FIN 460 - Dynamic Asset Pricing Theory

• Instructors:

  • Dr Eymen Errais
  • Dr. Bechir Bouzid

• Email:

  • eymen@errais.com
  • bbouzid@worldbank.org

• Pre-requisite:

  • None (with some basic/intermediate knowledge of R software)

Course Description

This course introduces students to the tools, concepts, and issues of financial modelling. This course is an introduction to multiperiod models in finance, mainly pertaining to optimal portfolio choice and asset pricing. The course begins with discrete-time models for portfolio choice and security prices, and then moves to a continuous-time setting. The topics then covered include advanced derivative pricing models, models of the term structure of interest rates, the valuation of corporate securities, portfolio choice in continuous-time settings, and finally over-the-counter asset pricing models. Upon completion of this course, the students will master different asset classes pricing theories and will be able read and implement scientific finance pricing papers. This course is a must for people looking to work on trading floors and asset management firms as well as students pursuing quantitative finance graduate studies.

This course will include sessions on introduction to econometric models governing the analysis of financial and business data. Those sessions will discuss selected analytical methods that are useful in analyzing and forecasting financial data and will mainly focus on extensive hands-on applications using R program. The goal is to provide a thorough understanding of some of the commonly used analytical tools for financial and business data modeling.

Course Learning Outcomes

Upon successful completion of the course, students will be able to:

• Acquire and understand the central issues of how to model financial phenomena using stochastic processes.
• Enhance their ability to use different kinds of technical tools such as stochastic modelling, statistics & probability as well stochastic calculus.
• Learn how to price and hedge financial derivatives
• Gain experience in analyzing financial and business data and know how and when to use some of the methods learned.
• Model some of the dynamic features of financial series to better understand its past evolution and forecast its future trends.
• Apply different analytical tools and techniques to unpack useful insights from data that could be used in a data-driven business decision.

Course Materials

• Elementary Stochastic Calculus with Finance view (6th Edition) by Thomas Mikosch.
• Stochastic calculus for finance I and II by Steven Shreve.
• Problems and Solutions in Mathematical Finance, by Eric Chin, Dian Net and Sverrir Olafsson. Wiley
• Derivatives Analytics with Python by Yves Hilpisch. Wiley

Course Content

• Probability Space and Stochastic Processes
• Conditional expectations
• Martingales
• Brownian Motion
• Stochastic calculus
• Interest rate models
• Credit models

TBS Grading Scale