Mathematical Finance & Financial Time Series Analysis

Program Overview

This three-week summer program offers an intensive introduction to quantitative finance for overseas students. Covering mathematical finance and time series analysis, it equips students with computational skills and theoretical knowledge to pursue careers in this specialized field. The program features hands-on lab sessions, a mini-project, and formal assessment. Upon completion, students will have a strong foundation in financial engineering and data analysis tools.

Program Outline

Degree Overview:

This is a three-week summer program equivalent to an accredited undergraduate course (20 UK credits) delivered by University faculty who are experts in their field. The program is designed for students based overseas who want to experience studying abroad and gain insight into quantitative finance. It covers fundamental knowledge in financial engineering, a specialized and rapidly growing area. The program aims to equip students with computational skills and the underlying mathematical and statistical theory to prepare for a career in quantitative finance. It is both technical and pragmatic, covering mathematical finance and financial time series analysis.

Outline:

Mathematical Finance:

• Week 1-2:
• Introduction to stocks/shares and lognormal random walks (including Supply and Demand)
• Introduction to Portfolios, arbitrage and risk-free investments
• Introduction to Options/Derivatives (Payoff functions, Rates of Return, and the effects of Gearing)
• A simple derivation of the Black Scholes equation
• American vs European options
• Simple Binomial Methods for determining the value of European/American options
• Introduction to Path Dependent Options
• Simple Monte Carlo Methods for determining the value of Path Dependent options
• Derivative Disasters/LIBOR Scandal/ForEx Scandal
• Lab Sessions:
• Use the MatLAB Software package (fully introduced)
• Implement the Binomial Method and simple Monte Carlo simulations
• Dice-rolling games and a Stock Market game to facilitate understanding of concepts of Mathematical Finance
• Class Test (short and diligent students are expected to pass)

Time Series Analysis:

• Week 3:
• Introduction to stationary and non-stationary variables
• Introduction to Autoregressive distributed lag models and forecasting
• The Additive Model for a Time Series
• Linear Filtering of Time Series
• Autocovariances and Autocorrelations
• Linear Filters and Stochastic Processes
• Moving Averages and Autoregressive Processes
• The Box–Jenkins Program
• Lab Sessions:
• Based on R (introductory material provided)
• Work on a mini-project presented on the last day of the module
• Implement suitable models to analyze a real-world dataset
• Oral presentation of the mini-project (formal assessment for the 3rd week)

Assessment:

• Class test (Mathematical Finance)
• Small project (Time Series Analysis)
• Oral presentation (Time Series Analysis)

Teaching:

• Delivered by University faculty who are experts in their field.
• Includes lectures, hands-on computer lab demonstrations, and work on mini-projects.
• Requires independent study for assessment.

Careers:

• The program aims to prepare students for a career in quantitative finance.
• Students will gain skills and knowledge in financial engineering, mathematical finance, and time series analysis.
• The program provides hands-on experience in using computing programs.

Other:

• The program plan is subject to confirmation for BISS 2022.
• The program is formally assessed.
• Students must check with their home institution regarding the transfer of credits.
• On completion of the program, students will have demonstrated strong analytical skills in mathematical finance, knowledge of theoretical and empirical methods involved in analyzing real-world data, an understanding of the power and limitations of applied statistical analysis, and hands-on experience in using computing programs.