The objective of this paper is to study the optimal consumption and portfolio choice problem of risk-controlled investors who strive to maximize total expected discounted utility of both consumption and terminal wealth. Risk is measured by the variance of terminal wealth, which introduces a nonlinear function of the expected value into the control problem. The control problem presented is no longer a standard stochastic control problem but rather, a mean field-type control problem. The optimal portfolio and consumption rules are obtained explicitly. Numerical results shed light on the importance of controlling variance risk. The optimal investment policy is nonmyopic, and consumption is not sacrificed.
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Capital Accumulation with Constraint: A Mean Field Type Control Framework
To succeed in a competitive business environment, optimal capital investment plays a significant role. A firm cannot ignore the penalty associated with carrying excessive or insufficient production capacity. We provide a model of the optimal rate of capital investment under uncertainty incorporating a penalty to study the key impact. The penalty is modeled as a squared deviation between the expected and the desired levels. The payoff functional thus incorporates a nonlinear function of the expected capital level. This control problem is of the mean field type. We obtain a closed form solution by a direct method. As expected for mean field type control problems, the optimal feedback depends not only on the current states, but also on the initial conditions. We perform numerical studies to quantitatively address how risk control in capital level deviation affects the optimal investment policy.
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- Award ID(s):
- 1905449
- PAR ID:
- 10469621
- Publisher / Repository:
- Polymat Publishing Company
- Date Published:
- Journal Name:
- Markov Processes And Related Fields
- ISSN:
- 1024-2953
- Subject(s) / Keyword(s):
- Keywords: mean field type control, capital investment, time-inconsistent solution, G\^{a}teaux differential
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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