In plain words: A review of deep learning studies from 2005 to 2019 that predict prices for stock indexes, currencies, and commodities, sorted by the type of network used. It finds these deep networks generally beat older machine learning tools, and notes open problems and chances ahead.
Abstract · Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019
Financial time series forecasting is, without a doubt, the top choice of computational intelligence for finance researchers from both academia and financial industry due to its broad implementation areas and substantial impact. Machine Learning (ML) researchers came up with various models and a vast number of studies have been published accordingly. As such, a significant amount of surveys exist covering ML for financial time series forecasting studies. Lately, Deep Learning (DL) models started appearing within the field, with results that significantly outperform traditional ML counterparts. Even though there is a growing interest in developing models for financial time series forecasting research, there is a lack of review papers that were solely focused on DL for finance. Hence, our motivation in this paper is to provide a comprehensive literature review on DL studies for financial time series forecasting implementations. We not only categorized the studies according to their intended forecasting implementation areas, such as index, forex, commodity forecasting, but also grouped them based on their DL model choices, such as Convolutional Neural Networks (CNNs), Deep Belief Networks (DBNs), Long-Short Term Memory (LSTM). We also tried to envision the future for the field by highlighting the possible setbacks and opportunities, so the interested researchers can benefit.
Omer Berat Sezer, Mehmet Ugur Gudelek, Ahmet Murat Ozbayoglu
arXiv:1911.13288 · cs.LG, q-fin.CP, stat.ML · submitted Nov 29, 2019
abstract · pdf · html · 13 figures, 13 tables, submitted to Applied Soft Computing
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2) There's lots of interesting trading you can do even without having any idea about what the price is going to do. Do you think volatility is going to increase? You can make money from that - read about the Collar Trade Strategy (This is just an example).
3) There's lots of strategies which don't make enough money for companies to be interested in, but are viable for an individual.