IIT has productized software systems based on state-of-the-art methodologies and related software used internally for some time. The common denominator is solving optimization problems in which uncertainty is explicitly incorporated in the models. The problem formulations and solution methods have been developed over many years of research and are rigorously justified from a theoretical standpoint.

IITPortf™ is an advanced system for portfolio optimization and backtesting. The core problem optimizes a weighted combination of expected return and return variance, subject to a wide range of possible constraints on asset holdings and portfolio exposures to defined risk factors. The system handles long-short and leveraged portfolios, with due consideration of transaction costs and turnover. The risk (variance) model can be based on a fundamental factor model (imported or user-defined and estimated using provided tools), a statistical factor model, or a combination of the two.

WealthiOR™ is a uniquely powerful tool for asset allocation that provides a truly dynamic portfolio optimization against a highly customizable specification of an investor’s financial situation and preferences. It computes an optimal initial allocation and a contingent allocation strategy over time that is a function of the attained account value and the time remaining in the investment horizon. The solution maximizes the expected utility of the account value stream, taking into account possible injections to and withdrawals from the account over time.

DECIS™ is a system for solving general, large-scale optimization problems for which some of the defining parameters are not known with certainty. By judiciously combining methods drawn from both optimization and simulation disciplines, DECIS™ can provide approximately optimal solutions to problems with far too many possible outcomes to allow for an exact solution. As a general-purpose tool, DECIS™ can be profitably utilized in many application domains.