Use case
A fuzzy hybrid integrated framework for portfolio optimization in private banking
In this article from "Expert Systems with Applications," financial services researchers delve into the use of Artelys Knitro for decision-making in complex and uncertain environments, aiming to select the optimal alternative. Results include portfolio optimization, enabling the identification of the best approach while considering regulatory concerns and investor objectives.

Portfolio optimization is the process of finding the best portfolio allocation in terms of risk/reward profile of the investment. When planning personal finance strategies, financial institutions use a questionnaire to assess which products, services, and operations are best suited to their clients’ needs.

The objective of this process is to place the investor in a suitable category, which depends on matters such as risk, the objective of the investment, and the client’s knowledge of the market. Simultaneously, banks classify their funds into categories based on market and credit risks. Banks then propose a portfolio that maximizes the adequacy of the investments for the client’s profile, the reward of the portfolio, and to minimize the portfolio risk.

The authors propose a multi-step procedure for personal investment portfolio selection in private banking, combining fuzzy decision-making and optimization-based approaches.

The efficiency of Artelys Knitro is exploited within this procedure, allowing to consider simultaneously regulation issues, and investors’ objectives and preferences.

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You’re not familiar with nonlinear optimization? This tutorial will present some examples of nonlinear problems for various applications. You will discover nonlinear programming methods using the Artelys Knitro solver in a Python notebook, through different examples.

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