Online Course
Financial Engineering and Risk Management Part II
Columbia University via Coursera
Overview
Class Central Tips
Financial Engineering is a multidisciplinary field involving finance and economics, mathematics, statistics, engineering and computational methods. The emphasis of FE & RM Part II will be on the use of simple stochastic models to (i) solve portfolio optimization problems (ii) price derivative securities in various asset classes including equities and credit and (iii) consider some advanced applications of financial engineering including algorithmic trading and the pricing of real options. We will also consider the role that financial engineering played during the financial crisis.
We hope that students who complete the course and the prerequisite course (FE & RM Part I) will have a good understanding of the "rocket science" behind financial engineering. But perhaps more importantly, we hope they will also understand the limitations of this theory in practice and why financial models should always be treated with a healthy degree of skepticism.
We hope that students who complete the course and the prerequisite course (FE & RM Part I) will have a good understanding of the "rocket science" behind financial engineering. But perhaps more importantly, we hope they will also understand the limitations of this theory in practice and why financial models should always be treated with a healthy degree of skepticism.
Syllabus
Mean-Variance Analysis and CAPM
-Problem formulation and solution; the efficient frontier; including the risk-free asset; the Capital Asset Pricing Model (CAPM);implications of CAPM: α, β, security and capital market lines
Practical Issues in Implementing Mean Variance
-Problems with mean-variance analysis; ETFs and leveraged ETFs; VaR and CVaR for asset allocation; survivorship bias, performance evaluation and other statistical pitfalls.
Equity Derivatives in Practice: Part I
-Problems with mean-variance analysis; ETFs and leveraged ETFs; VaR and CVaR for asset allocation; survivorship bias, performance evaluation and other statistical pitfalls.
Equity Derivatives in Practice: Part II
-More about Black-Scholes, the Greeks and delta-hedging; the volatility surface; pricing derivatives using the volatility surface; model calibration.
Credit Derivatives and Structured Products
-Mechanics and pricing of CDOs; exotic structured credit securities including CDO-squared’s and CDO-cubed’s. Risk management of these products and their role in the financial crisis.
Other Applications of Financial Engineering
-Real options; energy and commodities modeling; algorithmic trading.
Background Material
-
-Problem formulation and solution; the efficient frontier; including the risk-free asset; the Capital Asset Pricing Model (CAPM);implications of CAPM: α, β, security and capital market lines
Practical Issues in Implementing Mean Variance
-Problems with mean-variance analysis; ETFs and leveraged ETFs; VaR and CVaR for asset allocation; survivorship bias, performance evaluation and other statistical pitfalls.
Equity Derivatives in Practice: Part I
-Problems with mean-variance analysis; ETFs and leveraged ETFs; VaR and CVaR for asset allocation; survivorship bias, performance evaluation and other statistical pitfalls.
Equity Derivatives in Practice: Part II
-More about Black-Scholes, the Greeks and delta-hedging; the volatility surface; pricing derivatives using the volatility surface; model calibration.
Credit Derivatives and Structured Products
-Mechanics and pricing of CDOs; exotic structured credit securities including CDO-squared’s and CDO-cubed’s. Risk management of these products and their role in the financial crisis.
Other Applications of Financial Engineering
-Real options; energy and commodities modeling; algorithmic trading.
Background Material
-
Taught by
Martin Haugh and Garud Iyengar
Tags
Reviews
4.3 rating, based on 3 reviews
-
Zulqarnain is taking this course right now, spending 2 hours a week on it and found the course difficulty to be medium.
-
John W.
John completed this course and found the course difficulty to be very hard.
-
Rohit completed this course.
Never Stop Learning!
