Hands-On AI Trading with Python, QuantConnect, and AWS

Part IIFoundations of AI and ML in Algorithmic Trading

Artificial intelligence (AI) refers to using advanced computational techniques and algorithms to perform complex tasks that typically require human intelligence. These tasks range from recognizing patterns in data and understanding natural language to making data-driven decisions.

While machine learning (ML) and AI are closely related fields, they are not synonymous: ML is a subset of AI that deals with developing algorithms and statistical models enabling computers to learn and make decisions without being explicitly programmed for specific tasks. AI includes other algorithms, such as rule-based systems and symbolic reasoning, which do not necessarily involve learning from data.

One of the critical applications of AI in finance is algorithmic trading, with AI analyzing vast amounts of historical data for profitable patterns, making predictions about future market movements with complex market dynamics models, and executing trades at the speed, scale, and efficiency superior to any human trader.

In addition, financial markets are inherently complex and unpredictable, and AI models must be carefully designed and trained, which includes selecting the right data sets, choosing the appropriate algorithms, and continuously monitoring and refining the models to improve their accuracy and reliability.

This part has been designed to provide a practical introduction to navigating this environment. We start with the outline of the ...