Abstract

We introduce a novel out-of-sample approach to solve a real-time investor's multiperiod portfolio choice problem in a setting with (time-varying) conditional predictability, multiple assets and downside risk control. The method involves defining a discrete set of one-period portfolio allocation policies and choosing among them at portfolio revision dates within a discrete-time stochastic dynamic programming approach so as to maximize an investor's expected utility. Our framing of the portfolio problem overcomes the curse of dimensionality that is associated with time-varying investment opportunity sets and multiple assets. We apply our technique to dynamic investment decision problems in futures markets and demonstrate its feasibility and usefulness.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.