Explore the evolution of AI investing and online wealth management
Investing and managing your wealth online has never been easier, but how does AI investing work and what are the challenges?
On this course, you’ll explore how technology has changed the way we invest money. You’ll consider the evolution of AI-driven online wealth management platforms, robo-advisors, and learn how they work and why they’re successful.
Moving from human-based data-driven investing strategies to neural networks, you’ll assess the ability of artificial intelligence to make investment decisions and discover the role of AI and machine learning in making trading decisions.
This course is designed for anyone interested in understanding cutting edge financial technologies.
This course will be of particular interest to learners with a background in finance, development, or business leadership and learning how to develop and use new financial technologies in their own context.
Ronny De Winter completed this course, spending 3 hours a week on it and found the course difficulty to be medium.
This course gives a good overview of the possibilities of AI today in FinTech/Investing. The first week positions Investing within FinTech amongst the other financial services like money transfer and raising money, and its constituents investment advice,...
This course gives a good overview of the possibilities of AI today in FinTech/Investing. The first week positions Investing within FinTech amongst the other financial services like money transfer and raising money, and its constituents investment advice, trading services and private banking/wealth management.
Robo advising, as part of wealth management, covers the main concepts of asset allocation and risk, the role of diversification and correlation, and how to build efficient portfolios using CAPM. Exchange-Traded Funds (ETFs) offer a low-cost method for diversified portfolio construction. Pros and cons of Robo advisors vs human contacts are discussed. A reference is provided to an existing Robo advisor and the learner is invited to discuss it on the course forum.
In stock selection, the use of neural networks is explained that can be used to find patterns and signals one could use to improve returns, however with the caveat that these patterns can change over time.
Factor portfolios, aka smart-beta, are explained and you get an exercise to create one.
In the last week AI / Machine Learning / Big data are discussed in its different forms, including the newer and more advanced techniques using unstructured data and big data, deep learning, ...
The course closes with an overview of the key values and pitfalls of investTech and you get as an exercise to write a memo with a proposal on introducing ML/AI in a hypothetical investment company.
This is not an AI/ML course, it does not go into the details of these techniques, therefore you'll need more technical courses. The course, however, gives a good overview of how these techniques are used today in fintech. With a few exercises, you learn how to set up alternative portfolios and calculate the resulting returns.
Form July 2020 this same course will also be delivered via the Coursera platform. The Futurelearn platform is good for interacting with other learners, and the course is delivered at fixed time schedules. When I took the course there were not that many students and the interactions on the forum were rather limited, also the course staff was completely absent on the forum. So the interactive FutureLearn forum was not really an advantage here. If you prefer Coursera you can use that platform with a similar learning experience.