Applying an interior point algorithm to asset-liability models

The development of optimization models for financial planning has drawn an increasing attention from practitioners in operations research lately. These optimization models have become more realistic, incorporating several new modeling features such as taxes, portfolio insurance strategies, turnover constraints, transaction costs, etc., to fulfill the increasing demand from portfolio managers. Operations research analysts now face larger optimization problems than a decade ago, requiring thus more reliable and efficient optimization algorithms. Interior point algorithms proved to be a superior choice to solve a large class of optimization problems that arises in financial planning-asset-liability models-as shown in this work.