TY - JOUR
T1 - Minimum probability function of crossing the upper regulatory threshold for asset-liability management
AU - Sheng, De Lei
AU - Li, Danping
AU - Shen, Peilong
N1 - Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.
PY - 2021
Y1 - 2021
N2 - In this paper, a stochastic model of asset-liability multiple is considered. To avoid the unbearable investment risk of asset price collapse, an upper regulatory threshold constraint is imposed on the asset-liability multiple. A Hamilton-Jacobi-Bellman (HJB) equation is established using the stochastic optimal control technique. The explicit minimum probability function and the optimal investment strategy are obtained, meanwhile, a verification theorem is also proved. Numerical examples illustrate the effectiveness of our results, which indicates that the current level and the upper regulatory threshold have significant influences on the minimum probability function.
AB - In this paper, a stochastic model of asset-liability multiple is considered. To avoid the unbearable investment risk of asset price collapse, an upper regulatory threshold constraint is imposed on the asset-liability multiple. A Hamilton-Jacobi-Bellman (HJB) equation is established using the stochastic optimal control technique. The explicit minimum probability function and the optimal investment strategy are obtained, meanwhile, a verification theorem is also proved. Numerical examples illustrate the effectiveness of our results, which indicates that the current level and the upper regulatory threshold have significant influences on the minimum probability function.
KW - Asset-liability multiple
KW - minimum probability function
KW - upper regulatory threshold
UR - https://www.scopus.com/pages/publications/85081347814
U2 - 10.1080/03610926.2020.1734824
DO - 10.1080/03610926.2020.1734824
M3 - 文章
AN - SCOPUS:85081347814
SN - 0361-0926
VL - 50
SP - 5530
EP - 5553
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 23
ER -