S&P-500 vs. Nasdaq-100 price movement prediction with LSTM for different daily periods
This paper explores the efficiency of LSTM neural networks in predicting price movements for the two major U.S. stock indices: the S&P-500 and the Nasdaq-100 index. We consider three distinct daily periods: “overnight” (Close-to-Open), “daytime” (Open-to-Close) and “24-hour” (Close-to-Close) tra...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827024000938 |
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