In the past decade, artificial intelligence (AI) has made significant inroads into the financial industry, with applications ranging from stock trading to fraud detection. Now, AI is being used to create “systems that can trade stocks or other assets.” These AI-based systems are able to analyze vast amounts of data and make predictions about future price movements.
One notable example of an AI-based system that trades stocks is “Flash Crash,” developed by a team at Cornell University. Flash Crash uses a deep learning algorithm to predict stock price movements. The system was able to correctly predict the direction of the stock market on 87% of days during the testing period.
Another example of an AI-based system that trades stocks is “DeepTradeBot,” developed by a team at the University of Waterloo. DeepTradeBot uses a deep learning algorithm to predict the direction of the stock market. The system was found to be accurate in its predictions on 70% of days during the testing period.
Systems that trade stocks using AI have the potential to outperform human traders. They can make longer-term predictions and are not subject to emotional biases. However, these systems are still in their early stages of development and need to be constantly monitored and tweaked.
References:
https://www.cornell.edu/news/2018/02/cornell-engineers-build-artificial-intelligence-system-can-predict-market-moves
https://uwaterloo.ca/waterloo-stories/article/deep-learning-algorithm-outperforms-human-stock-traders