PE 19-20: Module 5:
Artificial Intelligence in Investing
12 and 19 May
Artificial Intelligence, currently the most disruptive technology in many sectors, has had relatively little impact on the investment management industry so far. Learn to be ahead of the curve as investment professional or as asset management firm manager.
Program 12th May, by Luiz Felix
Applications of AI in investing: challenges, opportunities and a practical deep-dive
Taking a practitioner perspective, Luiz Felix explores the main application of artificial intelligence (AI) to investing: information filtering, forecasting and portfolio construction. He identifies examples of these usages and the important trade-offs between them. He provides a broad comparison of AI methods and their flexibility, complexity, explainability, and learning autonomy. He distinguishes, in a conceptual and accessible level, the two main types of learning methods used by AI: supervised and unsupervised learning. He touches upon the main challenges to applying AI methods to financial data and investments (i.e., time-series data, overfitting, lack of transparency and governance in AI-led investment processes) and advises how investment professionals and asset management firms could act to overcome these difficulties. Given that some powerful AI methods, such as deep learning, are black-boxes, he also identifies promising advances on the transparency of such opaque approaches. Lastly, he deep dives into a practical application of AI for investing where a machine learning technique is used in active management, unveiling one of the opportunities of applying this technology by asset managers.
Program 19th May, by Iman van Lelyveld
Implementing AI in practice: diving deeper and resurfacing
The promising approaches discussed in the first session need to be embedded in your organisation in order to reap the full benefits of these new technologies. This requires changes to (data) governance and the expertise of staff. After a brief exploration of the former we will then explore a supervised learning analysis using a Jupyter Notebook to get a better sense of how algorithms are developed and what expertise is needed. Furthermore, understanding the inner workings of algorithm development will allow for more fruitful interaction between quantitative experts and commercial roles. Then we will discuss what managers, society and regulators currently expect and require from AI approaches and how this might change going forward. For example, DNB has published a White Paper sketching out expectations (https://www.dnb.nl/nieuws/nieuwsoverzicht-en-archief/DNBulletin2019/dnb385020.jsp).
Luiz Felix has worked in financial markets since 2001, starting his career as a fixed income portfolio manager in Brazil. In 2005, he joined ABN AMRO Asset Management in Amsterdam as a quantitative investment strategist. Since 2008 he works at the Asset Allocation & Overlay (AA&O) team of APG Asset Management. In AA&O Luiz has managed several derivative-based strategies, ranging from hedging and protection programs to systematic active strategies as well as a global macro hedge fund portfolio. He is the main designer of APG's tactical asset allocation (TAA) and the active FX mandates. Lately, his research focus on the application of artificial intelligence techniques to investing, leading him to develop natural language processing (NLP)- and deep learning-based investment strategies. He holds a PhD in Finance from VU Amsterdam and is a Chartered Financial Analyst and Certificate in Quantitative Finance charterholder. Luiz also consults for other pension funds and is the Advisory Board chairman of machineByte.
Iman van Lelyveld is Professor of Banking and Financial Markets at the Finance department of the Vrije Universiteit Amsterdam where he teaches a course 'Machine Learning for Finance'. He is also a Senior Policy Advisor at De Nederlandsche Bank (DNB). He is keen to use new data sources for solid data driven policy. At DNB he currently spearheads the Data Science Hub initiative. He has been involved in many regulatory policy issues covering amongst others, interest rate risk in the banking book, deposit guarantee pricing, and CVA charges and the BCBS Research Task Force. He has chaired several international groups, most recently on liquidity stress testing. He holds a PhD from Radboud University and has published widely on, amongst other topics, interbank networks and internal capital markets. Iman has worked for Deutsche Bank, the Bank of England, and the International Data Hub at the Bank for International Settlements.
- Everyone is welcome. To ensure a balanced interaction with the teacher and fellow students the number of course participants is limited to a maximum of 25.
- The course material will be sent to you upon registration.
- During the course preparation instructors are supervised by an academic coordinator to ensure the quality of the courses is in accordance with the objectives of CFA Society VBA Netherlands.
- You will receive a certificate of participation.
Terms and Conditions
Stichting VBA Opleidingsinstituut Morreau (Training Institute) is the education and training institute of CFA Society VBA Netherlands and as such organizes and executes the society's PE Modules.
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