A NONLINEAR CONTROL POLICY USING KERNEL METHOD FOR DYNAMIC ASSET ALLOCATION(<Special Issue>SCOPE (Seminar on Computation and OPtimization for new Extensions))
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概要
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We build a computational framework for determining an optimal dynamic asset allocation over multiple periods. To do this, we use a nonlinear control policy, which is a function of past returns of investable assets. By employing a kernel method, the problem of selecting the best control policy from among nonlinear functions can be formulated as a convex quadratic optimization problem. Furthermore, we reduce the problem to a linear optimization problem by employing L1-norm regularization. A numerical experiment was conducted wherein scenarios of the rate of return of investable assets were generated by using a one-period autoregressive model, and the results showed that our investment strategy improves an investment performance more than other strategies from previous studies do.