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Teaching/MH4518

MH4518 · Undergraduate

Simulation Techniques in Finance

Mathematical Sciences

Semester 2 (from 2026)Back to module tabs

Course materials and assessment information for registered students are provided through NTULearn. External resource links may require NTU access.

Overview

Scheduling note: MH4518 moves to Semester 2 from AY2025/26, while MH4514 moves to Semester 1. Timetable-clash requests are not accepted.



This course aims to equip you with standard and advanced simulation techniques for stochastic processes and cover their applications in finance, including derivatives pricing and risk management. In this course, you will develop skills in modelling and simulating time series data, and based on which you will be able to devise solutions to quantitative finance problems.

Prerequisites: MH2500 (Probability & Introduction to Statistics); MH3511 (Data Analysis with Computer)
Rules for Prerequisite Waiver Requests: There is no way to approve the waivers of MH2500. MH3511 can be waived as long as you can show evidence that you are familiar with the programming in R or Python; though, the illustration of the implementation codes (in lab sessions) is in R.

Intended Learning Outcomes

Upon successfully completing this course, you should be able to:
  1. Implement the basic simulation
  2. Incorporate with the variance reduction techniques in simulations
  3. Formulate and resolve quantitative finance problems, including derivatives pricing and hedging strategies, with simulation techniques
  4. Evaluate a financial product from a risk manager's perspective with simulated forward-looking financial data

Assessment Scheme

  • Take-home Assignments (15%)
  • Group Project (35%): a group of 3 students analyzes a real structured product
  • Restricted Open-book Final Exam (50%)

Topics

  1. [3hrs] Introduction and Concepts [Slides]
  2. [4.5hrs] Generating Randomness [Slides]
  3. [3.5hrs] Models of Asset Dynamics I - Discrete-time Approach [Slides]
  4. [3hrs] Models of Asset Dynamics II - Continuous-time Approach [Slides]
  5. [4hrs] Variance Reduction Techniques [Slides]
  6. [5hrs] Derivatives Pricing I - Risk-Neutral Valuation [Slides]
  7. [4hrs] Derivatives Pricing II - Monte Carlo Simulation [Slides]
  8. [3hrs] Derivatives Pricing III - Estimating Sensitivities [Slides]
  9. [3hrs] Derivatives Pricing IV - American-type Derivatives [Slides]
  10. [3hrs] Simulations in Risk Management [Slides]

Textbook and Primary References

  1. [Textbook] N. H. Chan and H. Y. Wong (2015) Simulation Techniques in Financial Risk Management (2nd Edition). Wiley. ISBN:978-1-118-73581-7
  2. N. H. Chan and H. Y. Wong (2013) Handbook of Financial Risk Management: Simulations and Case Studies. Wiley. ISBN: 978-0-470-64715-8
  3. J. S. Dagpunar (2007) Simulation and Monte Carlo: with Applications in Finance and MCMC, Wiley. ISBN: 978-0-470-85494-5
  4. P. Glasserman (2003) Monte Carlo Methods in Financial Engineering, Springer-Verlag, New York. ISBN: 978-0-387-21617-1

Secondary References

  1. T. Björk (2019) Arbitrage Theory in Continuous Time (4th Edition). Oxford University Press.
  2. D. G. Luenberger (2013) Investment Science (2nd Edition). Oxford University Press.
  3. Y.-K. Kwok (2008) Mathematical Models of Financial Derivatives. Springer.