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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
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| Paper Title: | Predicting Stock Prices for the Next 7 Days: A Comparative Analysis of SARIMA and LSTM Models |
| Authors Name: | Jyothsna R , K R Kaushik Kumar , Rashmi R |
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IJRTI_188139
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| Published Paper Id: | IJRTI2310004 |
| Published In: | Volume 8 Issue 10, October-2023 |
| DOI: | |
| Abstract: | A rigorous comparative analysis of two prominent models, seasonal autoregressive integrated moving average (SARIMA) and long-term memory (LSTM) neural networks, to forecast stock prices over a 7-day horizon. Historical daily stock prices of large companies in various economic sectors were used in the research. The SARIMA model is used to describe the underlying trends and seasonality in financial time series, while the LSTM model, a deep learning model, is used to capture complex sequential dependencies. Both models are analyzed using specified performance measures such as mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE). The results provide valuable insight into the strengths and limitations of each model and provide guidance to investors, financial analysts and decision makers in forecasting stock markets. This study adds to the existing stock market forecasting literature and provides a basis for further advances and improvements in financial market |
| Keywords: | Deep Learning, Machine Learning, Stocks, SARIMA, LSTM, Data Analysis, Visualization, Tensorboard |
| Cite Article: | "Predicting Stock Prices for the Next 7 Days: A Comparative Analysis of SARIMA and LSTM Models", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 10, page no.11 - 17, October-2023, Available :http://www.ijrti.org/papers/IJRTI2310004.pdf |
| Downloads: | 000205269 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2310004
Registration ID:188139
Published In: Volume 8 Issue 10, October-2023
DOI (Digital Object Identifier):
Page No: 11 - 17 Country: Bangalore, Karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2310004 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2310004 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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