FINANCIAL MARKET MODELS
Syllabus
Updated A.Y. 2015-2016
Preliminary version: January 13, 2016
Office Hours
I have an open door policy, but please e-mail me ahead of time if you want to make sure I am in.
contact: c.robotti@imperial.ac.uk
Overview
This is a course on discrete time and continuous time financial models. The topics covered are chosen among those that require a rather intensive use of quantitative modeling tools. In particular, we will focus on mean-variance analysis, optimal portfolio selection, static and dynamic asset-pricing models, return predictability, the term structure of interest rates, and option pricing. While you may have seen these topics in other classes, this course emphasizes a hands-on modeling experience. Students will be required to analyze data and participate in class discussions.
Programming requirements
The emphasis of the course is on understanding how financial models can produce useful answers to economic questions. Therefore, this is not a course in computer programming. Only the use of Matlab is required. On the other hand, those among you who have prior programming experience should feel free to complete assignments in any language of their choice.
Readings
The class slides are your main source for preparing for this course. The two suggested books are (i) Asset Pricing by John Cochrane (2005) and (ii) Empirical Dynamic Asset Pricing by Kenneth Singleton (2006).
Prerequisites
Students must have a basic knowledge of matrix algebra, calculus, statistics, and econometrics.
Course Assessment
• Class participation, 15%
• Group assignments, 30%
• Final exam, 55%
List of topics
Week 1: Asset Pricing Theory
• Lesson 1: Contingent claims, risk-neutral probabilities, law of one price and existence of a stochastic discount factor, no-arbitrage and positive discount factors.
• Lesson 2: Mean-variance frontier and beta representations, relation between mean-variance frontiers and discount factors, Hansen-Jagannathan bounds, tests of spanning and intersection, implications of existence and equivalence theorems.
• Lesson 3: Mean-variance analysis and portfolio optimization, introducing higher moments, shrinkage approach to asset allocation, optimized portfolios versus equally-weighted portfolios.
Week 2: Asset Pricing Theory
•Lesson 4: Capital asset pricing model (CAPM), Intertemporal CAPM (ICAPM), arbitrage pricing theory (APT), APT versus ICAPM, the Fama-French 3 and 5-factor models.
•Lesson 5: Conditioning information, scaled payoffs, conditional and unconditional models, scaled factors, pricing kernels and dynamic asset pricing models (DAPMs).
•Lesson 6: Economic motivations for examining asset return predictability, evidence on stock-return predictability, a digression on unit roots in time series, tests for serial correlation in returns.
Week 3: Estimating and Evaluating Asset-Pricing Models
• Lesson 7: Generalized method of moments (GMM) in explicit discount factor models, interpreting the GMM procedure, applying GMM, general GMM formulas.
• Lesson 8: Testing moments, standard errors by anything by delta method, using GMM for regressions, prespecified moments.
• Lesson 9: Regression-based tests of linear factor models, time-series regressions, cross-sectional regressions, Fama-MacBeth procedure.
Week 4: Estimating and Evaluating Asset-Pricing Models
• Lesson 10: GMM for linear factor models in discount factor form, the case of excess returns, testing for priced factors, mean-variance frontier and performance evaluation, testing for characteristics.
• Lesson 11: Performance measures: Hansen-Jagannathan distance and cross-sectional R2s, horse races, pairwise and multiple model comparison.
• Lesson 12: Maximum-likelihood estimation, traded and non-traded factors, model misspecification, lack of identification.
Week 5: Term Structure of Interest Rates
• Lesson 13: Definition and notation, yield curve and expectations hypothesis, term structure models.
• Lesson 14: Continuous-time term structure models, Vasicek (1977), Cox, Ingersoll, and Ross (1985), affine model.
• Lesson 15: Unspanned factors, heterogeneous beliefs, extensions.
Week 6: Option Pricing
• Lesson 16: Background, one-period and multiple-period models, binomial pricing.
• Lesson 17: Martingales, Ito’s lemma, Black-Scholes formula.
• Lesson 18: Option pricing without perfect replication, no-arbitrage pricing, one-period good-deal bounds, multiple periods and continuous time, extensions, other approaches.