Machine Learning vs. Quants: The Advantages of Machine Learning in Finance

Many unexploited opportunities have been evident to quants for decades, but although the solutions may be clear statistically at some level, the limiting factor has been computation. A simple example is incorporating unstructured data like online content, or semi-structured data like company reports and transaction data, into predictive models. Feature engineering is the process machine learning folks use to generate inputs to statistical models from raw input data. There are approaches for automated feature learning with techniques like deep learning -- recently, this has allowed us to unlock the potential of understanding and labeling images. Then there are approaches that require collaboration with subject matter experts.