Computer Science Approaches to Finance Problems: Computational Complexity and Efficient Algorithms

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PI: Ming-Yang KaoInstitution: Yale UniversityProposal Number: 9988376In scientific disciplines, significant issues are sometimes assumedaway by overmodeling, which results in lost knowledge. Suchovermodeling is often caused by analytical or computational difficultyof the issues involved. By shifting the existing balance amongmodeling, analytical, and computational components of the currentsolution to an issue, one inevitably discovers new technologies.Motivated by this research philosophy, this project has three generalthemes. The first is to explore trade-offs between modeling andcomputation in finance with emphasis on advancing computationaltechnologies for practical and theoretical finance problems. Thesecond is to develop finance ideas to help solve computer scienceproblems. The third is to formulate novel finance problems whichbreak away from traditional paradigms of finance research.This project pursues these three themes in five interrelated areas ofcomputational finance: (1) market modeling, (2) investment and tradingalgorithms, (3) risk management, (4) market index design, and (5)auctions.For the area of market modeling, the main goal is to study short-termpredictability of stock markets using agent-based approaches. Themodels established will be used to test algorithms developed for otherparts of the project.For the area of investment and trading algorithms, this projectfocuses on two fundamental issues: (1) what sorts of information canbe used to enhance the performance of a portfolio and (2) how tomeasure the performance of investment and trading algorithms. Resultsin this area can be useful for long-term investors such as those whosave for retirement.For the area of risk management, this project investigates two basicissues: (1) how to assess the risk of a portfolio of assets and (2)how to design optimal portfolios which meet security requirements.Results in this area may be used to help institutional investorsdetect and minimize unwanted risks.For the area of market index design, novel optimization problems willbe formulated to help design portfolios which are easier to managethan popular market indices but can track or outperform the indices.For the area of auctions, the primary goal is to use auctionalgorithms to design solutions to computer science problems. To thisend, the project will identify auction primitives which can be used toconstruct complicated auction mechanisms.