fraction oftotal wealth as management fee. The investor's objective is to maximize the expectedutility of consumption over a given horizon.The problem faced by the investor is formulated in a stochastic discrete-continuous-time control problem. An optimal transaction interval for the inverstor is derived.


Algorithms ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 252
Author(s):  
Weiping Wu ◽  
Lifen Wu ◽  
Ruobing Xue ◽  
Shan Pang

This paper revisits the dynamic MV portfolio selection problem with cone constraints in continuous-time. We first reformulate our constrained MV portfolio selection model into a special constrained LQ optimal control model and develop the optimal portfolio policy of our model. In addition, we provide an alternative method to resolve this dynamic MV portfolio selection problem with cone constraints. More specifically, instead of solving the correspondent HJB equation directly, we develop the optimal solution for this problem by using the special properties of value function induced from its model structure, such as the monotonicity and convexity of value function. Finally, we provide an example to illustrate how to use our solution in real application. The illustrative example demonstrates that our dynamic MV portfolio policy dominates the static MV portfolio policy.


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