High-dimensional data analysis with constraints
Traditional Markowitz portfolio is very sensitive to errors in estimated input for a high dimensional dataset. This problem inspired us to connect the high dimensional portfolio selection problem to a constrained lasso problem to deal with the input uncertainty. In this paper, we developed a new alg...
Saved in:
Main Author: | Zhou, Hanxiao |
---|---|
Other Authors: | Pun Chi Seng |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/156929 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Information Analysis of High-Dimensional Data and Applications
by: Xin She Yang, et al.
Published: (2018) -
Large-Dimensional Factor Analysis Without Moment Constraints
by: He, Yong, et al.
Published: (2021) -
Network-based screening for ultra-high dimensional survival data subject to semi-competing risks
by: Chin, Nicholas Wei Lun
Published: (2022) -
Independence test for high dimensional data based on regularized canonical correlation coefficients
by: Yang, Yanrong, et al.
Published: (2015) -
High dimensional clustering for mixture models
by: Liu, Yiming
Published: (2020)