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Harnessing a Hybrid CNN-LSTM Model for Portfolio Performance: A Case Study on Stock Selection and Optimization
16 references·1 citing·45 second hop
Harnessing a Hybrid CNN-LSTM Model for Portfolio Performance: A Case Study on Stock Selection and Optimization (2023)Harnessing a Hybrid CNN-LSTM Model for Po…Predicting stock market index using LSTM (2022)Predicting stock market index…Portfolio optimization with return prediction using deep learning and machine learning (2020)Portfolio optimization with r…A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images (2020)A combined deep CNN-LSTM netw…A CNN-LSTM-Based Model to Forecast Stock Prices (2020)A CNN-LSTM-Based Model to For…Stock price prediction based on deep neural networks (2019)Stock price prediction based …Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data (2019)Forecasting stock prices with…ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module (2018)ModAugNet: A new forecasting …Decision-making for financial trading: A fusion approach of machine learning and portfolio selection (2018)Decision-making for financial…Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach (2018)Algorithmic financial trading…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem (2017)A Deep Reinforcement Learning…Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Predicting stock and stock pr…On the use of cross-validation for time series predictor evaluation (2012)On the use of cross-validatio…Portfolio optimization problems in different risk measures using genetic algorithm (2009)Portfolio optimization proble…An MCDM approach to portfolio optimization (2003)An MCDM approach to portfolio…PORTFOLIO SELECTION* (1952)PORTFOLIO SELECTION*Enhancing Stock Market Prediction: A Robust LSTM-DNN Model Analysis on 26 Real-Life Datasets (2024)Enhancing Stock Market Predic…Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Another look at measures of forecast accuracy (2006)Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure (2016)A note on the validity of cross-validation for evaluating autoregressive time series prediction (2017)Forecasting: theory and practice (2022)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Financial time series forecasting using support vector machines (2003)Forecasting stock market movement direction with support vector machine (2004)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)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)On Persistence in Mutual Fund Performance (1997)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Time Series Analysis: Forecasting and Control. (1978)A novel graph convolutional feature based convolutional neural network for stock trend prediction (2020)Stock price prediction using deep learning and frequency decomposition (2020)The Behavior of Stock-Market Prices (1965)Time Series Analysis Forecasting and Control. (1971)A novel deep learning framework: Prediction and analysis of financial time series using CEEMD and LSTM (2020)Deep learning in finance and banking: A literature review and classification (2020)Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions (2021)The Cross-Section of Expected Stock Returns (1992)A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network (2020)Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions (2020)A stock price prediction method based on deep learning technology (2021)Economic prediction using neural networks: the case of IBM daily stock returns (1988)Time series forecasting using a hybrid ARIMA and neural network model (2003)Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)Harvesting social media sentiment analysis to enhance stock market prediction using deep learning (2021)Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)Stock Price Prediction Using the ARIMA Model (2014)Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models (2018)The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction (2021)Cryptocurrency trading: a comprehensive survey (2022)Machine learning techniques and data for stock market forecasting: A literature review (2022)Forecasting turning points in stock price by applying a novel hybrid CNN-LSTM-ResNet model fed by 2D segmented images (2022)Big data analytics deep learning techniques and applications: A survey (2023)A review on evaluating mental stress by deep learning using EEG signals (2024)Conditional value-at-risk for general loss distributions (2002)Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy? (2007)The relationship between corporate social responsibility and shareholder value: an empirical test of the risk management hypothesis (2008)
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References

  • 1952PORTFOLIO SELECTION*13,480 cited
  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
  • 2012On the use of cross-validation for time series predictor evaluation1,324 cited
  • 2014Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques1,139 cited
  • 2020A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images691 cited
  • 2020A CNN-LSTM-Based Model to Forecast Stock Prices564 cited
  • 2018Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach433 cited
  • 2019Stock price prediction based on deep neural networks378 cited
  • 2018ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module373 cited
  • 2019Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data342 cited
  • 2003An MCDM approach to portfolio optimization323 cited
  • 2022Predicting stock market index using LSTM314 cited
  • 2017A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem310 cited
  • 2020Portfolio optimization with return prediction using deep learning and machine learning

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299 cited
  • 2009Portfolio optimization problems in different risk measures using genetic algorithm288 cited
  • 2018Decision-making for financial trading: A fusion approach of machine learning and portfolio selection276 cited
  • Cited by

    • 2024Enhancing Stock Market Prediction: A Robust LSTM-DNN Model Analysis on 26 Real-Life Datasets48 cited