TY - JOUR
T1 - Optimal tracking portfolio with a ratcheting capital benchmark
AU - Bo, Lijun
AU - Liao, Huafu
AU - Yu, Xiang
N1 - Funding Information:
\ast Received by the editors June 29, 2020; accepted for publication (in revised form) April 20, 2021; published electronically June 24, 2021. https://doi.org/10.1137/20M1348856 \bfF \bfu \bfn \bfd \bfi \bfn \bfg : The first author is supported by the Natural Science Foundation of China under grants 11971368 and 11961141009 and by the Key Research Program of Frontier Sciences of the Chinese Academy of Science under grant QYZDBSSW-SYS009. The second author is supported by Singapore MOE AcRF grant R-146-000-271-112. The third author is supported by the Hong Kong Early Career Scheme under grant 25302116. \dagger School of Mathematics and Statistics, Xidian University, Xi'an, 710071, China (lijunbo@ustc. edu.cn). \ddagger Department of Mathematics, National University of Singapore, Singapore 119076, Singapore ([email protected]). \S Department of Applied Mathematics, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong ([email protected]).
Publisher Copyright:
© 2021 Society for Industrial and Applied Mathematics
PY - 2021/6
Y1 - 2021/6
N2 - This paper studies finite horizon portfolio management by optimally tracking a ratcheting capital benchmark process. It is assumed that the fund manager can dynamically inject capital into the portfolio account such that the total capital dominates a nondecreasing benchmark floor process at each intermediate time. The tracking problem is formulated to minimize the cost of accumulated capital injection. We first transform the original problem with floor constraints into an unconstrained control problem, but under a running maximum cost. By identifying a controlled state process with reflection, the problem is further shown to be equivalent to an auxiliary problem, which leads to a nonlinear Hamilton-Jacobi-Bellman (HJB) equation with a Neumann boundary condition. By employing the dual transform, the probabilistic representation, and some stochastic flow analysis, the existence of a unique classical solution to the HJB equation is established. The verification theorem is carefully proved, which gives a complete characterization of the feedback optimal portfolio. The application to market index tracking is also discussed when the index process is modeled by a geometric Brownian motion.
AB - This paper studies finite horizon portfolio management by optimally tracking a ratcheting capital benchmark process. It is assumed that the fund manager can dynamically inject capital into the portfolio account such that the total capital dominates a nondecreasing benchmark floor process at each intermediate time. The tracking problem is formulated to minimize the cost of accumulated capital injection. We first transform the original problem with floor constraints into an unconstrained control problem, but under a running maximum cost. By identifying a controlled state process with reflection, the problem is further shown to be equivalent to an auxiliary problem, which leads to a nonlinear Hamilton-Jacobi-Bellman (HJB) equation with a Neumann boundary condition. By employing the dual transform, the probabilistic representation, and some stochastic flow analysis, the existence of a unique classical solution to the HJB equation is established. The verification theorem is carefully proved, which gives a complete characterization of the feedback optimal portfolio. The application to market index tracking is also discussed when the index process is modeled by a geometric Brownian motion.
KW - Nondecreasing capital benchmark
KW - Optimal tracking
KW - Probabilistic representation
KW - Running maximum cost
KW - Stochastic flow analysis
UR - http://www.scopus.com/inward/record.url?scp=85109416168&partnerID=8YFLogxK
U2 - 10.1137/20M1348856
DO - 10.1137/20M1348856
M3 - Journal article
AN - SCOPUS:85109416168
SN - 0363-0129
VL - 59
SP - 2346
EP - 2380
JO - SIAM Journal on Control and Optimization
JF - SIAM Journal on Control and Optimization
IS - 3
ER -