Financial Engineering and Risk Management Part II

Columbia University

About this Course

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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.

Learner Career Outcomes

27%

started a new career after completing these courses

44%

got a tangible career benefit from this course

22%

got a pay increase or promotion

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 17 hours to complete

English

Subtitles: English

Skills you will gain

Real Options ValuationDerivative (Finance)Risk ManagementReal Options

Learner Career Outcomes

27%

started a new career after completing these courses

44%

got a tangible career benefit from this course

22%

got a pay increase or promotion

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 17 hours to complete

English

Subtitles: English

Instructors

Instructor rating

4.32/5 (30 Ratings)

Martin Haugh

Co-Director, Center for Financial Engineering

Industrial Engineering & Operations Research

367,373 Learners

2 Courses

Garud Iyengar

Professor

Industrial Engineering and Operations Research Department

367,373 Learners

2 Courses

Offered by

Columbia University

For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries and service to society.

Syllabus - What you will learn from this course

Week

Week 1

2 hours to complete

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

2 hours to complete

6 videos (Total 97 min), 2 readings, 1 quiz

6 videos

Overview of Mean Variance19m

Introduction to Mean Variance in Excel9m

Efficient Frontier19m

Mean Variance with a Risk-free Asset14m

Risk-free Frontier in Excel13m

Capital Asset Pricing Model20m

2 readings

Lesson Supplements10m

Quiz Instructions10m

1 practice exercise

Mean-Variance Analysis and CAPM Problem Set30m

Week

Week 2

3 hours to complete

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.

3 hours to complete

6 videos (Total 103 min), 2 readings, 1 quiz

6 videos

Implementation Difficulties with Mean Variance20m

Negative Exposures and Leveraged ETFs14m

Beyond Variance13m

Statistical Biases in Performance Evaluation17m

How Should Average Returns be Computed?14m

Survivorship Bias and Data Snooping23m

2 readings

Lesson Supplements10m

Quiz Instructions10m

1 practice exercise

Practical Issues in Implementing Mean Variance Problem Set30m

Week

Week 3

3 hours to complete

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.

3 hours to complete

7 videos (Total 112 min), 2 readings, 1 quiz

7 videos

Review of the Binomial Model for Option Pricing10m

The Black-Scholes Model8m

The Greeks: Delta and Gamma19m

The Greeks: Vega and Theta18m

Risk-Management of Derivatives Portfolios16m

Delta-Hedging14m

The Volatility Surface23m

2 readings

Lesson Supplements10m

Quiz Instructions10m

1 practice exercise

Equity Derivatives in Practice: Part I30m

Week

Week 4

2 hours to complete

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.

2 hours to complete

5 videos (Total 82 min), 1 reading

5 videos

The Volatility Surface in Action9m

Why is There a Skew?14m

What the Volatility Surface Tells Us17m

Pricing Derivatives Using the Volatility Surface21m

Beyond the Volatility Surface and Black-Scholes19m

1 reading

Lesson Supplements10m

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Financial Engineering and Risk Management Part II