# Application of a Shallow Neural Network to Short-Term Stock Trading

## TL;DR

This paper demonstrates that a simple single-layer neural network can effectively make buy or sell decisions in short-term stock trading by analyzing historical high prices, showing potential for neural network applications in finance.

## Contribution

The study introduces a neural network approach for short-term stock trading decisions, highlighting its ability to accurately classify buy or sell signals based on historical data.

## Key findings

- Neural network achieved accurate buy/sell predictions.
- Simple neural network can be effective in stock decision-making.
- Method shows promise for short-term trading strategies.

## Abstract

Machine learning is increasingly prevalent in stock market trading. Though neural networks have seen success in computer vision and natural language processing, they have not been as useful in stock market trading. To demonstrate the applicability of a neural network in stock trading, we made a single-layer neural network that recommends buying or selling shares of a stock by comparing the highest high of 10 consecutive days with that of the next 10 days, a process repeated for the stock's year-long historical data. A chi-squared analysis found that the neural network can accurately and appropriately decide whether to buy or sell shares for a given stock, showing that a neural network can make simple decisions about the stock market.