Forecasting exchange rates with the iMLP: New empirical insight on one multi-layer perceptron for interval time series (ITS)-Reference-Cited by-同舟云学术

Forecasting exchange rates with the iMLP: New empirical insight on one multi-layer perceptron for interval time series (ITS)

Published:2021-09 Issue: Volume:104 Page:104358
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Maté Carlos,Jimeńez Lucía

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference44 articles.

1. Point, interval and density forecasts of exchange rates with time varying parameter models;Abbate;J. Roy. Statist. Soc. Ser. A,2018

2. Special issue on neural networks in financial engineering;Abu-Mostafa;IEEE Trans. Neural Netw.,2001

3. Interval time series analysis with an application to the sterling-dollar exchange rate;Ai;J. Syst. Sci. Complex.,2008

4. Different approaches to forecast interval time series: a comparison in finance;Arroyo;Comput. Econ.,2011

5. Arroyo, J., Maté, C., 2006. Introducing interval time series: Accuracy measures. In: Proceedings in Computational Statistics. COMPSTAT 2006. pp. 1139–1146.

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Forecasting USD/RMB exchange rate using the ICEEMDAN‐CNN‐LSTM model;Journal of Forecasting;2024-08-19

2. Enhancing interval-valued time series forecasting through bivariate ensemble empirical mode decomposition and optimal prediction;Engineering Applications of Artificial Intelligence;2024-07

3. Forecasting interval‐valued returns of crude oil: A novel kernel‐based approach;Journal of Forecasting;2024-06-04

4. Predicting multi-horizon currency exchange rates using a stacked ensemble of random forest and SVR;Intelligent Decision Technologies;2024-02-20

5. A multi-model approach to the development of algorithmic trading systems for the Forex market;Expert Systems with Applications;2024-02