Model and Solver Integration for Interoperability between Options and their Evaluation Algorithms in Financial Decision Support Systems

As the financial option markets grow, financial decision support systems need an efficient framework that enables us to mix and match options and their various evaluation algorithms according to diverse pricing and evaluation purposes. Under such many-to-many relationships between options and algorithms, the systems often encounter inefficiency problems caused by duplicated developments of their interfaces when adding or modifying the options or the algorithms. To resolve such problems, this paper proposes a system framework for dynamic integration of options and algorithms based on the model management system perspective. Specifically, the detailed mapping relationships between the parameters of options and those of algorithms are managed with a separate mapping table, so the addition or the modification is easily incorporated only with altering the table without affecting the integration processes.