A Comparative Study of LSTM, LightGBM, and Autoregressive Model in Narrow-Based ETF Market Prediction with Multi-Ticker Models-Reference-Cited by-同舟云学术

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A Comparative Study of LSTM, LightGBM, and Autoregressive Model in Narrow-Based ETF Market Prediction with Multi-Ticker Models

Published:2023-10-27 Issue: Volume: Page:10-16
ISSN:
Container-title:The 6th International Conference on Machine Learning and Machine Intelligence
language:
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Author:

Hong Mengze¹^ORCID,Chen Zhiyuan²^ORCID,Mahmoud Soliman Waleed²^ORCID,Zhang Kun²^ORCID

Affiliation:

1. School of Mathematical Sciences, University of Nottingham Malaysia, Malaysia

2. School of Computer Science, University of Nottingham Malaysia, Malaysia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3635638.3635640

Reference21 articles.

1. Stock Price Prediction Using the ARIMA Model

2. John E. Baiden. 2011. Exchange Traded Funds-Advantages and Disadvantages. SSRN Electron. J. (2011). DOI:https://doi.org/10.2139/ssrn.1874409

3. Variational Autoencoders and Wasserstein Generative Adversarial Networks for Improving the Anti-Money Laundering Process

4. The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation

5. Artificial intelligence for ETF market prediction and portfolio optimization

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