Courses2017-03-29T19:59:50+00:00

ECO525 – Asset Pricing

Introduction to asset pricing covering theory in both continuous and discrete time to study dynamic portfolio choice; derivative pricing; the term structure of interest rates; and intertemporal asset-pricing and consumption-based models. Pre-requisites: All required courses in micro, macro and econometrics at the first-year PhD level.

ECO526/FIN526 – Corporate Finance

Introduction to corporate finance covering theories and empirical evidence about principal-agent models of firm managerial structure, takeover bids, capital structure, corporate governance; regulation of financial markets; financial markets and institutions with a focus on asymmetric information, transaction costs, or both; dynamic models of market making; and portfolio manager performance evaluation. Pre-requisite: ECO 525.

ECO527/FIN527 – Financial Modelling

Advanced asset pricing and corporate finance including a selection from: models of financial crises and bubbles; interaction between finance and macroeconomics, derivative pricing in incomplete markets; tests of asset pricing models and associated anomalies; models of investor behavior; financial econometrics, including tests of asset pricing models and methods for high frequency data. Pre-requisites: ECO 525 and 526 (526 may be taken concurrently).

ECO529 – Financial and Monetary Economics

The recent Great Recession led to a transformational rethinking. In Monetary Economics the key friction shifted from price stickiness and wage rigidities to financial frictions. In financial regulation the focus shifted from micro- to macro-prudential regulation and new systemic risk measures. The course also covers interaction between monetary policy and macro-prudential policy as well as spillover analysis and the implications for the international financial architecture. In terms of economic methodology, the course teaches students new advanced tools, including formal modeling, economic dynamical systems in continuous time, strategic interactions, asymmetric information, and modern welfare analysis. The empirical component would range from model estimation, calibration to reduced form analysis.

ORF526 – Probability Theory

This course measures spaces, random variables, expectation, characteristic functions, law of large numbers, central limit theorem, conditioning, Martingales, and Markov chains.

ORF527 – Stochastic Calculus

An introduction to stochastic calculus based on Brownian motion. Topics include: construction of Brownian motion; martingales in continuous time; the Ito integral; localization; Ito calculus; stochastic differential equations; Girsanov’s theorem; martingale representation; Feynman-Kac formula.

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