Course syllabus - Time Series Analysis
Scope
7.5 credits
Course code
MMA702
Valid from
Autumn semester 2013
Education level
Second cycle
Progressive Specialisation
A1F (Second cycle, has second-cycle course/s as entry requirements).
Main area(s)
Mathematics/Applied Mathematics
School
School of Education, Culture and Communication
Ratified
2013-02-01
Literature lists
Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.
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Books
Analysis of financial time series
3rd ed. : Hoboken, N.J. : Wiley, c2010. - xxiii, 677 p.
ISBN: 978-0-470-41435-4 (cloth) LIBRIS-ID: 11901702
Objectives
Time series play a key role in analytical finance and insurance, and in financial engineering. The course presents the basic models of time series such as linear time series, autoregressive type models, nonlinear time series, high-frequency models, continuous time models and multivariate time series, elements of statistical estimation as well as simulation of time series. This basic part of the course can also be interesting for students from other specialties than analytical finance and financial engineering. The examples used in the course are selected from time series applications economics, finance and insurance.
Learning outcomes
At the end of the course the student is expected to be able to
- perform descriptive analysis of sample data.
- choose appropriate models for financial time series.
- use formulas for evaluation of various distributional parameters, prices for financial contracts, and other characteristics connected with financial time series.
- solve equations connected with financial time series.
- use algorithms and formulas for statistical estimation in time series analysis.
- build algorithms for Monte Carlo simulation of various time series models.
Course content
Financial time series and their characteristics. Linear time series analysis, autoregressive type models (ARCH, GARCH, CHARMA and stochastic volatility models). Nonlinear models. High-frequency data analysis and market microstructure. Continuous-time models. Extreme values, quantile estimation and value at risk. Multivariate time series analysis. Principal component analysis and factor models. Multivariate volatility models. State-space models and Kalman filter. Monte Carlo methods.
Tuition
Lectures combined with exercises. Continuous examination of problems/projects combined with written tests. Examination of seminars through oral presentation of written reports.
Specific requirements
At least 120 credits totally from these areas: technical, natural sciences, business administration or economics where Stochastic Processes 7,5 credits or equivalent is included and a TOEFL test result, minimum score 173 (CBT), 500 (PBT) or 61 (iBT) or an IELTS test result with an overall band score of minimum 5,0 and no band score below 4,5. The English test is COMPULSORY for all applicants except citizens of Australia, Canada, Ireland, New Zealand, United Kingdom and USA.
Examination
Continuous examination/projects combined with written test (PRO1), 4.5 credits, marks Pass (G) or Pass with distinction (VG)
Seminars (SEM1), 3 credits, marks Pass (G) or Pass with distinction (VG)
A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.
Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.
Grade
Pass with distinction, Pass, Fail