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Financial Engineering and Risk Management

Martin Haugh, Garud Iyengar, and Ali Hirsa

This specialization is intended for aspiring learners and professionals seeking to hone their skills in the quantitative finance area. Through a series of 5 courses, we will cover derivative pricing, asset allocation, portfolio optimization as well as other applications of financial engineering such as real options, commodity and energy derivatives and algorithmic trading. Those financial engineering topics will prepare you well for resolving related problems, both in the academic and industrial worlds.

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What's inside

Five courses

Introduction to Financial Engineering and Risk Management

(0 hours)

Introduction to Financial Engineering and Risk Management provides a fundamental introduction to fixed income securities, derivatives, and their pricing models. It covers probability, optimization, fixed income securities, swaps, options, and option pricing using the Binomial and Black-Scholes Models.

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Term-Structure and Credit Derivatives

(0 hours)

This course focuses on capturing the evolution of interest rates and providing deep insight into credit derivatives. It discusses term structure lattice models, cash accounts, fixed income derivatives, model calibration, credit derivatives, Credit Default Swaps, securitization, asset backed securities, Mortgage Backed Securities, and Collateralized Mortgage Obligations.

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Optimization Methods in Asset Management

(0 hours)

This course focuses on applications of optimization methods in portfolio construction and risk management. It discusses portfolio construction via Mean-Variance Analysis and Capital Asset Pricing Model (CAPM) in an arbitrage-free setting. It also introduces Value at Risk (VaR) and Conditional Value at Risk (CVaR) as risk measurements, and Exchange Traded Funds (ETFs), which play an important role in trading and asset management.

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Advanced Topics in Derivative Pricing

(0 hours)

This course covers advanced topics in derivative pricing. It begins with the Black-Scholes model and Greeks, then explores risk management and implied volatility. The course also covers credit derivatives, structured products, and real options.

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Computational Methods in Pricing and Model Calibration

(0 hours)

This course covers computational methods in pricing and model calibration for options and interest rate products. Topics include option types, pricing techniques (FT, FFT), models (BMS, Heston, VG), bid-ask prices, implied volatility, model calibration, interest rates, forward rates, spot rates, swap rates, term structure, LIBOR curves, swap curves, bond pricing, swap pricing, interest rate model calibration techniques, Vasicek model, CIR model.

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Learning objectives

1. valuing options, swaps, forwards, futures, and other complex financial derivatives using stochastic models
2. develop a systematic, data-driven approach to formulating modeled returns and risks for significant asset classes and optimal portfolios

3. back test and implement trading models and signals in an active, live trading environment

1. valuing options, swaps, forwards, futures, and other complex financial derivatives using stochastic models
2. develop a systematic, data-driven approach to formulating modeled returns and risks for significant asset classes and optimal portfolios
3. back test and implement trading models and signals in an active, live trading environment

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Time

3 hours

Level

Intermediate

Via

Coursera

Institution

Columbia University

Instructors

Martin Haugh

Garud Iyengar

Ali Hirsa

Level

Intermediate

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