Challenges in Financial Computing y Martin B. Haugh and Andrew W. Lo This Draft: March 18, 2001 Abstract One of the fastest growing areas of scienti c computing is in the nancial industry. Manyof the most basic problems in nancial analysis are still unsolved, and are surprisingly resilient to the onslaught of legions of talented researchers from many diverse disciplines. In this article, we hop e to give readers a sense of these challenges by describing a relatively simple problem that all investors face|managing a p ortfolio of nancial securities over time to optimize a particular ob jective function|and showing how complex such a problem can b ecome as real-world considerations such as taxes, preferences, and p ortfolio constraints are incorp orated into its formulation. This researchwas partially supp orted by the MIT Lab oratory for Financial Engineering. y MIT Sloan Scho ol of Management and Op erations ResearchCenter. Corresp onding author: Andrew W. Lo, 50 Memorial Drive, E52-432, Cambridge, MA 02142{1347, (617) 253{0920 (voice), (617) 258{5727 (fax),
[email protected] (email). Contents 1 Intro duction 1 2 The Portfolio Optimization Problem 1 3 Taxes 4 4 Preferences 6 5 Portfolio Constraints 7 6 Possible Solution Techniques 8 References 11 1 Intro duction One of the fastest growing areas of scienti c computing is in the nancial industry. Two decades ago, terms such as \ nancial engineering", \computational nance", and \ nancial mathematics" did not exist in common usage, yet to day these areas are regarded as distinct and enormously p opular academic disciplines, with their own journals, conferences, and professional so cieties.