Financial Engineering and Risk Management Part II

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Financial Engineering and Risk Management Part II

Coursera (CC)
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Description

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About this course: 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 …

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Didn't find what you were looking for? See also: Equities, Risk Management, Engineering, Software / System Engineering, and M&A (Mergers & Acquisitions).

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: 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.

Created by:  Columbia University
  • Taught by:  Martin Haugh, Co-Director, Center for Financial Engineering

    Industrial Engineering & Operations Research
  • Taught by:  Garud Iyengar, Professor

    Industrial Engineering and Operations Research Department
Commitment 13 hours videos and quizzes Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.7 stars Average User Rating 4.7See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Syllabus


WEEK 1


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


6 videos, 2 readings expand


  1. Reading: Lesson Supplements
  2. Video: Overview of Mean Variance
  3. Video: Introduction to Mean Variance in Excel
  4. Video: Efficient Frontier
  5. Video: Mean Variance with a Risk-free Asset
  6. Video: Risk-free Frontier in Excel
  7. Video: Capital Asset Pricing Model
  8. Reading: Quiz Instructions

Graded: Mean-Variance Analysis and CAPM Problem Set

WEEK 2


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.


6 videos, 2 readings expand


  1. Reading: Lesson Supplements
  2. Video: Implementation Difficulties with Mean Variance
  3. Video: Negative Exposures and Leveraged ETFs
  4. Video: Beyond Variance
  5. Video: Statistical Biases in Performance Evaluation
  6. Video: How Should Average Returns be Computed?
  7. Video: Survivorship Bias and Data Snooping
  8. Reading: Quiz Instructions

Graded: Practical Issues in Implementing Mean Variance Problem Set

WEEK 3


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.


7 videos, 2 readings expand


  1. Reading: Lesson Supplements
  2. Video: Review of the Binomial Model for Option Pricing
  3. Video: The Black-Scholes Model
  4. Video: The Greeks: Delta and Gamma
  5. Video: The Greeks: Vega and Theta
  6. Video: Risk-Management of Derivatives Portfolios
  7. Video: Delta-Hedging
  8. Video: The Volatility Surface
  9. Reading: Quiz Instructions

Graded: Equity Derivatives in Practice: Part I

WEEK 4


Equity Derivatives in Practice: Part II
about Black-Scholes, the Greeks and delta-hedging; the volatility surface; pricing derivatives using the volatility surface; model calibration.


5 videos, 1 reading expand


  1. Reading: Lesson Supplements
  2. Video: The Volatility Surface in Action
  3. Video: Why is There a Skew?
  4. Video: What the Volatility Surface Tells Us
  5. Video: Pricing Derivatives Using the Volatility Surface
  6. Video: Beyond the Volatility Surface and Black-Scholes


WEEK 5


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.


9 videos, 2 readings expand


  1. Reading: Lesson Supplements
  2. Video: Structured Credit: CDOs and Beyond
  3. Video: The Gaussian Copula Model
  4. Video: A Simple Example: Part I
  5. Video: A Simple Example: Part II
  6. Video: The Mechanics of a “Synthetic” CDO Tranche
  7. Video: Computing the Fair Value of a CDO Tranche
  8. Video: Cash and Synthetic CDOs
  9. Video: Pricing and Risk Management of CDO Portfolios
  10. Video: CDO-Squared's and Beyond
  11. Reading: Quiz Instructions

Graded: Credit Derivatives and Structured Products

WEEK 6


Other Applications of Financial Engineering
Real options; energy and commodities modeling; algorithmic trading.


8 videos, 2 readings expand


  1. Reading: Lesson Supplements
  2. Video: Liquidity, Trading Costs, and Portfolio Execution
  3. Video: Optimal Execution
  4. Video: Portfolio Execution
  5. Video: Optimal Execution in Excel 1
  6. Video: Optimal Execution in Excel 2
  7. Video: Real Options
  8. Video: Valuation of Natural Gas and Electricity Related Options
  9. Video: Real Options in Excel
  10. Reading: Quiz Instructions

Graded: Other Applications of Financial Engineering

WEEK 7


Background Material



11 videos, 1 reading expand


  1. Reading: Lesson Supplements
  2. Video: Review of Basic Probability
  3. Video: Review of Conditional Expectations and Variances
  4. Video: Review of Multivariate Distributions
  5. Video: The Multivariate Normal Distribution
  6. Video: Introduction to Martingales
  7. Video: Introduction to Brownian Motion
  8. Video: Geometric Brownian Motion
  9. Video: Review of Vectors
  10. Video: Review of Matrices
  11. Video: Review of Linear Optimization
  12. Video: Review of Nonlinear Optimization
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