Multi-period portfolio choice and the intertemporal hedging demands for stocks and bonds: International evidence

被引:26
|
作者
Rapach, David E. [1 ]
Wohar, Mark E. [2 ]
机构
[1] St Louis Univ, Dept Econ, St Louis, MO 63108 USA
[2] Univ Nebraska, Dept Econ, Omaha, NE 68182 USA
关键词
Intertemporal hedging demand; Multi-period portfolio choice problem; Parametric bootstrap; Return predictability; DIVIDEND YIELDS; RISK-AVERSION; MARKET PARTICIPATION; DYNAMIC CONSUMPTION; TEMPORAL BEHAVIOR; EXPECTED RETURNS; ASSET-ALLOCATION; SUBSTITUTION; SELECTION; PREDICTABILITY;
D O I
10.1016/j.jimonfin.2008.12.004
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
We investigate the intertemporal hedging demands for stocks and bonds for investors in the U.S., Australia, Canada, France, Germany, Italy, and U.K. Using the methodology of Campbell et al. [Campbell, J.Y., Chan, Y.L., Viceira, L.M., 2003a. A multivariate model of strategic asset allocation. journal of Financial Economics 67(1), 41-81], we solve a multi-period portfolio choice problem for an investor in each country with an infinite horizon and Epstein-Zin-Weil utility, where the dynamics governing asset returns are described by a vector autoregressive process. We find sizable mean intertemporal hedging demands for domestic stocks in the U.S. and U.K. and considerably smaller mean hedging demands for domestic stocks in the other countries. An investor in the U.S. who has access to foreign stocks and bonds displays small mean intertemporal hedging demands for foreign stocks and bonds, while investors in Australia, Canada, France, Germany, Italy, and the U.K. who have access to U.S. stocks and bonds all exhibit sizable mean hedging demands for U.S. stocks. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:427 / 453
页数:27
相关论文
共 50 条
  • [31] Multi-period portfolio optimization using model predictive control with mean-variance and risk parity frameworks
    Li, Xiaoyue
    Uysal, A. Sinem
    Mulvey, John M.
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2022, 299 (03) : 1158 - 1176
  • [32] Multi-period mean-variance fuzzy portfolio optimization model with transaction costs
    Liagkouras, K.
    Metaxiotis, K.
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2018, 67 : 260 - 269
  • [33] Lasso-based simulation for high-dimensional multi-period portfolio optimization
    Li, Zhongyu
    Tsang, Ka Ho
    Wong, Hoi Ying
    IMA JOURNAL OF MANAGEMENT MATHEMATICS, 2020, 31 (03) : 257 - 280
  • [34] Research on Fuzzy Multi-objective Multi-period Portfolio by Hybrid Genetic Algorithm with Wavelet Neural Network
    Yu, Yechun
    Deng, Xue
    Chen, Chuangjie
    Cheng, Kai
    ENGINEERING LETTERS, 2020, 28 (02) : 594 - 600
  • [35] Multi-period mean-semi-entropy portfolio management with transaction costs and bankruptcy control
    Zhou, Jiandong
    Li, Xiang
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 12 (01) : 705 - 715
  • [36] Surrogate-assisted hyper-parameter search for portfolio optimisation: multi-period considerations
    van Zyl, Terence L.
    Woolway, Matthew
    Paskaramoorthy, Andrew
    NEURAL COMPUTING & APPLICATIONS, 2023,
  • [37] Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach
    Cui, Tianxiang
    Du, Nanjiang
    Yang, Xiaoying
    Ding, Shusheng
    TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2024, 198
  • [38] Multi-period mean-variance portfolio optimization based on Monte-Carlo simulation
    Cong, F.
    Oosterlee, C. W.
    JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2016, 64 : 23 - 38
  • [39] Robust multi-period portfolio model based on prospect theory and ALMV-PSO algorithm
    Liu, Jiahe
    Jin, Xiu
    Wang, Tianyang
    Yuan, Ying
    EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (20) : 7252 - 7262
  • [40] Multi-period uncertain portfolio optimization model with minimum transaction lots and dynamic risk preference
    Dai, Yuanzhen
    Qin, Zhongfeng
    APPLIED SOFT COMPUTING, 2021, 109 (109)