TY - JOUR
T1 - Mean–variance portfolio selection under no-shorting rules: A BSDE approach
AU - Zhang, Liangquan
AU - Li, Xun
N1 - Funding Information:
L. Zhang acknowledges the financial support partly by the National Nature Science Foundation of China (Grant No. 12171053, 11701040, 11871010 & 61871058) and the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China (Grant No. 23XNKJ05).X. Li acknowledges the financial support by the Hong Kong General Research Fund, China under grants 15216720, 15221621 and 15226922.
Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/7
Y1 - 2023/7
N2 - This paper revisits the mean–variance portfolio selection problem in continuous-time within the framework of short-selling of stocks is prohibited via backward stochastic differential equation approach. To relax the strong condition in Li et al. (Li et al. 2002), the above issue is formulated as a stochastic recursive optimal linear–quadratic control problem. Due to no-shorting rules (namely, the portfolio taking non-negative values), the well-known “completion of squares” no longer applies directly. To overcome this difficulty, we study the corresponding Hamilton–Jacobi–Bellman (HJB, for short) equation inherently and derive the two groups of Riccati equations. On one hand, the value function constructed via Riccati equations is shown to be a viscosity solution of the HJB equation mentioned before; On the other hand, by means of these Riccati equations and backward semigroup, we are able to get explicitly the efficient frontier and efficient investment strategies for the recursive utility mean–variance portfolio optimization problem.
AB - This paper revisits the mean–variance portfolio selection problem in continuous-time within the framework of short-selling of stocks is prohibited via backward stochastic differential equation approach. To relax the strong condition in Li et al. (Li et al. 2002), the above issue is formulated as a stochastic recursive optimal linear–quadratic control problem. Due to no-shorting rules (namely, the portfolio taking non-negative values), the well-known “completion of squares” no longer applies directly. To overcome this difficulty, we study the corresponding Hamilton–Jacobi–Bellman (HJB, for short) equation inherently and derive the two groups of Riccati equations. On one hand, the value function constructed via Riccati equations is shown to be a viscosity solution of the HJB equation mentioned before; On the other hand, by means of these Riccati equations and backward semigroup, we are able to get explicitly the efficient frontier and efficient investment strategies for the recursive utility mean–variance portfolio optimization problem.
KW - Efficient frontier
KW - HJB equation
KW - Mean–variance portfolio selection
KW - Recursive utility
KW - Short-selling prohibition
KW - Viscosity solution
UR - http://www.scopus.com/inward/record.url?scp=85158818471&partnerID=8YFLogxK
U2 - 10.1016/j.sysconle.2023.105545
DO - 10.1016/j.sysconle.2023.105545
M3 - Journal article
AN - SCOPUS:85158818471
SN - 0167-6911
VL - 177
SP - 1
EP - 11
JO - Systems and Control Letters
JF - Systems and Control Letters
M1 - 105545
ER -