Modified non-transformed principal component and adaptive penalized high dimension for grouping effect of stock market price
Nonstationary time series is complex and difficult to be modelled. Many researchers resolved it by transforming it into stationary time series. However, loss of generality will occur which make its inference more difficult. To overcome this, therefore a modified non-transformed approach is proposed...
Saved in:
Main Author: | Andu, Yusrina |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/102444/1/YusrinaAnduPFS2020.pdf.pdf http://eprints.utm.my/id/eprint/102444/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:145895 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Modified non-transformed principal component and adaptive penalized high dimension for grouping effect of stock market price.
by: Yusrina Andu
Published: (2020) -
Non-transformed principal component technique on weekly construction stock market price
by: Andu, Yusrina, et al.
Published: (2019) -
Adaptive elastic net with distance correlation on the grouping effect and robust of high dimensional stock market price
by: Yusrina Andu,, et al.
Published: (2021) -
Penalized poisson regression model using adaptive modified elastic net penalty
by: Algamal, Zakariya Yahya, et al.
Published: (2015) -
Measuring the systematic risk factors in Malaysia stock market returns: A principal component analysis approach
by: Muhamad Shameer Fahmi, et al.
Published: (2019)