Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting-Reference-Cited by-同舟云学术

Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting

Published:2022-07-24 Issue:8 Volume:41 Page:1701-1724
ISSN:0277-6693
Container-title:Journal of Forecasting
language:en
Short-container-title:Journal of Forecasting

Author:

Albuquerque Pedro Henrique Melo¹^ORCID,Peng Yaohao¹^ORCID,Silva João Pedro Fontoura da¹^ORCID

Affiliation:

1. Machine Learning Laboratory in Finance and Organizations ‐ LAMFO Departamento de Administração ‐ Campus Darcy Ribeiro, Universidade de Brasília Brasília Brazil

Publisher

Wiley

Subject

Management Science and Operations Research,Statistics, Probability and Uncertainty,Strategy and Management,Computer Science Applications,Modeling and Simulation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/for.2894

Reference166 articles.

1. Adhikari R. &Agrawal R. K.(2012).Combining multiple time series models through a robust weighted mechanism. In2012 1st International Conference on Recent Advances in Information Technology (RAIT)(pp.455–460). IEEE.

2. Bayesian consensus forecasts of macroeconomic variables

3. Persistence in forecasting performance and conditional combination strategies

4. An empirical analysis of the accuracy of SA, OLS, ERLS and NRLS combination forecasts

5. Ali A.(2020).Ensemble learning model for prediction of natural gas spot price based on least squares boosting algorithm. In2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI)(pp.1–6). IEEE.

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