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About Stock Market Forecasting Using Deep Learning and Technical Analysis A Systematic Review
This document summarizes a systematic review of deep learning models for stock market forecasting using technical analysis. It finds that long short-term memory (LSTM) techniques are widely applied, representing 73.5% of studies. However, it also finds limitations in the literature, with only 35.3% of studies analyzing profitability metrics and just two articles implementing risk management strategies. While deep learning for stock forecasting using technical indicators is a widely explored area, there remain open questions around thoroughly evaluating model performance, profitability, and risk.
Detailed Information
| Author: | ['Bachi'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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