Part I. The Status Quo of Robo-Advisory.- Chapter 1. Robo-Advisory: The Rise of the Investment Machines; Peter Scholz and Michael Tertilt.- Chapter 2. Situating Robo-Advisory; Sinan Krueckeberg.- Part II. The Implementation of Robo-Advisory.- Chapter 3. Risk Preferences of Investors; Monika Mueller, Paul Resnik and Craig Saunders.- Chapter 4. Robo-Economicus: The Impact of Behavioral Biases on Robo-Advisory; Peter Scholz, David Grossmann and Joachim Goldberg.- Chapter 5. Quant Models for Robo-Advisors; Thorsten Ruehl.- Chapter 6. The Analysis of Robo-Advisors as a Replacement for Personal Selling; Goetz Greve and Frederike Meyer.- Chapter 7. The Regulation of Robo-Advisors in the United States; Melanie L. Fein.- Chapter 8. The Regulation of Robo-Advisory in Europe and Germany; Christian Hammer.- Part III. Case Studies of Robo-Advisory.- Chapter 9. (Re)Launching a Robo-Advisor as a Bank; Theodor Schabicki, Yvonne Quint and Soeren Schroeder.- Chapter 10. How Can Robo-Advisory be Implemented and Integrated into Existing Banks?; Ana-Maria Climescu, Christian von Keitz, Jan Rocholl and Madeleine Sander.- Part IV. The Future of Robo-Advisory.- Chapter 11. The Role of Artificial Intelligence in Robo-Advisory; Alexander D. Beck.- Chapter 12. What Role does Social Media Play for Robo-Advisors?; Ana-Maria Climescu.- Chapter 13. Success Factors for Robo-Advisory: Now and Then; Madeleine Sander.
Peter Scholz has over ten years of practical experience with Deka Investment and Deutsche Bank, where he has worked in capital market related divisions such as Asset Management, Global Markets, Risk Management, Private and Retail Banking. Since 2013, he has been a Professor of Business Sciences, specifically Banking & Financial Markets, at Hamburg School of Business Administration, Germany. His research interests focus on the digitalization of the financial sector, behavioral finance, and the performance of active asset management and equity derivatives, especially on retail certificates and technical timing strategies.
Robo-Advisory is a field that has gained momentum over recent years, propelled by the increasing digitalization and automation of global financial markets. More and more money has been flowing into automated advisory, raising essential questions regarding the foundations, mechanics, and performance of such solutions. However, a comprehensive summary taking stock of this new solution at the intersection of finance and technology with consideration for both aspects of theory and implementation has so far been wanting. This book offers such a summary, providing unique insights into the state of Robo-Advisory.
Drawing on a pool of expert authors from within the field, this edited collection aims at being the vital go-to resource for academics, students, policy-makers, and practitioners alike wishing to engage with the topic. Split into four parts, the book begins with a survey of academic literature and its key insights paired with an analysis of market developments in Robo-Advisory thus far. The second part tackles specific questions of implementation, which are complemented by practical case studies in Part III. Finally, the fourth part looks ahead to the future, addressing questions of key importance such as artificial intelligence, big data, and social networks. Thereby, this timely book conveys both a comprehensive grasp of the status-quo as well as a guiding outlook onto future trends and developments within the field.