Forecasting with Deep Learning

• URL: http://arxiv.org/abs/2302.12027v1
• Date: Fri, 17 Feb 2023 10:09:22 GMT
• Title: Forecasting with Deep Learning
• Authors: Gissel Velarde
• Abstract summary: This paper presents a method for time series forecasting with deep learning and its assessment on two datasets. A single time series can be used to train deep learning networks if time series in a dataset contain patterns that repeat even with a certain variation. For less structured time series such as stock market closing prices, the networks perform just like a baseline that repeats the last observed value.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents a method for time series forecasting with deep learning and its assessment on two datasets. The method starts with data preparation, followed by model training and evaluation. The final step is a visual inspection. Experimental work demonstrates that a single time series can be used to train deep learning networks if time series in a dataset contain patterns that repeat even with a certain variation. However, for less structured time series such as stock market closing prices, the networks perform just like a baseline that repeats the last observed value. The implementation of the method as well as the experiments are open-source.

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