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AT-LSTM: An Attention-based LSTM Model for Financial Time Series Prediction
5 references·6 citing·42 second hop
AT-LSTM: An Attention-based LSTM Model for Financial Time Series Prediction (2019)AT-LSTM: An Attention-based LSTM Model fo…Using neural networks and data mining techniques for the financial distress prediction model (2008)Using neural networks and dat…AUTOMATED INFERENCE AND LEARNING IN MODELING FINANCIAL VOLATILITY (2005)AUTOMATED INFERENCE AND LEARN…GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics (2001)GARCH 101: The Use of ARCH/GA…Intraday periodicity and volatility persistence in financial markets (1997)Intraday periodicity and vola…Long-term dependence in common stock returns (1977)Long-term dependence in commo…LSTM-ARIMA as a hybrid approach in algorithmic investment strategies (2025)LSTM-ARIMA as a hybrid approa…Attention-enhanced LSTM for high-value customer behavior prediction: Insights from Thailand’s E-commerce sector (2025)Attention-enhanced LSTM for h…Forecasting Stock Market Indices Using the Recurrent Neural Network Based Hybrid Models: CNN-LSTM, GRU-CNN, and Ensemble Models (2023)Forecasting Stock Market Indi…LSTM in Algorithmic Investment Strategies on BTC and S&P500 Index (2022)LSTM in Algorithmic Investmen…Forecasting Agricultural Commodity Prices Using Dual Input Attention LSTM (2022)Forecasting Agricultural Comm…STL-ATTLSTM: Vegetable Price Forecasting Using STL and Attention Mechanism-Based LSTM (2020)STL-ATTLSTM: Vegetable Price …The Behavior of Stock-Market Prices (1965)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Stock market prices and long-range dependence (1999)The Long Memory of the Efficient Market (2004)Some stylized facts of the Bitcoin market (2017)Financial Ratios As Predictors of Failure (1966)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)Predicting corporate financial distress based on integration of decision tree classification and logistic regression (2011)A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data (2014)Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition (2019)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility (2009)Precious metals–exchange rate volatility transmissions and hedging strategies (2010)Crude oil hedging strategies using dynamic multivariate GARCH (2011)Forecasting principles and practiceStock Price Prediction Using the ARIMA Model (2014)A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)Agricultural Product Price Forecasting Methods: A Review (2023)Forecasts of wholesale food price indices through Gaussian process regressions (2025)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)Deep learning with long short-term memory networks for financial market predictions (2017)Stock market's price movement prediction with LSTM neural networks (2017)Neural network forecasting for seasonal and trend time series (2003)Seasonal forecasting of agricultural commodity price using a hybrid STL and ELM method: Evidence from the vegetable market in China (2017)Agricultural commodity futures prices prediction based on a new hybrid forecasting model combining quadratic decomposition technology and LSTM model (2024)Deep Learning Approaches for Potato Price Forecasting: Comparative Analysis of LSTM, Bi-LSTM, and AM-LSTM Models (2024)A Dual Output Temporal Convolutional Network With Attention Architecture for Stock Price Prediction and Risk Assessment (2025)Time series analysis forecasting and control (2009)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)New frontiers for arch models (2002)Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm (2010)Systemic Risk Measurement: Multivariate GARCH Estimation of CoVaR (2012)Deutsche Mark–Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies (1998)Realized Variance and Market Microstructure Noise (2006)Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise (2008)Stock market prediction with time series data and news headlines: a stacking ensemble approach (2023)A deep fusion model for stock market prediction with news headlines and time series data (2024)Artificial intelligence techniques in financial trading: A systematic literature review (2024)
this work references cited by second hop

References

  • 1997Intraday periodicity and volatility persistence in financial markets1,301 cited
  • 2001GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics1,224 cited
  • 1977Long-term dependence in common stock returns478 cited
  • 2005AUTOMATED INFERENCE AND LEARNING IN MODELING FINANCIAL VOLATILITY343 cited
  • 2008Using neural networks and data mining techniques for the financial distress prediction model283 cited

Cited by

  • 2020STL-ATTLSTM: Vegetable Price Forecasting Using STL and Attention Mechanism-Based LSTM103 cited
  • 2023Forecasting Stock Market Indices Using the Recurrent Neural Network Based Hybrid Models: CNN-LSTM, GRU-CNN, and Ensemble Models99 cited
  • 2022Forecasting Agricultural Commodity Prices Using Dual Input Attention LSTM87 cited
  • 2025LSTM-ARIMA as a hybrid approach in algorithmic investment strategies45 cited
  • 2022LSTM in Algorithmic Investment Strategies on BTC and S&P500 Index36 cited
  • 2025Attention-enhanced LSTM for high-value customer behavior prediction: Insights from Thailand’s E-commerce sector10 cited

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