Volatility autocorrelation in the stock market with artificial neural networks
Predicting the trend of financial features in complex financial systems is important and challenging, one useful tool is looking at the autocorrelation function, used in technical analysis as it shows how closely related a pattern reappears in the future. In this paper, we demonstrate a way to op...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175690 |
| Summary: | Predicting the trend of financial features in complex financial systems is important and
challenging, one useful tool is looking at the autocorrelation function, used in technical
analysis as it shows how closely related a pattern reappears in the future. In this paper,
we demonstrate a way to optimise the autocorrelation of a linear combination of a stock’s
volatility in prices and volumes, lagged at different times using regression neural networks. |
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