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

PI: Ming-Yang kaming - yang institution: Yale university提案号：9988376在科学学科中，重要的问题有时会被过度建模所忽略，从而导致知识的丢失。这种过度建模通常是由所涉及问题的分析或计算困难引起的。通过将当前解决方案的建模、分析和计算组件之间的现有平衡转移到某个问题，人们不可避免地会发现新技术。在这个研究理念的激励下，这个项目有三个主题。第一个是探索金融建模和计算之间的权衡，重点是推进实际和理论金融问题的计算技术。二是发展金融思想，帮助解决计算机科学问题。三是提出新的金融问题，突破传统的金融研究范式。这个项目在计算金融的五个相互关联的领域中研究这三个主题：(1)市场建模，(2)投资和交易算法，(3)风险管理，(4)市场指数设计，(5)拍卖。在市场建模领域，主要目标是使用基于主体的方法研究股票市场的短期可预测性。建立的模型将用于测试为项目其他部分开发的算法。对于投资和交易算法领域，本项目侧重于两个基本问题：(1)哪些类型的信息可用于提高投资组合的绩效；(2)如何衡量投资和交易算法的绩效。结果，这一领域对长期投资者（如那些为退休而储蓄的人）很有用。对于风险管理领域，本项目研究了两个基本问题：(1)如何评估资产组合的风险；(2)如何设计满足安全要求的最佳投资组合。该领域的研究结果可用于帮助机构投资者发现和减少不必要的风险。在市场指数设计领域，将制定新的优化问题来帮助设计投资组合，使其更容易管理流行的市场指数，但可以跟踪或优于指数。对于拍卖领域，主要目标是使用拍卖算法来设计计算机科学问题的解决方案。为此，该项目将确定可用于构建复杂拍卖机制的拍卖原语。

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.