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A Discrete Stock Price Prediction Engine Based on Financial News

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Financial Analysis and Corporate Governance

Abstract

The Arizona Financial Text system leverages statistical learning to make trading decisions based on numeric price predictions. Research demonstrates that AZFinText outperforms the market average and performs well against existing quant funds.

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References

2001Application of support vector machines in financial time series forecasting 1999Time series properties of an artificial stock market 2004Forecasting Intraday stock price trends with text mining techniques 2002Predicting stock price performance: a neural network approach 2002News Sensitive Stock Trend Prediction 2006Textual Analysis of Stock Market Prediction Using Financial News Articles

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2021Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic 2021Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature 2016Using social media mining technology to assist in price prediction of stock market 2018Effect of Digitalized Rumor Clarification on Stock Markets

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