Abstract: Embodiments model a series of partial trades on an investment portfolio to reduce the optimality discrepancy relative to a target optimal portfolio, and determine whether a partially rebalanced portfolio along the trading path is within a predefined threshold of statistical optimality relative to the target optimal portfolio. Certain embodiments maximize the impact of partial rebalancing of a portfolio by maximizing reduction of an optimality discrepancy while minimizing the trade cost function along the trading path from the initial portfolio toward the target optimal portfolio.

Abstract: Computer-implemented methods for constructing a risk-return optimal allocation to a set of assets, where a subset of the assets is at least partially insured or modified by the addition of derivative securities. The methods entail resampling a plurality of sets of returns consistent with a return distribution for each asset, with at least one asset modified by a derivative overlay, subject to terms of at least one contract requirement. A statistical mean of associated optimal portfolios is established, generating a resampled efficient frontier, on the basis of which a portfolio weight is selected for each asset according to a specified risk objective.

Abstract: Michaud rebalance probabilities are renormalized in the case of successive datasets, historical or simulated, where partial commonality of information is imputed to the two datasets. Two separate sets of optimization inputs correspond to a stochastic process and optimization subject to a set of constraints making the optimization analytically intractable. A subset of data drawn on the basis the first optimization input is recursively replaced with data sampled from the second optimization input, the extent of replacement governed by the extent of common information. A set of rebalance probabilities is calculated, and the Lth percentile is selected from the set of rebalance probabilities, where L is a specified confidence level. An adjusted critical value serves as a need-to-execute trigger for a single portfolio or a class of portfolios.

Abstract: A computer-implemented method and computer program product for selecting a portfolio weight (subject to specified constraints) for each of a plurality of assets of an optimal portfolio. A mean-variance efficient frontier is calculated based on expected return and standard deviation of return of each of the plurality of assets. Multiple sets of optimization inputs are drawn from a distribution of simulated optimization inputs consistent with the expected return and standard deviation of return of each of the assets and a specified level of forecast certainty, and then a simulated mean-variance efficient frontier is computed for each set of optimization inputs. A meta-resampled efficient frontier is determined as a statistical mean of associated portfolios, and a portfolio weight is selected for each asset according to a specified investment objective.

Abstract: A computer-implemented method and computer program product for selecting a portfolio weight (subject to specified constraints) for each of a plurality of assets of an optimal portfolio. A mean-variance efficient frontier is calculated based on input data characterizing the defined expected return and the defined standard deviation of return of each of the plurality of assets. Multiple sets of optimization inputs are drawn from a distribution of simulated optimization inputs consistent with the defined expected return, the defined standard deviation of return of each of the plurality of assets and then a simulated mean-variance efficient frontier is computed for each set of optimization inputs. A meta-resampled efficient frontier is determined as a statistical mean of associated portfolios among the simulated mean-variance efficient frontiers, and a portfolio weight is selected for each asset from the meta-resampled efficient frontier according to a specified investment objective.

Abstract: A computer-implemented method and computer program product for selecting a portfolio weight (subject to specified constraints) for each of a plurality of assets of an optimal portfolio. A mean-variance efficient frontier is calculated based on input data characterizing the defined expected return and the defined standard deviation of return of each of the plurality of assets. Multiple sets of optimization inputs are drawn from a distribution of simulated optimization inputs consistent with the defined expected return, the defined standard deviation of return of each of the plurality of assets and then a simulated mean-variance efficient frontier is computed for each set of optimization inputs. A meta-resampled efficient frontier is determined as a statistical mean of associated portfolios among the simulated mean-variance efficient frontiers, and a portfolio weight is selected for each asset from the meta-resampled efficient frontier according to a specified investment objective.

Abstract: A method for evaluating statistical congruence of an existing or putative portfolio with a target portfolio, both the current portfolio and the target portfolio having a plurality of assets. A mean-variance efficient portfolio is computed for a plurality of simulations of input data statistically consistent with an expected return and expected standard deviation of return, and each such portfolio is associated, by means of an index, with a specified portfolio on the mean variance efficient frontier. The number of simulations and the number of simulations periods is specified on the basis of a specified information correlation value. A statistical mean of the index-associated mean-variance efficient portfolios is used for evaluating a portfolio, in accordance with a specified balancing test, for statistical consistency with a specified risk objective and, additionally, for defining investment-relevant allocation ranges of portfolio weights.

Abstract: A method for evaluating statistical congruence of an existing or putative portfolio with a target portfolio, both the current portfolio and the target portfolio having a plurality of assets. A mean-variance efficient portfolio is computed for a plurality of simulations of input data statistically consistent with an expected return and expected standard deviation of return, and each such portfolio is associated, by means of an index, with a specified portfolio on the mean variance efficient frontier. The number of simulations and the number of simulations periods is specified on the basis of a specified information correlation value. A statistical mean of the index-associated mean-variance efficient portfolios is used for evaluating a portfolio, in accordance with a specified balancing test, for statistical consistency with a specified risk objective and, additionally, for defining investment-relevant allocation ranges of portfolio weights.

Abstract: A method for evaluating an existing or putative portfolio having a plurality of assets. A mean-variance efficient portfolio is computed for a plurality of simulations of input data statistically consistent with an expected return and expected standard deviation of return, and each such portfolio is associated, by means of an index, with a specified portfolio on the mean variance efficient frontier. A statistical mean of the index-associated mean-variance efficient portfolios is used for evaluating a portfolio for consistency with a specified risk objective.