As Artificial Intelligence becomes a widespread and mature technology, the investment industry is increasingly turning its tools to face the complexity of financial markets. From security analysis to portfolio construction, there are many fields in which AI has proved capable of adding scale and efficiency to the investment process and be a valuable resource for asset and investment managers.
Yet, despite the many touchpoints with traditional quantitative models, it is the ability to improve the signal-to-noise ratio and focus on a holistic – rather than narrow – understanding of market dynamics that set AI models apart. As we are going to see, this brings a new level of understanding of the inner workings of financial markets.
Knowledge is Power
Over the past decade, the tools of machine learning and Artificial Intelligence (AI) have led to an impressive technological revolution that has redefined – and in some cases disrupted – a wide array of industries. Among their benefits, these tools have allowed us to process data more efficiently and dramatically improved our ability to understand, interpret and adapt to the complexity of the real world.
For these reasons, apart from some of its well-known applications in fields like space exploration or medical imaging, AI is being increasingly adopted by the investment industry. Indeed, as financial markets represent a traditionally complex and dynamic environment, the opportunity offered by AI is twofold: improve the quality of investment decision making and quickly adapt to the gradual evolution of financial markets.
