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UW M.S. Computational Finance & Risk Management
  • 🎓Master of Science in Computational Finance & Risk Management
  • 📈RESEARCH
    • 🎓Graduate Thesis
  • đŸ™ī¸Outside the Classroom
    • đŸĸParametric Fellowship
    • đŸ–Ĩī¸Algorithmic Trading @ University of Washington
    • âš–ī¸Graduate and Professional Student Senate
    • đŸ›Šī¸Husky Flying Club
    • đŸ–Ĩī¸IMC Prosperity
  • đŸ–Ĩī¸WorldQuant IQC
  • 📈OVERVIEW
    • âŒ¨ī¸MS-CFRM
  • 📈First Quarter
    • 1ī¸âƒŖCFRM 501: Investment Science
    • 1ī¸âƒŖCFRM 504: Options & Other Derivatives
    • 1ī¸âƒŖCFRM 506: Financial Data Analysis
  • 📈Second Quarter
    • 2ī¸âƒŖCFRM 502: Financial Data Science
    • 2ī¸âƒŖCFRM 505: Monte Carlo Methods in FInance
    • 2ī¸âƒŖCFRM 540: Risk in Financial Institutions
  • 📈Third Quarter
    • 3ī¸âƒŖCFRM 503: Asset Allocation & Portfolio Management
    • 3ī¸âƒŖCFRM 509: Ethics in the Finance Profession
    • 3ī¸âƒŖCFRM 521: Machine Learning in Finance
    • 3ī¸âƒŖCFRM 523: Advanced Trading Systems
    • 3ī¸âƒŖCFRM 532: Endowment & Institutional Investment Management
  • 📈FOURTH QUARTER
    • 4ī¸âƒŖCFRM 542: Credit Risk Management
  • 📎EXTRAS
    • đŸ–ŧī¸Gallery
    • 📔Guest Book
    • Website
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  1. First Quarter

CFRM 501: Investment Science

This course really puts the "Applied" in Applied Mathematics. The whole course was a mapping of everything I learned from coursework prior to how I should expect to see it in quantitative finance.

Reading Material:

  • Investment Science, D. Luenberger, 1997.

  • Asset Management: A Systematic Approach to Factor Investing, A. Ang, 2014.

  • Asset Pricing and Portfolio Choice, K. Back, 2017.

This course is an introduction to the mathematical, statistical and economic foundations of Finance. Learning of the theoretical concepts will be reinforced through use of computing exercises. The material is similar in scope to an MBA level investments course, but at a significantly higher quantitative level. The course aims to establish various quantitative methods for investment decision-making in the context of modern financial markets.

  1. Theory of Capital Markets and Returns

  2. Expected Utility Theory

  3. Mean-Variance Analysis

  4. The Capital-Asset Pricing Model

  5. Pricing Factors and Statistical Factors

  6. Arbitrage and Equilibrium

  7. Rational Expectations and Market Efficiency

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Last updated 1 year ago

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