Deep Learning and Time Series-to-Image Encoding for Financial Forecasting

doi:10.1109/JAS.2020.1003132

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > IEEE/CAA Journal of Automatica Sinica

	Deep Learning and Time Series-to-Image Encoding for Financial Forecasting
	Silvio Barra; Salvatore Mario Carta; Andrea Corriga; Alessandro Sebastian Podda; Diego Reforgiato Recupero
刊名	IEEE/CAA Journal of Automatica Sinica
	2020
卷号	7 期号:3 页码:683-693
关键词	Convolutional neural networks (CNNs) ensemble of CNNs financial forecasting Gramian angular fields (GAF) imaging
ISSN号	2329-9266
DOI	10.1109/JAS.2020.1003132
英文摘要	In the last decade, market financial forecasting has attracted high interests amongst the researchers in pattern recognition. Usually, the data used for analysing the market, and then gamble on its future trend, are provided as time series; this aspect, along with the high fluctuation of this kind of data, cuts out the use of very efficient classification tools, very popular in the state of the art, like the well known convolutional neural networks (CNNs) models such as Inception, ResNet, AlexNet, and so on. This forces the researchers to train new tools from scratch. Such operations could be very time consuming. This paper exploits an ensemble of CNNs, trained over Gramian angular fields (GAF) images, generated from time series related to the Standard & Poor’s 500 index future; the aim is the prediction of the future trend of the U.S. market. A multi-resolution imaging approach is used to feed each CNN, enabling the analysis of different time intervals for a single observation. A simple trading system based on the ensemble forecaster is used to evaluate the quality of the proposed approach. Our method outperforms the buy-and-hold (B&H) strategy in a time frame where the latter provides excellent returns. Both quantitative and qualitative results are provided.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42979]
专题	自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Silvio Barra,Salvatore Mario Carta,Andrea Corriga,et al. Deep Learning and Time Series-to-Image Encoding for Financial Forecasting[J]. IEEE/CAA Journal of Automatica Sinica,2020,7(3):683-693.
APA	Silvio Barra,Salvatore Mario Carta,Andrea Corriga,Alessandro Sebastian Podda,&Diego Reforgiato Recupero.(2020).Deep Learning and Time Series-to-Image Encoding for Financial Forecasting.IEEE/CAA Journal of Automatica Sinica,7(3),683-693.
MLA	Silvio Barra,et al."Deep Learning and Time Series-to-Image Encoding for Financial Forecasting".IEEE/CAA Journal of Automatica Sinica 7.3(2020):683-693.