AI and Machine Learning Gain Momentum with Algo Trading & ATS Amid Volatility

An increasing number of capital markets firms are adopting machine learning and other artificial intelligence techniques to build algorithmic trading systems that learn from data without relying on rules-based systems. With the hiring of data scientists, advances in cloud computing, and access to open source frameworks for training machine learning models, AI is transforming the trading desk. Already the largest banks have rolled out self-learning algorithms for equities trading. "Machine learning is a natural next step of algorithmic trading because machine learning identifies patterns and behaviors in historical data and learns from it," said Robert Hegarty, managing partner, Hegarty Group, a consultancy focusing on financial services, technology, data, and AI/machine learning. While traditional algorithms are created by programmers and quant strategists, these algorithms based on if/then rules do not learn on their own; they need to be updated.