Mr. Yanzhe Luo Profile

Yanzhe Luo

at The University of Birmingham

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Proceedings Article | 23 August 2022 Paper

Assets prediction using machine learning techniques

Yanzhe Luo

Proceedings Volume 12330, 123301B (2022) https://doi.org/10.1117/12.2646743

KEYWORDS: Principal component analysis, Machine learning, Data modeling, Neural networks, Linear filtering, Performance modeling, Visualization, Statistical modeling, 3D modeling, Statistical analysis

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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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