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Comparison of Predictive Algorithms: Backpropagation, SVM, LSTM and Kalman Filter for Stock Market
1 references·7 citing·27 second hop
Comparison of Predictive Algorithms: Backpropagation, SVM, LSTM and Kalman Filter for Stock Market (2019)Comparison of Predictive Algorithms: Back…A Machine Learning Model for Stock Market Prediction (2014)A Machine Learning Model for …Optimizing investment portfolios with a sequential ensemble of decision tree-based models and the FBI algorithm for efficient financial analysis (2024)Optimizing investment portfol…Encoder–Decoder Based LSTM and GRU Architectures for Stocks and Cryptocurrency Prediction (2024)Encoder–Decoder Based LSTM an…A comparative study on effect of news sentiment on stock price prediction with deep learning architecture (2023)A comparative study on effect…Event prediction within directional change framework using a CNN-LSTM model (2022)Event prediction within direc…Stock Market Prediction using Bi-Directional LSTM (2021)Stock Market Prediction using…COMPARING THE PREDICTION ACCURACY OF LSTM AND ARIMA MODELS FOR TIME-SERIES WITH PERMANENT FLUCTUATION (2020)COMPARING THE PREDICTION ACCU…Stock Market Behaviour Prediction using Stacked LSTM Networks (2019)Stock Market Behaviour Predic…Stock market prediction using Hidden Markov Models (2012)Improving Stock Closing Price Prediction Using Recurrent Neural Network and Technical Indicators (2018)Predicting stock market trends using machine learning algorithms via public sentiment and political situation analysis (2019)Construction of Hybrid Deep Learning Model for Predicting Children Behavior based on their Emotional Reaction (2021)Time series forecasting using a hybrid ARIMA and neural network model (2003)Stock Price Prediction Using the ARIMA Model (2014)Deep learning with long short-term memory networks for financial market predictions (2017)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD (2020)Analysis and forecasting of Time-Series data using S-ARIMA, CNN and LSTM (2021)Research on a hybrid prediction model for stock price based on long short-term memory and variational mode decomposition (2021)A recurrent neural network approach in predicting daily stock prices an application to the Sri Lankan stock market (2017)Stock transaction prediction modeling and analysis based on LSTM (2018)Deep Learning-Based Stock Price Prediction Using LSTM and Bi-Directional LSTM Model (2020)Stock market's price movement prediction with LSTM neural networks (2017)Cost Harmonization LightGBM-Based Stock Market Prediction (2023)Model-driven multimodal LSTM-CNN for unbiased structural forecasting of European Union allowances open-high-low-close price (2024)Random Walks in Stock Market Prices (1995)Navigating Uncertainty: Enhancing Markowitz Asset Allocation Strategies through Out-of-Sample Analysis (2024)Evaluation of Cost-Sensitive Learning Models in Forecasting Business Failure of Capital Market Firms (2025)PORTFOLIO SELECTION* (1952)Portfolio Selection: Efficient Diversification of Investments (1959)Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy? (2007)NSE Stock Market Prediction Using Deep-Learning Models (2018)Applications of deep learning in stock market prediction: Recent progress (2021)Machine learning techniques and data for stock market forecasting: A literature review (2022)
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References

  • 2014A Machine Learning Model for Stock Market Prediction132 cited

Cited by

  • 2022Event prediction within directional change framework using a CNN-LSTM model71 cited
  • 2019Stock Market Behaviour Prediction using Stacked LSTM Networks61 cited
  • 2023A comparative study on effect of news sentiment on stock price prediction with deep learning architecture42 cited
  • 2024Optimizing investment portfolios with a sequential ensemble of decision tree-based models and the FBI algorithm for efficient financial analysis37 cited
  • 2020COMPARING THE PREDICTION ACCURACY OF LSTM AND ARIMA MODELS FOR TIME-SERIES WITH PERMANENT FLUCTUATION33 cited
  • 2021Stock Market Prediction using Bi-Directional LSTM28 cited
  • 2024Encoder–Decoder Based LSTM and GRU Architectures for Stocks and Cryptocurrency Prediction26 cited

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