1 The rise of robo-advisors

1.1 What are robo-advisors?

Robo-advisors have become a popular alternative to human financial advisors. Historically, financial advisors met with clients, discussed their goals, created a financial plan, and then managed their clients’ money over time. In exchange for this personal attention, they charged clients fees, often in excess of 1% per year of their assets under management. Numerous companies have been trying to disrupt this business through online platforms that provide automated, algorithmic investment services similar to those of a financial advisor. Some of these automated systems “advise” clients through algorithmic implementations of modern portfolio theory, based on the Nobel Prize–winning work of Harry Markowitz in the 1950s, and others use optimization techniques borrowed from other disciplines. These companies have collectively become known as robo-advisors.

In this book, we show how anyone with a basic understanding of Python can build their own robo-advisor. We hope this will be useful for anyone who wants to work in this area, apply these algorithms to their own portfolio, or advise others.

1.1.1 Key features of robo-advisors

1.1.2 Comparison of robo-advisors

1.1.3 Things robo-advisors don’t do

1.2 Advantages of robo-advisors

1.2.1 Low fees

1.2.2 Tax savings

1.2.3 Avoiding behavioral biases

1.2.4 Saving time

1.3 Example: Social Security benefits

1.4 Python and robo-advising

1.5 Who might be interested in learning about robo-advising?

Summary