A5064432251- Insurance and Financial Risk Management
- Insurance, Mortality, Demography, Risk Management
- Banking stability, regulation, efficiency
- Financial Markets and Investment Strategies
- Agricultural risk and resilience
- Financial Risk and Volatility Modeling
- Probability and Risk Models
- Corporate Governance and Management
- Social and Demographic Issues in Germany
- Risk and Portfolio Optimization
- Healthcare Policy and Management
- Risk Management in Financial Firms
- Information and Cyber Security
- Credit Risk and Financial Regulations
- Law, Economics, and Judicial Systems
- Housing Market and Economics
- Financial Literacy, Pension, Retirement Analysis
- finance, banking, and market dynamics
- Market Dynamics and Volatility
- Cybercrime and Law Enforcement Studies
- Global Health Care Issues
- Corporate Finance and Governance
- Social Policies and Healthcare Reform
- German Economic Analysis & Policies
- Decision-Making and Behavioral Economics
University of St. Gallen
2015-2024
Universität Ulm
2008-2016
Helmholtz-Institute Ulm
2009-2016
University of Wisconsin–Madison
2007-2008
University of Münster
2005
A frequent comment is that investment funds with a nonnormal return distribution cannot be adequately evaluated by using the classic Sharpe ratio. Research on hedge fund data compared ratio other performance measures, however, found virtually identical rank ordering various measures. The study reported here analyzed dataset of 38,954 investing in seven asset classes over 1996–2005 and previous result true not only for but also mutual stocks, bonds, real estate, funds, commodity trading...
Abstract As early as the 1970s, European Union (EU) member countries implemented rules to coordinate insurance markets and regulation. However, with more recent movement toward a general single EU market, financial services regulation has taken on new meaning priority. Solvency I regulations went into effect for nations by January 2004. The creation of risk‐based capital standards, main focus II, now appears likely sometime after 2007. purpose discussion presented here is outline specifics...
Purpose This paper aims to provide an overview of the main research topics in emerging fields cyber risk and insurance. The also illustrates future directions, from both academic practical points view. Design/methodology/approach authors conduct a literature review on insurance using standardized search identification process that has been used various articles. Based upon this selection process, database 209 papers is created. results findings are extracted organized seven clusters....
Abstract We analyze the impact of factors related to corporate governance (i.e., compensation, monitoring, and ownership structure) on risk taking in insurance industry. measure asset, product, financial companies employ a structural equation model which is modeled as latent factor. Based this model, we present empirical evidence link between taking, considering insurers from two large European markets. Higher levels increased monitoring (more independent boards with more meetings),...
Abstract Based on a data set of 91 papers and 22 industry studies, we analyse the impact artificial intelligence insurance sector using Porter’s (1985) value chain Berliner’s (1982) insurability criteria. Additionally, present future research directions, from both academic practitioner points view. The results illustrate that cost efficiencies new revenue streams can be realised, as business model will shift loss compensation to prediction prevention. Moreover, identify two possible...
Abstract Cybersecurity research started in the late 1960s and has continuously evolved under different names such as computer security information security. This article briefly covers that history but will especially focus on latest incarnation known “cyber risk management,” which includes both technical economic/management dimensions. The main of is to review individual steps cyber management process overall highlight gaps determine directions. Two findings are difficult include enterprise...
Abstract With the largest data set ever used for this purpose (covering more than 1 million contracts), we analyze impact of product and policyholder characteristics on lapse in life insurance market. The are provided by a German insurer cover two periods market turmoil that incorporate into our proportional hazards generalized linear models. results show such as type or contract age gender important drivers rates. Our findings improve understanding might be managers regulators value‐...