Automated investment management: Comparing the design and performance of international robo‐managers

Abstract

Robo‐managers offer automated asset management; however, their overall performance is highly debated. We analyze 15 robo‐managers from Germany, the United States and the United Kingdom by conducting a comprehensive qualitative and quantitative study. The qualitative comparison shows considerable differences between the various robo‐managers, not only across but also within countries. The quantitative evaluation utilizes different measures to evaluate the performance of the robo‐manager sample. Our results indicate that each country has one particularly favourable robo‐manager. Furthermore, we find that the costs and characteristics of rebalancing measures have only a small effect on performance.

Artificial intelligence and customers’ intention to use robo-advisory in banking services

“…In the case of fully automated advice, an advanced degree of artificial intelligence algorithms enables it to make decisions on the creation and execution of investment strategies. In other cases, the software is responsible for preparing investment recommendations, as well as selecting assets for the portfolio, but investment decisions are still made by clients after consultation with a personal financial advisor (Helms et al, 2021;Maume, 2021). To make accurate recommendations, financial intermediaries offering robo-advisory services aim to identify clients' levels of financial literacy, their financial needs and goals, and their attitude towards investment risk.…”

Deep Reinforcement Learning for Quantitative Finance: Time Series Forecasting using Proximal Policy Optimization

“…The beginning of model driven approaches really goes back to applied statistical methods from the early 1900's, such as mean reversion, however, these early methods were far from automated [1]. Automated approaches really took off once accompanying advancements in computation were made and exchanges pursued computerizing the markets through the 1970's onward [2,3,4,5,6]. One method of investing which arose from this digitization of markets, high frequency trading, often employs automated trade executions which classically used simplistic algorithmic rules, but is now applying more advanced methods such as using DRL [7,6].…”