Mikhail A. Beketov
Papers
1
Total Citations
134
H-Index
1
About
Mikhail A. Beketov is a leading researcher at the intersection of financial technology and quantitative portfolio management, with a primary focus on the algorithmic systems known as Robo Advisors. His most influential work, the 2018 paper *"Robo Advisors: quantitative methods inside the robots,"* has garnered 134 citations and stands as a foundational study in the field. In this work, Beketov systematically dissected the "black box" of Robo Advisory platforms, providing the first comprehensive taxonomy of the core portfolio optimization and asset allocation methods—such as Modern Portfolio Theory and Black-Litterman models—used within these automated systems. By demystifying the quantitative engines driving this disruptive trend in wealth management, his research has become an essential reference for both academics and industry practitioners seeking to understand the technological backbone of modern financial advising. Beketov’s contributions have helped bridge the gap between complex financial theory and practical fintech application, establishing him as a key voice in the ongoing evolution of automated investment services.
Research Focus
Key Achievements
Top Papers
- 1Robo Advisors: quantitative methods inside the robots134 citations · 2018