Mathematical Finance & Financial Time Series Analysis

3 weeks
Course Type
Summer School, Undergraduate

At the University’s well established and highly regarded School of Mathematics we deliver this exciting summer study programme specialised in Mathematical Finance and Financial Time series analysis.

The programme is ideal for students based overseas who would like to experience studying abroad and also gain a valuable insight into the fascinating yet challenging field of quantitative finance.

The programme covers the fundamental knowledge in financial engineering, which is a highly specialised and rapidly growing area. You will be able to explore the computational skills as well as the underlying mathematical and statistical theory to prepare for a career on the computational end of quantitative finance. The programme is both technical and pragmatic. In Mathematical Finance, you will first learn to examine the financial derivatives using a continuous-time approach, then analyse a range of discrete time financial models and investment models. In the 3rd week of the program, you will start the econometric modelling of financial time series. You will learn various methods of fitting linear and non-linear models to time series data, statistical validation and their use such as forecasting and simulation using the statistical package SAS®.

Topic may include:

Mathematical Finance

1) Introduction to stocks/shares and lognormal random walks (including Supply and Demand)
2) Introduction to Portfolios, arbitrage and risk-free investments
3) Introduction to Options/Derivatives (Payoff functions, Rates of Return, and the effects of Gearing)
4) A simple derivation of the Black Scholes equation
5) American vs European options
6) Simple Binomial Methods for determining the value of European/American options
7) Introduction to Path Dependent Options
8) Simple Monte Carlo Methods for determining the value of Path Dependent options
9) Derivative Disasters/LIBOR Scandal/ForEx Scandal

The Lab Sessions will use the MatLAB Software package, which will be fully introduced. You will be expected to implement the Binomial Method and simple Monte Carlo simulations. Dice-rolling games and a Stock Market game will be used to facilitate understanding of concepts of Mathematical Finance. The Class Test will be short and diligent students are expected to pass.

Time Series Analysis

The coverage will be focused on the explorations of the following topics in particular, but not exclusively:

1) Introduction to stationary and non-stationary variables
2) Introduction to Autoregressive distributed lag models and forecasting
3) The Additive Model for a Time Series
4) Linear Filtering of Time Series
5) Autocovariances and Autocorrelations
6) Linear Filters and Stochastic Processes
7) Moving Averages and Autoregressive Processes
8) The Box–Jenkins Program

The Lab Sessions will be based on R. You will be provided introductory material and work on a mini-project which will be presented in on the last day of the module. You will be expected to implement suitable models to analyse a real-world dataset. The oral presentation of the mini-project will be the formal assessment part for the 3rd week.

Please note that the programme plan is subject to confirmation for BISS 2021.

The teachers were excellent.

Haotian, Mathematical Finance & Financial Time Series Analysis programme

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To be accepted onto the Mathematical Finance programme you must:

  • Have relevant subject background: the programme operates at ‘beginners’ level’ but students are required to have prerequisites of  calculus, probability and statistics, or have the equivalent level of knowledge. Students must be able to demonstrate relevant subject background with a translated transcript.
  • Meet the BISS Entry Requirements

This is a three week programme and is equivalent to an accredited undergraduate course (20 UK credits) and is delivered by University faculty who are experts in their field. In addition there will be ‘hands-on’ computer lab demonstrations and work on mini-projects, and lectures. In addition you will be required to undertake independent study to allow for assessment. The programme is formally assessed. Please check with your home institution regarding the transfer of credits.

On completion of the programme in addition to obtaining 20 credits you will have been given a unique opportunity to:

• Demonstrate strong analytical skills in the mathematical finance
• Demonstrate knowledge of theoretical and empirical methods involved in analysing real-world data
• Evaluate differences in types of models, and demonstrate an understanding of the power and limitations of applied statistical analysis
• Gain hands-on experience in using computing programs

Assessment Methods

The programme will be formally assessed through a class test, small project and oral presentation.


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