金融预测：N-HiTS和N-BEATS神经预测模型的比较分析
计算金融
2024-09-10 v2
摘要
在快速发展的金融预测领域，神经网络的应用在传统统计模型方面提供了引人入目的数据。本研究论文探讨了两种特定神经预测模型N-HiTS和N-BEATS在预测金融市场趋势方面的有效性。通过与传统模型进行系统比较，本研究表明神经方法在处理金融时间序列数据中所固有的非线性动力学和复杂模式方面具有优势。结果表明，N-HiTS和N-BEATS不仅提高了预测的准确性，也增强了金融预测的鲁棒性和适应性，为需要实时决策的环境提供了实质性的优势。本文以对神经金融预测在金融市场中的实际意义以及未来研究方向的见解为结论。
引用
@article{arxiv.2409.00480,
title = {Advancing Financial Forecasting: A Comparative Analysis of Neural Forecasting Models N-HiTS and N-BEATS},
author = {Mohit Apte and Yashodhara Haribhakta},
journal= {arXiv preprint arXiv:2409.00480},
year = {2024}
}
备注
This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution will be published in the Proceedings of the International Conference on Information Systems for Business Management (ISBM 2024), Springer Lecture Notes in Networks and Systems (LNNS), 2024