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AMS 512, Capital Markets and Portfolio Theory 
Development of capital markets and portfolio theory in both continuous time and multi-period settings. Utility theory and its application to the determination of optimal consumption and investment policies. Asymptotic growth under conditions of uncertainty. Applications to problems in strategic asset allocation over finite horizons and to problems in public finance. Whenever practical, examples will use real market data. Numerical exercises and projects in a high-level programming environment will also be assigned.

Prerequisite: AMS 511 
3 credits, ABCF grading


Recommended/Optional Text:

"Risk and Asset Allocation" by Attilio Meucci, 3rd corrected printing, published by Spring, ISBN 978-3-540-22213-2 (hardcover); ISBN 978-3-642-00964-8 (softcover)

"Advanced Stochastic Models, Risk Assessment, and Portfolio Management" by Rachev, Stoyanov, Fabozzi, published by Wiley, 2008, ISBN 978-0-470-05316-4

"Investments" by Bordie, Marcus and Kane, published by McGraw-Hill, 10th edition, ISBN 978-0-077-86167-4

"Quantitative Risk Management: Concepts, Techniques and Tools" by Alexander J. McNeil, Rudiger Frey and Paul Embrechts, published by Princeton University Press, 2005, (Revised Edition); ISBN 978-1400866281

"Modern Portfolio and Analysis", published by Wiley.


AMS 512 course page

Learning Outcomes:

1) Understand the models used in portfolio selection problem.
      * Markowitz portfolio selection;
      * Capital Asset Pricing Model (CAPM);
      * Arbitrage Pricing Models (APT).

2) Demonstrate skill with optimization and statistical methods used in portfolio selection.
      * Linear programming;
      * Lagrange and KKT multipliers;
      * Linear regression;
      * Bayesian estimation.  

3) Understand the concept of Active Portfolio Management and some basic active portfolio selection methods.
      * Benchmark and excess return;
      * Forecasting Alpha;
      *Black-Litterman model.

4) Understand the importance of Risk Measures in portfolio selection and some basic risk measure methods.
      * Value at Risk (VaR);
      * Conditional VaR;
      * Copula.

5) Beware the main practical issues in portfolio management and their possible impact on the portfolio selection.

6) Use computer software to calibrate models from market data and solve portfolio selection problems numerically.