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Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices
16 references·9 citing·36 second hop
Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices (2019)Comparing the effectiveness of deep feedf…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Deep learning networks for st…Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)Deep neural networks, gradien…Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Predicting stock and stock pr…Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting direction of stock…Textual analysis of stock market prediction using breaking financial news (2009)Textual analysis of stock mar…Forecasting stock market movement direction with support vector machine (2004)Forecasting stock market move…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Emerging equity market volatility (1997)Emerging equity market volati…Predictable Risk and Returns in Emerging Markets (1995)Predictable Risk and Returns …Predictable Risk and Returns in Emerging Markets (1994)Predictable Risk and Returns …Long-Term Memory in Stock Market Prices (1991)Long-Term Memory in Stock Mar…Efficient Capital Markets: II (1991)Efficient Capital Markets: IILong-term Memory in Stock Market Prices (1989)Long-term Memory in Stock Mar…EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)EFFICIENT CAPITAL MARKETS: A …Efficient Capital Markets: A Review of Theory and Empirical Work (1970)Efficient Capital Markets: A …A novel prediction based portfolio optimization model using deep learning (2023)A novel prediction based port…A decision-making tool for the determination of the distribution center location in a humanitarian logistics network (2023)A decision-making tool for th…Forecasting the overnight return direction of stock market index combining global market indices: A multiple-branch deep learning approach (2022)Forecasting the overnight ret…Stock market index prediction based on reservoir computing models (2021)Stock market index prediction…Effective forecasting of stock market price by using extreme learning machine optimized by PSO-based group oriented crow search algorithm (2021)Effective forecasting of stoc…An efficient equilibrium optimizer with support vector regression for stock market prediction (2021)An efficient equilibrium opti…Big Data, Artificial Intelligence and Machine Learning: A Transformative Symbiosis in Favour of Financial Technology (2020)Big Data, Artificial Intellig…Assess deep learning models for Egyptian exchange prediction using nonlinear artificial neural networks (2020)Assess deep learning models f…Portfolio management via two-stage deep learning with a joint cost (2019)Portfolio management via two-…Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Time series forecasting using a hybrid ARIMA and neural network model (2003)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Financial time series forecasting using support vector machines (2003)Evaluating multiple classifiers for stock price direction prediction (2015)Sentiment analysis on social media for stock movement prediction (2015)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)The Cross-Section of Expected Stock Returns (1992)Application of support vector machines in financial time series forecasting (2001)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)Corporate financing and investment decisions when firms have information that investors do not have (1984)Common risk factors in the returns on stocks and bonds (1993)Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors (2000)Capital markets research in accounting (2001)The Behavior of Stock-Market Prices (1965)The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets (1965)ON THE PRICING OF CORPORATE DEBT: THE RISK STRUCTURE OF INTEREST RATES* (1974)Theory of the firm: Managerial behavior, agency costs and ownership structure (1976)Users of the world, unite! 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References

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  • 2009

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Textual analysis of stock market prediction using breaking financial news
777 cited
  • 2016Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500749 cited
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    • 2020Assess deep learning models for Egyptian exchange prediction using nonlinear artificial neural networks41 cited
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    • 2020Big Data, Artificial Intelligence and Machine Learning: A Transformative Symbiosis in Favour of Financial Technology22 cited