Paper
23 August 2022 Assets prediction using machine learning techniques
Author Affiliations +
Proceedings Volume 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022); 123301B (2022) https://doi.org/10.1117/12.2646743
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 2022, Huzhou, China
Abstract
The theme of this paper was to examine different forecasting techniques to predict future stock returns based on past returns and numerical news indicators to construct a portfolio of multiple stocks in order to diversify the risk. This was done by applying supervised learning methods for stock price forecasting by interpreting the seemingly chaotic market data. Predicting the Impact of News articles on the Closed Price of the Apple Inc. Stocks using Naive Bayes Classifier. First of all the News Articles dataset and Historical Stocks Dataset were merged into a single dataset on the 'Date' column after making some necessary changes to them. Further, methods such as ensemble classifier which mainly entailed knowledge Nearest Neighbour(k-NN) were applied. Afterwards Natural Language Processing was applied on the News Headlines text and obtained a Bag of words containing 20000 most common words from by converting them to vectorized form. Then later the Naive Bayes model was trained (Gaussian, Multinomial or Bernoulli each in different files) by splitting the dataset, 80% as training dataset and 20% as test dataset. Overall, it was observed that the neural-based models achieved slightly better accuracy and macro-average F1 than the standard and ensemble models, and significantly better accuracy than the ZeroR baseline. Therefore, the news articles such as the model helps in classifying the news articles to a profit or a loss. This was done by calculating the difference in closed price of present day with the previous day.
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Yanzhe Luo "Assets prediction using machine learning techniques", Proc. SPIE 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 123301B (23 August 2022); https://doi.org/10.1117/12.2646743
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KEYWORDS
Principal component analysis

Machine learning

Data modeling

Neural networks

Linear filtering

Performance modeling

3D modeling

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