Instructor: Prof. Fotios C. Harmantzis
Firstname.Lastname at stevens dot edu
 http://www.stevens.edu/fina

Course Description

An essential introduction to modern portfolio theory and optimal portfolio selection using optimization techniques such as linear programming. Addresses contingent investment decisions, deferral options, combination options, and mergers and acquisitions. Probe financial risk management, emphasizing Value-at-Risk (VAR) analysis and methods. Exploit general and parametric distributions and VAR as a risk measure. Examples from case studies are drawn from contemporary scenarios.

Prerequisites: FE610, FE620, FE621.

Requirements: Assignments require knowledge of one of the following programming languages: C++, Excel Visual Basic for Applications (VBA) or Java.

Text Books

• Elton, Gruber, Brown & Goetzmann. Modern Portfolio Theory and Investment Analysis.
  6th Edition, 2003. Wiley. ISBN 0-471-23854-6.
• Hull. Options, Futures, and Other Derivatives. 2005. Sixth Edition. Prentice Hall. ISBN: 0131499084

Grading

• Assignments-----20%
• Project --------- 25%
• Final ------------55%

Topics

• PART A: Modern Portfolio Theory
  • Mean Variance Portfolio Theory: Opportunity Set & Efficient Portfolios
  • Simplifying the Portfolio Selection Process: Single-Index Model, Multi-Index
    Models, Calculation of Efficient Frontier.
  • Utility Theory. Objective Functions. Stochastic Dominance.
  • International Diversification
  • Equilibrium Pricing Theories: The Capital Asset Pricing Model (CAPM). Alternatives
    to CAPM. Empirical Tests. The Arbitrage Pricing Theory (APT) Model.
  • Evaluation of Portfolio Performance

• PART B: Risk Management and Banking Capital
• Market Risk: Value at Risk. Econometric models for volatility.
• Credit Risk & Credit Derivatives.
• Operational Risk
• Managing Banking Capital and the Basel Accord

Selected Past Projects

• The Black-Litterman Model (W. Wang), 2006
• Portfolio Optimization: Mean-Variance vs. Resampled Efficiency (J. Provenzano), 2006
• Optimal Portfolio Construction: Single Index vs. Constant Correlation Model (M. Krause), 2006
• APT (Arbitrage Pricing Theory) Modeling: Implementation of the "Fundamental Economic Variables, Expected Returns, and Bond Fund Performance", by Elton, Gruber & Blake, appeared in J. of Finance, Vol. L, No. 4, Sept. 1995. (L. Ortega), 2005
• Implementation of the "Portfolio Optimization with Constraints on Tracking Error", by Jorion, appeared in Financial Analysts Journal, Sept. 2003, pp. 70-82. (L. Rodney), 2005
• Valuing CDO Tranches: Large Homogeneous Portfolio (LHP) approximation vs. Monte Carlo simulation vs. DJ CDX.NA.IG (S. Gregory), 2006
• Pricing of Pay-as-You-Go (PAUG) CDO via Monte Carlo Simulation (S. Edwards), 2006
• Pricing of CDOs and First-to-Default (FTD) baskets using Gaussian
  copulas (A. Alanani), 2006
• Implementation and testing of different VaR Methodologies: Historical, Parametric, Monte-Carlo Historical. (F. Lu), 2005

Recommended Books

• Grinold & Kahn. Active Portfolio Management. 2nd Edition, 2000. McGraw-Hill.
  ISBN 0-07-024882-6.
• Fabozzi, Focardi & Kolm. Financial Modeling of the Equity Market. 2006. Wiley. ISBN 0-471-69900-4
• Litterman. Modern Investment Management: An Equilibrium Approach. 2003. Wiley. ISBN 0471124109
• Alexander J. McNeil, Rüdiger Frey, and Paul Embrechts, Quantitative Risk Management: Concepts, Techniques, and Tools, Princeton Unviversity Press, 2005. ISBN: 0-691-12255-5
• Duffie, D., and K. J. Singleton, 2003, Credit risk: Pricing, measurement, and management, Princeton University Press. ISBN: 0-691-09046-7

Recommended Readings

• Risk Managment
• Artzner, P., F. Delbaen, J.-M. Eber, and D. Heath, (1999) “Coherent Measures of Risk”, Math. Fin. 9 (3), 203-228.
• Johansen, A. and D. Sornette, Winter 2001/02, Large Stock Market Price Drawdowns Are Outliers, Journal of Risk, 4(2), 69-110.
• Melo Mendes, B. V. de, and R. Brandi, 2004, "Modeling Drawdowns and Drawups in Financial Markets", Journal of Risk(Spring), pp. 53-69.
• Marcos Mailoc Lopez de Prado and Achim Peijan "Measuring Loss Potential of Hedge Fund Strategies", Journal of Alternative Investments, Summer 2004
• Harmantzis, F., L. Miao, and Y. Chien , Empirical Study of Value-at-Risk and Expected Shortfall Models with Heavy Tails, Journal of Risk Finance, 7, 2 (2006): 117 - 135.
• Portfolio Managment
• M.M. Dacorogna, R. Gencay, U.A. Muller, O.V. Pictet, "Effective return, risk aversion and drawdowns," Physica A, vol. 289, pp. 229-248 (2001)
• Fama, Eugene F. and Keneth R. French, “The Equity Premium,” The Journal of Finance, Vol. 57, No. 2, April 2002.
• Roger Clarke, Harindra de Silva, and Steven Thorley , "Portfolio Constraints and the Fundamental Law of Active Management", Financial Analysts Journal, Sep 2002, Vol. 58, No. 5: 48-66.
• Markowitz, Harry and Nilufer Usmen. 2003. “Resampled Frontiers Versus DiffuseBayes: An Experiment.” Journal of Investment Management, 4th quarter.
• Thomas M Iszorek, 2004. A Step-by-Step Guide to the Black-Litterman Model - Incorporating user specified confidence levels.
• A. Chekhlov, S. Uryasev, and M. Zabarankin. Drawdown measure in portfolio optimization. International Journal of Theoretical and Applied Finance, 8(1):13–58, 2005.
• Arnott, Robert D., Jason Hsu, and Philip Moore. 2005.“Fundamental Indexation.” Financial Analysts Journal, vol. 61, no. 2 :83–99.
• Roger Clarke, Harindra de Silva, and Steven Thorley, "Performance Attribution and the Fundamental Law", Financial Analysts Journal, Sep 2005, Vol. 61, No. 5: 70-83.

• Credit Risk
• Jarrow, Robert A & Lando, David & Turnbull, Stuart M, 1997. "A Markov Model for the Term Structure of Credit Risk Spreads," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 10(2), pages 481-523.
• Kealhofer, S. Quantifying Credit Risk I: Default Prediction, Financial Analysts Journal, 59, 1 (2003a), 30-44.
• Kealhofer, S. Quantifying Credit Risk II: Debt Valuation, Financial Analysts Journal, 59, 3 (2003b), 78-92.
• Jarrow, R. A., and Protter, P., 2004, “Structural versus reduced form models: a newinformation based perspective,” Journal of Investment Management 2, 1-10.
• Giesecke, Kay and Goldberg, Lisa R., ‘Forecasting default in the face of uncertainty’,Journal of Derivatives, 12(1), 11–25, 2004
• C.H. Hui, T.C. Wong, C.F. Lo and M.X. Huang (2005) , "Benchmarking model of default probabilities of listed companies" Journal of Fixed Income, 15(2):76-86

• Credit Derivatives
• Duffie, D., Credit Swap Valuation, Financial Analysts Journal, 55 (1999), 73-89.
• Li, D.X., “On Default Correlation: A Copula Approach” Journal of Fixed Income, 9 (2000), pp 43-54.
• Finger,C.C., V.Finkelstein, G.Pan, J.-P. Lardy, T. Ta, and J.Tierney (2002), CreditGrades, Technical document. RiskMetrics Group, Inc., New York.
• Andersen, L., J. Sidenius, and S. Basu, “All Your Hedges in One Basket,” RISK, November 2003.
• Hull, J.C., and A. White, Valuation of a CDO and nth to Default CDS Without Monte Carlo Simulation, Journal of Derivatives,12, 2 (Winter 2004) pp 8-23
• Hull, J., and A White, The Perfect Copula, working paper, University of Toronto, 2005.