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Related Experiment Video

Updated: Nov 29, 2025

Mass Production of Genetically Modified Aedes aegypti for Field Releases in Brazil

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Published on: January 4, 2014

Predicting Stock Price Falls Using News Data: Evidence from the Brazilian Market.

Juvenal José Duarte¹, Sahudy Montenegro González¹, José César Cruz¹

¹School of Management and Technology, Federal University of São Carlos - UFSCar Sorocaba, São Paulo, 18052-780 Brazil.

Computational Economics

|November 23, 2020

Summary

Predicting stock market losses in Brazil is possible using news analysis. Machine learning models analyzing Portuguese news and historical prices outperform traditional strategies in forecasting financial downturns.

Keywords:

Brazilian Portuguese news Brazilian stock market Machine learning algorithms Price forecasting Text mining

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Area of Science:

Financial Markets
Computational Linguistics
Machine Learning

Background:

Investors utilize diverse information, including news, for investment decisions in risk assets like stocks.
This study investigates integrating public news with historical stock prices to forecast and mitigate losses in the Brazilian stock market.
An analysis of 64 securities across various economic sectors in Brazil is conducted.

Discussion:

The study compares traditional investment strategies (Buy & Hold, moving average) against 11 machine learning algorithms.
Experiments explore daily, weekly, and monthly time horizons for news publication and stock return windows.
The relevance and duration of news information's impact on market decisions are assessed.

Key Insights:

A significant correlation exists between news publications and stock price fluctuations in the Brazilian market, indicating short-term arbitrage possibilities.
Machine learning models effectively predict stock price declines using Portuguese news data.
Text mining approaches demonstrate superior performance over traditional strategies in predicting financial losses.

Outlook:

Text mining and machine learning offer advanced tools for financial loss prediction.
Further research can explore cross-market applications and refine news-based predictive models.
The findings suggest enhanced risk management strategies for Brazilian stock market participants.