The Big Smoke – in 2018, I plan to travel to the #7 in the ranking of the Global Financial Centres… Toronto! Weiterlesen
Together with my Ph.D. student David, we have analyzed liquidity risks and therefore finished the third article for his thesis.
The liquidity regulation of banks in Pillar 1 of the Basel framework does not consider funding cost risks of different bank business models. Therefore, we assemble a data set of balance sheet positions including maturities and use the method of Value-Liquidity-at-Risk to explore 118 European retail, wholesale, and trading banks. When examining liquidity-induced equity risks, trigged by exemplary rating shifts, we find that retail banks bear significantly lower funding cost risks than wholesale and trading banks. Consequently, a prudential regulation, which simultaneously considers the funding cost risk and the diversification of the banking system is recommended.
David Großmann & Peter Scholz (2017): The Golden Rule of Banking: Funding Cost Risks of Bank Business Models. SSRN Working Paper.
Photo zur Verfügung gestellt von Sarah Jastram
Vom 23. bis 24. November haben sich die Research Groups der HSBA nach Ratzeburg zurückgezogen um den Stand der Disserationsprojekte intensiv diskutieren zu können. Weiterlesen
This module has two main goals: it serves as a repetition of content students should already be familiar with as well as an application by transferring formulas into action. We rely on Excel, VBA, and MATLAB as software packages and cover basic concepts from B.Sc. studies as well as CFA Level I content. First and foremost, the essential time value of money, followed by applications in risk management as well as asset pricing, e.g. bonds, derivatives, and portfolios. By the end of this course, the participants are able to remember and to understand these basic concepts and they learned to apply these concepts on real data. Weiterlesen
From October 9th to 13th, I traveled to Hong Kong with 16 HSBA B.Sc. students and Sinan, my Ph.D. student.
This year, our destination had to be Asia, since five out of the top ten Global Financial Centres are located here. Currently, Hong Kong is third in the ranking, so we were curious what the city offers… besides a huge harbor and many, many skyscrapers…
In a joint work with Michael Tertilt, an HSBA alumnus of MBA Corporate Management, we analyze the current quality of robo-advice.
Robo-advisors promise efficient, rational, and transparent investment advisory. We analyze how robo-advisors ascertain their user’s risk tolerance and which equity exposure is derived from the individual risk profile. Our findings indicate significant differences in the quality of offered investment advice. On average, robo-advisors ask relatively few questions in their user’s risk profile assessment, and it is particularly surprising that some of the questions seem not to have any impact on the risk categorization. Moreover, the recommended equity exposure is relatively conservative.
Michael Tertilt & Peter Scholz (2017): To Advise, or Not to Advise — How Robo-Advisors Evaluate the Risk Preferences of Private Investors. SSRN Working Paper.
Together with my Ph.D. students David and Sinan, we have written an article for the second edition of the International Conference on European Integration and Sustainable Development.
During financial crises, market participants are pressurized and presumably prone to emotional biased decisions. We use the Economic Policy Uncertainty Indicator and Dow Jones Industrial Average as well as Nikkei 225 GARCH volatilities to test for ambiguity aversion and selective perception of investors. For most crises, we find a significant link between uncertainty and market volatility. However, with respect to ambiguity aversion, the causality differs between crises indicating that investors may not always be driven by uncertainty. Regarding selective perception, we find significant results for the Dot.Com and subprime crises, but not for the Japanese asset price bubble and the Asian crisis.
Peter Scholz, David Großmann & Sinan Krückeberg (2017): Better The Devil You Know Than The Devil You Don’t — Financial Crises between Ambiguity Aversion and Selective Perception. SSRN Working Paper.
Bank business models show diverse risk characteristics, but these differences are not sufficiently considered in Pillar 1 of the regulatory framework. Even if the business model is analyzed within the European SREP, global Pillar 2 approaches differ and could lead to competitive disadvantages. Using the framework of Miles et al. (2012), we examine a dataset of 115 European banks which is split into retail, wholesale, and trading banks. We show that shifts in funding structure affect business models differently. Consequently, a “one size” approach in Pillar 1 for the regulation of banks does not fit all.
David Großmann & Peter Scholz (2017): Bank Regulation — One Size Does Not Fit All. Journal of Applied Finance & Banking (7)5, 1-27.