Mathematics and Statistics of Algorithmic Trading (MATH0062)

Key information

Faculty: Faculty of Mathematical and Physical Sciences
Teaching department: Mathematics
Credit value: 15

Restrictions: N/A
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module introduces the theories and practices of algorithm trading, where we will see how statistical and mathematical models can be utilised to guide traders what strategies are to be employed under different contexts. Some examples include:

鈥� How to generate trading signals to recommend if a trader should long/short a particular asset? 鈥� How to optimally construct a portfolio of different assets to achieve certain risk-return objectives?

鈥� How to dynamically hedge a derivative product under a more complicated model beyond the Black-Schols paradigm?

鈥� A trader wants to sell a large quantity of stock. Submitting this large order to the market in a single trade will create market impact and move the price against the trader. How should this order be optimally broken down into smaller pieces and executed over time to minimise the cost associated with market impact?

Module deliveries for 2024/25 academic year

Intended teaching term: Term 2 听听听 Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study: In person
Methods of assessment: 100% Exam
Mark scheme: Numeric Marks

Other information

Number of students on module in previous year: 29
Module leader: Dr Alex Tse
Who to contact for more information: maths.mscteaching@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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Important information

The catalogue has been updated with key information about the modules that will run during the 2024/25 academic session. Current and prospective students can browse through the catalogue to consider possible module choices for the coming year.

Please note,听information in the catalogue is听subject to change as teaching and assessment arrangements for 2024/25 may need to be adjusted in line with the University's Feedback and Assessment principles and operating model.

Centrally managed exam durations will be provided on students' individual exam timetables. Arrangements for locally managed exams and in-class activity will be confirmed by the teaching department for the module.

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