How Neural Network Predictive Power Varies Across Stock Market Sectors
Start Date
7-8-2026 12:00 PM
End Date
7-8-2026 12:15 PM
Location
ALT 206
Abstract
In the stock market, different sectors have different characteristics. For instance, the consumer staples sector tends to be more stable because there’s always a demand for everyday items, whereas sectors like energy or financials tend to be more volatile. This made me wonder how the predictive power of neural networks varies across stock market sectors. Using historical market data from the past five years collected from Yahoo Finance, this project evaluates the performance of neural network models in forecasting future stock performance across multiple sectors. While this research is far from finished, the goal is to compare results across sectors and determine whether machine learning models perform more effectively in certain stock market sectors, while also identifying the factors that drive their predictive success.
How Neural Network Predictive Power Varies Across Stock Market Sectors
ALT 206
In the stock market, different sectors have different characteristics. For instance, the consumer staples sector tends to be more stable because there’s always a demand for everyday items, whereas sectors like energy or financials tend to be more volatile. This made me wonder how the predictive power of neural networks varies across stock market sectors. Using historical market data from the past five years collected from Yahoo Finance, this project evaluates the performance of neural network models in forecasting future stock performance across multiple sectors. While this research is far from finished, the goal is to compare results across sectors and determine whether machine learning models perform more effectively in certain stock market sectors, while also identifying the factors that drive their predictive success.
