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Day 1 - December 11, 2009
8:30-9:00 Registration and Opening Address
Petter Kolm, Deputy Director of Mathematics in Finance M.S. Program, Courant Institute
Morning Session (9:15-12:30)

Part I. Markets and Data

Lee Maclin
  • Mechanics of trading
    • Limit and market orders
    • The two-way double auction
    • Order placement rules
    • Exchange mechanisms
    • Order management systems and trading platforms
    • Direct market access pipes
  • Working with high frequency data
    • The TAQ data set
    • The Nasdaq aggregate data set

Part II. Optimal Execution and Market Impact Modeling

Petter Kolm

  • Introduction to the calculus of variations
  • Optimal execution of portfolio transactions
    • Permanent and temporary impact
    • Implementation shortfall
    • The Almgren-Chriss model
    • The efficient frontier of optimal execution
  • Market impact models
    • Almgren et al.
    • Models utilizing public data
Afternoon Session (1:30-5:00)

Part III. Robust Portfolio Optimization with Transaction Costs

Petter Kolm

  • The Black-Litterman model
  • Robust portfolio optimization
  • Incorporating transaction costs into portfolio optimization

Part IV. Risk Models

Eran Fishler

  • Factor models and covariance matrix estimation
    • Multifactor models
    • Some results from random matrix theory
    • Covariance matrix “cleaning”
    • PCA, linear regression, shrinkage and ridge regression
    • Shrinkage estimators of regression coefficients
    • Ridge regression

 

Day 2 - December 12, 2009
Morning Session (8:30-12:30)

Part I. Statistical Arbitrage in the U.S. Equities Market

Marco Avellaneda

  • Long-short equity
  • Hedging instruments
  • Back-testing

Part II. Factor-Based Quantitative Trading Strategies

Joseph Cerniglia

  • Quantitative trading strategies
  • Standard themes
  • Data
  • Back-testing methodologies
 Afternoon Session (1:30-5:00)

Part III. The Optimal Theta Framework

Lee Maclin
  • Introduction: Dynamic portfolio analysis
  • Traditional rebalancing
  • The dynamic portfolio framework
  • A simulation framework for dynamic portfolio analysis
  • Optimal betting (Optimal f) and optimal growth portfolios

Part IV. Dynamic Portfolio Analysis

Petter Kolm

  • Stochastic Linear Quadratic Gaussian (LQG) Regulator
  • Dynamic portfolio analysis with transaction costs

 
 
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