Wavelets for Time Series Analysis (May 2018)

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Course Code: 3FNA023
ECTS credits: 5
Level Doctoral course
Course contents
The course will cover the following topics:
- an introduction to wavelet analysis
- the Discrete Wavelet Transform (DWT)
- the Maximal Overlap DWT (MODWT)
- the wavelet variance, covariance, correlation and cross correlation
- analysis of long memory processes
- wavelet-based estimation
- wavelet-based bootstrapping

Expected learning outcomes
Upon finishing the course, the students will be able to:
- Use and apply the wavelet methods to real data in appropriate software.
- Discuss and explain the main merits and limitations of Wavelet analysis.
- Present empirical results based on the wavelet methods in a clear and precis way.


 

Course Data
University: 
Linné
Type of schedule: 
Travel friendly schedule
Level: 
PhD
Credits (ECTS): 
5.00
Offered: 
Not scheduled