We develop Milstein-type versions of semi-implicit split-step methods for numerical solutions of non-linear stochastic differential equations with locally Lipschitz coefficients. Under a one-sided linear growth condition on the drift term, we obtain some moment estimates and discuss convergence properties of these numerical methods. We compare the performance of multiple methods, including the backward Milstein, tamed Milstein, and truncated Milstein procedures on non-linear stochastic differential equations including generalized stochastic Ginzburg-Landau equations. In particular, we discuss their empirical rates of convergence.
We consider a complete financial market with deterministic
parameters where an investor and a fund manager have mean-variance
preferences. The investor is allowed to borrow with risk-free rate
and dynamically allocate his wealth in the fund provided his
holdings stay nonnegative. The manager gets proportional fees
instantaneously for her management services. We show that the
manager can eliminate all her risk, at least in the constant
coefficients case. Her own portfolio is a proportion of the amount
the investor holds in the fund. The equilibrium optimal strategies
are independent of the fee rate although the portfolio of each
agent depends on it. An optimal fund weight is obtained by the
numerical solution of a nonlinear equation and is not unique in
general. In one-dimensional case, the investor's risk is inversely
proportional to the weight of the risky asset in the fund. We also
generalize the problem to the case of multiple managers and
provide some examples.
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