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Another condition in which the min-max and max-min are equal is when the Lagrangian has a saddle point: (x∗, λ∗) is a saddle point of the Lagrange function L if and only if x∗ is an optimal solution to the primal, λ∗ is an optimal solution to the dual, and the optimal values in the indicated problems are equal to each other. [18 ...
Merton's portfolio problem is a problem in continuous-time finance and in particular intertemporal portfolio choice.An investor must choose how much to consume and must allocate their wealth between stocks and a risk-free asset so as to maximize expected utility.
The optimization of portfolios is an example of multi-objective optimization in economics. Since the 1970s, economists have modeled dynamic decisions over time using control theory. [14] For example, dynamic search models are used to study labor-market behavior. [15] A crucial distinction is between deterministic and stochastic models. [16]
Allocation efficiency occurs when there is an optimal distribution of goods and services, considering consumer's preference. When the price equals marginal cost of production, the allocation efficiency is at the output level. This is because the optimal distribution is achieved when the marginal utility of good equals the marginal cost.
A significant aspect of the Pareto frontier in economics is that, at a Pareto-efficient allocation, the marginal rate of substitution is the same for all consumers. [5] A formal statement can be derived by considering a system with m consumers and n goods, and a utility function of each consumer as = where = (,, …,) is the vector of goods, both for all i.
The assets in financial portfolios are, for practical purposes, continuously divisible while portfolios of projects are "lumpy". For example, while we can compute that the optimal portfolio position for 3 stocks is, say, 44%, 35%, 21%, the optimal position for a project portfolio may not allow us to simply change the amount spent on a project.
Of particular use is the property that for any fixed set of ~ values, the optimal result to the Lagrangian relaxation problem will be no smaller than the optimal result to the original problem. To see this, let x ^ {\displaystyle {\hat {x}}} be the optimal solution to the original problem, and let x ¯ {\displaystyle {\bar {x}}} be the optimal ...
Portfolio optimization is the process of selecting an optimal portfolio (asset distribution), out of a set of considered portfolios, according to some objective.The objective typically maximizes factors such as expected return, and minimizes costs like financial risk, resulting in a multi-objective optimization problem.