An online portfolio strategy based on trend promote price tracing ensemble learning algorithm

How to carry out an investment portfolio efficiently and reasonably has become a hot issue. This study mainly addresses the problem of the instability of forecasting stock price investment and the difficulty in determining investment proportion by proposing the trend peak price tracing (TPPT). First...

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Vydané v:Knowledge-based systems Ročník 239; s. 107957
Hlavní autori: Dai, Hong-Liang, Liang, Chu-Xin, Dai, Hong-Ming, Huang, Cui-Yin, Adnan, Rana Muhammad
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 05.03.2022
Elsevier Science Ltd
Predmet:
Algorithms
Averages
Ensemble learning
Ensemble learning algorithm
Forecasting
Gradient projection
Investment ratio
Investments
Machine learning
Online portfolio investment
Portfolios
Price anomaly
Prices
Statistical tests
Stock prices
Strategies
Strategy
Three-state price
Tracing
Value
Wealth
Width
Ensemble learning algorithm
Online portfolio investment
Three-state price
Gradient projection
Price anomaly
Investment ratio
ISSN:0950-7051, 1872-7409
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Shrnutí:How to carry out an investment portfolio efficiently and reasonably has become a hot issue. This study mainly addresses the problem of the instability of forecasting stock price investment and the difficulty in determining investment proportion by proposing the trend peak price tracing (TPPT). First of all, because of the influence of stock price anomaly, TPPT strategy sets adjustable historical window width. It uses slope value to judge prediction direction to track price change, which uses exponential moving average and peak equal weight slope value three-state price prediction method. Secondly, the accumulated wealth target is refined, and the fast error Back Propagation based on gradient projection algorithm (BP) is added. The algorithm solves investment proportion and feedbacks the increasing ability of assets to the investment proportion in order to maximize the accumulated wealth. Finally, comparison of eight empirical strategies in five typical data and statistical tests show that TPPT strategy has great advantages in balancing risk and return, and it is a robust and effective online portfolio strategy.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0950-7051
1872-7409
DOI:10.1016/j.knosys.2021.107957