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Study of Stock Return Predictions Using Recurrent Neural Networks with LSTM · Study

WorkStudy of Stock Return Predictions Using Recurrent Neural Networks with LSTM

Nagaraj Naik2019

Work2019

Study of Stock Return Predictions Using Recurrent Neural Networks with LSTM

Nagaraj Naik · Biju R. Mohan

36 citations·0/0 files stored·Communications in computer and information science

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Hydrological Forecasting Using AI

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References

2013Quantifying Trading Behavior in Financial Markets Using Google Trends 2013A Bayesian regularized artificial neural network for stock market forecasting 2008Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network 2016Forecasting daily stock market return using dimensionality reduction 2010Combining multiple feature selection methods for stock prediction: Union, intersection, and multi-intersection approaches 2016Application of artificial neural network for the prediction of stock market returns: The case of the Japanese stock market 2010Predicting stock returns by classifier ensembles 2017Mean-semivariance portfolio optimization with multiobjective evolutionary algorithms and technical analysis rules

Cited by

2020Machine Learning Based Stock Market Analysis: A Short Survey 2020COMPARING THE PREDICTION ACCURACY OF LSTM AND ARIMA MODELS FOR TIME-SERIES WITH PERMANENT FLUCTUATION 2021Predicting Stock Closing Prices in Emerging Markets with Transformer Neural Networks: The Saudi Stock Exchange Case

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Details

Year2019

Typeother

Published2019-01-01

VenueCommunications in computer and information science

ISSN-L1865-0929

Languageen

Citations36

Files0 public / 0

ShelfStock Market Forecasting Methods

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doi10.1007/978-3-030-20257-6_39

openalex_workW2946030813

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