Artificial Intelligence & Data Science in Capital Markets
An abundance of cheap and powerful computing capacity is bringing artificial intelligence to bear on an ocean of data, across a range of industrial applications.
Complex mathematical modelling has always been part of the data-driven financial world, but today professional money managers are exploring a new range of techniques including machine learning, deep learning and neural networks. They have also become familiar with the relatively new discipline of data science – really an intersection of software engineering, statistical modelling, research analytics, data mining and data warehousing.
Newsweek’s AI and Data Science in Capital Markets inaugural event in London provided participants with a clear view of what exactly these new tools are, and how they can capture value in the financial realm. This forthcoming event in New York will likewise bring together the best minds in quantitative finance and data science to discuss how advanced computing, when applied to vast and varied datasets, can help predict the price of financial instruments.
This will involve an exploration of new and exciting data sources currently being swooped upon by hedge funds and asset managers seeking an alpha edge. For example, in London we looked at cube satellite imagery, which can provide a cheap and accurate picture of commercially significant activity anywhere on the planet; automatic identification system (AIS) data, which map the whereabouts of all vessels on the ocean via inbuilt transponders; IoT data on farming yields; heterogeneous shopping data – the list was long.
The process of capturing, cleaning and formatting these large and sometimes noisy datasets is examined in detail, both from the proprietary perspective of large financial players, and also how this is done by third party vendors.
Portfolio management enhancements and risk management using machine learning will also be discussed, as will the regulatory response to algorithms that adapt to changes in market conditions; building trust in the industry and wider public, rather than the putative ‘black box’.
The event will also consider the extent to which advancements in AI happening in areas such as computer vision, voice recognition and self-driving cars can usefully be applied to finance. And at a higher level there will be discussions about human capital and the impact machines might have on key roles within finance such as discretionary traders and research analysts.
Our Advisory Board have been working to ensure that the overarching themes we're focusing on cover the most poignant topics when approaching and discussing Artificial Intelligence and Data Science in Capital Markets. So far, these include:
- Human capital
- High frequency trading
- Advances in high performance computing
- Advanced portfolio management
- Adapting state-of-the-art AI algorithms for use in capital markets
- Discretionary / fundamental to ‘quantamental’ i.e. introducing data science into fundamental investing
- Open source infrastructure and interoperability
- Cybersecurity, Risk & Regulation and CDSO