Introduction to the theory and practice of mathematical finance: basics of derivative securities; interest rate and bonds; forward and futures contracts, hedging using futures contracts; option contracts and arbitrage relationship; binomial model, no-arbitrage pricing, risk-neutral pricing, and American options pricing; Brownian motion, Black-Scholes-Merton model, delta hedging, Greek letters, implied volatility, and volatility smile; classical and advanced portfolio management and execution models and strategies.

Learning Objectives

At the end of the term, students will be able to:

  • Master the basics of derivatives, such as the mechanics, properties and functions of futures and options
  • Use derivatives to conduct trading and hedging
  • Price options using appropriate models including Black-Scholes-Merton model, binomial model and no-arbitrage principle
  • Design basic portfolio management and execution strategies

Measurable Outcomes

  • Master the basics of derivatives, including terms, characteristics, pricing and execution.
  • Use appropriate trading strategies based on the derivative properties, such as straddle strategy and butterfly strategy.
  • Construct hedging strategies based on different risk concerns, including delta-neutral strategy, delta-gamma-neutral strategy.
  • Price options using different methods, including BSM model, Binomial model.
  • Construct the optimal portfolio balancing return and risk.
  • Designing the optimal asset execution strategy targeting at minimum trading cost or risk exposure.

Pre-Requisite Subject(s)

(For Intake AY2019)

(For Intake AY2020 and onwards)

12 Credits

Awards

Students with strong academic performance and active class participation in this module will be eligible to win the Derivative Pricing and Risk Management Award 2021 & 2022.

Image Credit (https://www.lipscomb.edu/uploads/45801.jpg)