A Novel Online Portfolio Selection Strategy with Multiperiodical Asymmetric Mean Reversion
Joint Authors
Peng, Zijin
Xu, Weijun
Li, Hongyi
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-29
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Mean reversion is an important property when constructing efficient contrarian strategies.
Researchers observe that mean reversion has multiperiodical and asymmetric nature simultaneously in real market.
To better utilize mean reversion and improve the existing online portfolio selection strategies, we propose a new online strategy named multiperiodical asymmetric mean reversion (MAMR).
The MAMR strategy incorporates a multipiecewise loss function with the moving average method and then imitates the passive-aggressive algorithm.
We further provide a solution via convex optimization.
This strategy runs in linear time and thus is suitable for large-scale trading applications.
Our empirical results testing six real market datasets show that this strategy can achieve better results in bearing higher transaction cost.
American Psychological Association (APA)
Peng, Zijin& Xu, Weijun& Li, Hongyi. 2020. A Novel Online Portfolio Selection Strategy with Multiperiodical Asymmetric Mean Reversion. Discrete Dynamics in Nature and Society،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1153224
Modern Language Association (MLA)
Peng, Zijin…[et al.]. A Novel Online Portfolio Selection Strategy with Multiperiodical Asymmetric Mean Reversion. Discrete Dynamics in Nature and Society No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1153224
American Medical Association (AMA)
Peng, Zijin& Xu, Weijun& Li, Hongyi. A Novel Online Portfolio Selection Strategy with Multiperiodical Asymmetric Mean Reversion. Discrete Dynamics in Nature and Society. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1153224
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1153224