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Optimizing LSTM Based Network For Forecasting Stock Market
16 references·2 citing·33 second hop
Optimizing LSTM Based Network For Forecasting Stock Market (2020)Optimizing LSTM Based Network For Forecas…Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Statistical and Machine Learn…LSTM Model Optimization on Stock Price Forecasting (2018)LSTM Model Optimization on St…Genetic Algorithm-Optimized Long Short-Term Memory Network for Stock Market Prediction (2018)Genetic Algorithm-Optimized L…Combining Support Vector Machine with Genetic Algorithms to optimize investments in Forex markets with high leverage (2018)Combining Support Vector Mach…Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Stock price prediction using …Stock market's price movement prediction with LSTM neural networks (2017)Stock market's price movement…Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)Surveying stock market foreca…A Non‐Random Walk Down Wall Street. (2003)A Non‐Random Walk Down Wall S…Application of support vector machines in financial time series forecasting (2001)Application of support vector…A non-random walk down Wall Street (1999)A non-random walk down Wall S…Introduction to financial forecasting (1996)Introduction to financial for…Forecasting stock market volatility using (non-linear) Garch models (1996)Forecasting stock market vola…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Autoregressive Conditional He…Time Series Analysis Forecasting and Control (1972)Time Series Analysis Forecast…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 …Prediction of Stock Market Index Using a Hybrid Technique of Artificial Neural Networks and Particle Swarm Optimization (2021)Prediction of Stock Market In…Intelligent Asset Allocation using Predictions of Deep Frequency Decomposition (2021)Intelligent Asset Allocation …Stock market prediction system with modular neural networks (1990)Neural network forecasting of the British Pound/US Dollar exchange rate (1998)Financial time series forecasting using support vector machines (2003)Support vector machine with adaptive parameters in financial time series forecasting (2003)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Forecasting stock market movement direction with support vector machine (2004)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Deep learning with long short-term memory networks for financial market predictions (2017)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK* (1964)Investigating Causal Relations by Econometric Models and Cross-spectral Methods (1969)Book Review: Time Series Analysis: Forecasting and Control (1977)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! The challenges and opportunities of Social Media (2009)A Random Walk Down Wall Street (1973)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Applications of deep learning in stock market prediction: Recent progress (2021)Time Series Analysis Forecasting and Control. (1971)25 years of time series forecasting (2006)Stock Closing Price Prediction using Machine Learning Techniques (2020)Another look at measures of forecast accuracy (2006)N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (2019)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Econometric Analysis of Cross Section and Panel Data (2001)Empirical properties of asset returns: stylized facts and statistical issues (2001)The Efficient Market Hypothesis and Its Critics (2003)The Adaptive Markets Hypothesis (2004)
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References

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  • 2018Combining Support Vector Machine with Genetic Algorithms to optimize investments in Forex markets with high leverage73 cited
  • 2003

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A Non‐Random Walk Down Wall Street.
51 cited
  • 2018LSTM Model Optimization on Stock Price Forecasting48 cited
  • Cited by

    • 2021Prediction of Stock Market Index Using a Hybrid Technique of Artificial Neural Networks and Particle Swarm Optimization27 cited
    • 2021Intelligent Asset Allocation using Predictions of Deep Frequency Decomposition26 cited