Stefan Mayer,

a Munich, Germany, based economist, studied business administration and economics at the University of Passau (B.Sc.) and economics and public policy at the University of Augsburg (M.Sc.). He then obtained his Ph.D. in economics (Dr. rer. pol.) at the University of Augsburg with a dissertation on capital adequacy regulation.

Stefan Mayer is always on the hunt for interesting projects. He has a strong passion for new information technology in banking (FinTech/RegTech), accompanied with a solid understanding of economic principles and mechanisms.

Education

Dr. rer. pol., Economics
University of Augsburg, 2022

M.Sc., Economics and Public Policy
University of Augsburg, 2016

B.Sc., Business Administration and Economics
University of Passau, 2014

Portfolio / Selected Work

Duration and Convexity of Bonds with Embedded Options
Have you ever wondered how reliable are bond risk measures when your fixed-income investment is callable or putable? Risk measures of bonds with embedded options are sensitive to changes in the underlying economic and financial conditions. This is because the value and behavior of these investment, can be affected by factors such as changes in interest rates, credit spreads, and volatility. As a result, standard risk measures for these types of bonds are difficult to predict and require sophisticated modeling techniques. The exact level of sensitivity will depend on the specifics of the bond, including the type and terms of the embedded options. I have developed a lattice-based short-rate model that calibrates and predicts the duration and convexity of bonds with embedded options.

YARA - Yet Another Robo-Advisor
Automate the boring stuff, think about economies of scale! These are popular philosophies in programming and business, but not well-conceived, they lead to disastrous results. For instance, current financial-advisor AIs are not well-conceived, and their advice is merely financial platitude from the 1950s, but not state of the art. However, the best financial advise follows a very simple principle: having more money is always better than having less. To this end, I have developed a robo-advisor that outperforms existing software and even human advisors in terms of efficiency and accuracy.
This robo-advisor automatically analyzes complex financial market data and transaction costs that are beyond the capabilities of a human advisor. It utilizes state-of-the-art methods to forecast and automatically calculates the optimal (Markowitz) portfolio that is tailored to the client's preferences. The output is presented in the form of a simple "recipe" that the client can easily recreate. The recipe includes a list of two to three financial securities that the client only needs to purchase.
Compared to traditional financial advisors, my robo-advisor offers better performance at a lower cost. It provides a more (economical and statistical) efficient and reliable service to clients, and can make predictions with a quality that was once only accessible to big investment banks and hedge funds. With my robo-advisor, clients can be confident that they are making informed financial decisions that align with their goals and preferences: having more money is always better than having less.

Stefan Mayer,

Personal Information

Education

Skills

Portfolio / Selected Work