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Study of Effectiveness of Time Series Modeling (Arima) in Forecasting Stock Prices
3 references·16 citing·44 second hop
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References

  • 2007Model Based Inference in the Life Sciences: A Primer on Evidence1,842 cited
  • 1993Forecasting With Dynamic Regression Models.378 cited
  • 2009Model Based Inference in the Life Sciences: A Primer on Evidence327 cited

Cited by

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  • 2022Novel optimization approach for stock price forecasting using multi-layered sequential LSTM183 cited
  • 2022A comprehensive review on multiple hybrid deep learning approaches for stock prediction136 cited
  • 2020A time series analysis-based stock price prediction using machine learning and deep learning models105 cited
  • 2021Stock-Price Forecasting Based on XGBoost and LSTM100 cited
  • 2019A smart system for short-term price prediction using time series models99 cited
  • 2019Evaluation of forecasting methods from selected stock market returns92 cited
  • 2019Development of stock market trend prediction system using multiple regression75 cited
  • 2022ARIMA vs LSTM on NASDAQ stock exchange data75 cited
  • 2021Stock Price Prediction Using Convolutional Neural Networks on a Multivariate Time Series61 cited
  • 2018Bitcoin Price Forecasting Using Time Series Analysis52 cited

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  • 2023Stock market prediction with time series data and news headlines: a stacking ensemble approach49 cited
  • 2020Time Series Forecasting of Agricultural Products’ Sales Volumes Based on Seasonal Long Short-Term Memory47 cited
  • 2025LSTM-ARIMA as a hybrid approach in algorithmic investment strategies45 cited
  • 2023Stock price prediction using ARIMA versus XGBoost models: the case of the largest telecommunication company in the Middle East43 cited
  • 2021Stock Price Prediction Using ARIMA, Neural Network and LSTM Models41 cited