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Doctoral – Course Description

Microeconomics – Game Theory, with emphasis on Contract Theory. The aim of the course is twofold: first, to provide a rigorous treatment of the analytical tools of game theory and modern microeconomics; second, to address comprehensively the main topics of information economics and contract theory, with emphasis given to applications in banking and corporate finance. The main topics are: Strategic Games, Dynamic Games, Information and the Principal-Agent Problem, Adverse Selection, Signalling Models, Moral Hazard, Mechanism Design and Auctions. By the end of the course, the students should  have a deep understanding of the strategic foundations of financial markets and the ability to develop their own theoretical models.

Quantitative Methods. This course aims to deepen students’ knowledge in the mathematical and probability theory used in modern finance. It covers a wide range of topics in the fields of Measure Theory (measure spaces, Lebesgue Integral), Probability Theory (probability space, conditional expectation, convergence of random variables, laws of large numbers, central limit theorems), Stochastic Processes (martingales, convergence of stochastic processes, functional central limit theorem, Brownian motion), and Stochastic Calculus (stochastic integral, Ito’s formula, stochastic differential equations).

Econometrics. This course teaches the theory of the Linear Regression Model (least squares, vector autoregressive models, linear models with a unit root, cointegration) as well as topics such as Rational Expectations. Emphasis is placed on rigorous mathematical proofs, using matrix algebra. As a result, the students become proficient in matrix algebra, the Theory of Difference Equations and their application in econometrics.

Financial Theory I – Asset Pricing Theory. This course aims at providing a deep understanding of the pricing of stocks and other financial assets. To this end, it covers the theory of asset pricing and the related empirical literature. It places special emphasis on the presentation of a coherent theoretical framework which encompasses all asset pricing models as special cases. Additionally, the course examines the linkages between the asset pricing models and portfolio selection.

Time Series Analysis. This course presents the basic types of time series that are used in finance: Autoregressive, Moving average, ARMA, ARCH, GARCH models; and their vector equivalents, VAR, VARMA. It also covers state-space models and Kalman filtering.

Financial Theory II – Corporate Finance. This course analyzes the main parameters of investment and financing decisions of firms. Specifically, it covers capital budgeting, the Modigliani – Miller theorem and its extensions, capital structure under asymmetric information, dividend policy and stock repurchases, plus mergers and acquisitions.

Financial Theory ΙΙΙ – Continuous Time Finance. Brief review of Stochastic Calculus: integration with respect to continuous martingales, Ito’s change of variable formula, Girsanov theorem, stochastic differential equations, and diffusion processes. Dynamic Stochastic Control: introduction to finite horizon control problems, the method of dynamic programming, the Hamilton-Jacobi-Bellman pde, Merton’s problem, and the convex duality approach. Continuous-time stochastic models for asset-prices: notions of trading strategies, arbitrage opportunities, contingent claims, hedging and pricing, the Fundamental Theorem (equivalence between the absence of arbitrage opportunities and the existence of equivalent martingale measures), complete and incomplete markets, fair price as an expectation under the equivalent martingale measure and as the solution to a pde, and the example of the Black-Scholes formula.

Special Topics in Finance Ι. This course is adapted to the needs and interests of each incoming doctoral class. In the past, it covered topics such as financial intermediation theory, the economics of financial system regulation and topics in econometrics and international finance.