Not available in 2020/21
ST418 Half Unit
Non-Linear Dynamics and the Analysis of Real Time Series
This information is for the 2020/21 session.
Teacher responsible
Prof Leonard Smith PEL.4.01C
Availability
This course is available on the MSc in Applicable Mathematics, MSc in Econometrics and Mathematical Economics, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (ÐÓ°ÉÂÛ̳ and Fudan), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.
Pre-requisites
It is recommended that students have completed Time Series (ST422).
Course content
An introduction to the analysis of actual time series observations of real-world processes. The course casts both modern nonlinear methods and more traditional linear methods in a geometric approach. It introduces the properties of nonlinear mathematical models, covers chaos and the dynamics of uncertainty, and demonstrates the fundamental limitations in applied analysis which arise from model inadequacy. Fundamental aspects of predictability are addressed. Decision support under uncertainty is considered, with examples of economic impacts of forecasting, including weather and climate. The student will leave with a toolkit for the analysis and modelling of real data, with insights into how to evaluate which methods to employ (linear/non-linear, deterministic/stochastic) in a given problem, how to interpret the results in context, and how to avoid over interpreting nice theorems in practical circumstances. Concrete applications in economics (price time series, electricity demand, energy futures) and environment (weather, climate) as well as analytically tractable illustration from mathematics are considered.
Teaching
20 hours of lectures and 10 hours of computer workshops in the LT. 1 hour of lectures in the ST.
Week 6 will be used as a reading week.
Indicative reading
K Beven, Environmental Modelling: An uncertain Future? Routledge (2009); H Kantz & T Schreiber, Non-linear Time Series Analysis; E Ott, T Sauer & J A Yorke (Eds), Coping with Chaos: Analysis of Chaotic Data and The Exploitation of Chaotic Systems; E Ott, Chaos in Dynamical Systems; R Tsay, Analysis of Financial Time Series; L.A. Smith, Chaos: A Very Short Introduction. Oxford University Press (2007)
Assessment
Exam (70%, duration: 2 hours) in the summer exam period.
Project (30%) in the ST.
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Key facts
Department: Statistics
Total students 2019/20: 28
Average class size 2019/20: 14
Controlled access 2019/20: Yes
Value: Half Unit
Personal development skills
- Problem solving
- Communication
- Application of numeracy skills
- Specialist skills
