Martin Eling

The Solvency Ii Process: Overview and Critical Analysis

As early as the 1970s, European Union (EU) member countries implemented rules to coordinate insurance markets and regulation. However, with the more recent movement toward a general single EU market, financial services regulation has taken on new meaning and priority. Solvency I regulations went into effect for member nations by January 2004. The creation of risk-based capital standards, the main focus of Solvency II, now appears likely sometime after 2007. The purpose of the discussion presented here is to outline the specifics of Solvency II as they currently stand and provide input to evaluation process that, ultimately, will determine the exact form of capital regulation. Our analysis leads us to conclude that caution is warranted.

Does the Measure Matter in the Mutual Fund Industry

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 that compared the Sharpe ratio with other performance measures, however, found virtually identical rank ordering by the various measures. The study reported here analyzed a dataset of 38,954 funds investing in seven asset classes over 1996–2005 and found that the previous result is true not only for hedge funds but also for mutual funds investing in stocks, bonds, real estate, funds of hedge funds, commodity trading advisers, and commodity pool operators. In short, choosing a performance measure is not critical to fund evaluation and the Sharpe ratio is generally adequate. The Sharpe ratio measures the relationship between the risk premium (mean excess returns) and the standard deviation of the returns generated by a portfolio, asset, or fund. Hedge funds and other alternative investments are prone to generating returns that have nonnormal distributions. For this reason, a number of researchers have claimed that these funds cannot be adequately evaluated by using the Sharpe ratio. Consideration of this issue has led to the development of numerous new performance measures, including Omega, the Sortino ratio, the Calmar ratio, and the modified Sharpe ratio, all of which are currently being debated in hedge fund literature. Recent research was carried out to compare these new performance measures with the Sharpe ratio by using return data on 2,763 hedge funds. Despite significant deviations of hedge fund returns from a normal distribution, the Sharpe ratio and the other performance measures resulted in virtually identical rank ordering of the hedge funds. These researchers analyzed only hedge funds, however, and thus did not consider whether this result is also true for funds investing in other asset classes. The aim of the study reported here was to address this issue. Combining two large data sets, I analyzed the rankings generated by various performance measures for 38,954 investment funds for the 1996–2005 period. This empirical study investigated 11 performance measures: the Sharpe ratio, Omega, the Sortino ratio, Kappa 3, the upside potential ratio, the Calmar ratio, the Sterling ratio, the Burke ratio, the excess return on value at risk, the conditional Sharpe ratio, and the modified Sharpe ratio. I found that the earlier research result is robust in regard to a large number of asset classes, including stocks, bonds, real estate, hedge funds, funds of hedge funds, commodity trading advisers, and commodity pool operators. This finding has serious implications for performance measurement in the investment industry. From a practical point of view, the Sharpe ratio is adequate for analyzing hedge funds and mutual funds. This finding is in accord with other research findings that, despite some undesirable features, the Sharpe ratio is adequate for analyzing performance throughout the investment industry.

Does Hedge Fund Performance Persist? Overview and New Empirical Evidence

The contribution of this paper is to provide an overview and new empirical evidence on hedge fund performance persistence, which has been a controversial issue in the academic literature during the last several years. In the first step, we review recent studies and put them into a joint evaluation of hedge fund performance persistence. In the second step, the methodological framework developed in the overview is used to present new empirical evidence. We find different levels of performance persistence depending on the statistical methodology and the hedge fund strategy employed. In our study, performance persistence cannot be explained by the use of option-like strategies, but it can be partially explained by survivorship and backfilling bias. Differences among hedge fund strategies might be explained by return smoothing. Finally, we develop a rationale for choosing between different methodologies to measure performance persistence and conclude that the multi-period Kolmogorov-Smirnov test is the most useful for evaluating performance persistence of hedge funds.

The Performance of Microinsurance Programs: A Data Envelopment Analysis

The purpose of this research is to measure the performance of microinsurance programs using data envelopment analysis and to derive implications for the viable provision of microinsurance products. This is a worthwhile exercise given the significant limitations of the existing performance measures used in the microinsurance industry. A single and simple to interpret performance measure can overcome these limitations and provide a sophisticated tool for performance measurement within a multidimensional framework. Moreover, this technique can incorporate the important social function that microinsurers fulfill and provide powerful managerial implications. We illustrate the capabilities of data envelopment analysis using a sample of 20 microinsurance programs and recent innovations from the efficiency literature, such as the bootstrapping of efficiency scores and a truncated regression analysis of efficiency determinants.

Modeling and Management of Nonlinear Dependencies - Copulas in Dynamic Financial Analysis

We study the influence of nonlinear dependencies on a non-life insurers risk and return profile. To achieve this, we integrate several copula models in a dynamic financial analysis framework and conduct numerical tests. We also test risk management strategies in response to adverse outcomes. Nonlinear dependencies have a crucial influence on the insurers risk profile that can hardly be affected by the analyzed management strategies. We find large differences in risk assessment for the ruin probability and for the expected policyholder deficit. This has important implications for insurers, regulators, and rating agencies that use these measures as a foundation for internal risk models, capital standards, and ratings.

Skewed distributions in finance and actuarial science: a review

That the returns on financial assets and insurance claims are not well described by the multivariate normal distribution is generally acknowledged in the literature. This paper presents a review of the use of the skew-normal distribution and its extensions in finance and actuarial science, highlighting known results as well as potential directions for future research. When skewness and kurtosis are present in asset returns, the skew-normal and skew-Student distributions are natural candidates in both theoretical and empirical work. Their parameterization is parsimonious and they are mathematically tractable. In finance, the distributions are interpretable in terms of the efficient markets hypothesis. Furthermore, they lead to theoretical results that are useful for portfolio selection and asset pricing. In actuarial science, the presence of skewness and kurtosis in insurance claims data is the main motivation for using the skew-normal distribution and its extensions. The skew-normal has been used in studies on risk measurement and capital allocation, which are two important research fields in actuarial science. Empirical studies consider the skew-normal distribution because of its flexibility, interpretability, and tractability. This paper comprises four main sections: an overview of skew-normal distributions; a review of skewness in finance, including asset pricing, portfolio selection, time series modeling, and a review of its applications in insurance, in which the use of alternative distribution functions is widespread. The final section summarizes some of the challenges associated with the use of skew-elliptical distributions and points out some directions for future research.

Corporate Governance and Risk Taking: Evidence from the U.K. and German Insurance Markets

We analyze the impact of factors related to corporate governance (i.e., compensation, monitoring, and ownership structure) on risk taking in the insurance industry. We measure asset, product, and financial risk in insurance companies and employ a structural equation model in which corporate governance is modeled as a latent factor. Based on this model, we present empirical evidence on the link between corporate governance and risk taking, considering insurers from two large European insurance markets. Higher levels of compensation, increased monitoring (more independent boards with more meetings), and more blockholders are associated with lower risk taking. Our empirical results provide justification for including factors related to corporate governance in insurance regulation.

The Determinants of Microinsurance Demand

The purpose of this article is to structure the extant knowledge on the determinants of microinsurance demand and to discuss unresolved questions that deserve future research. To achieve this outcome, we review the academic literature on microinsurance demand published between 2000 and early 2013. The review identifies 12 key factors affecting microinsurance demand: price, wealth, risk aversion, non-performance risk, trust and peer effects, religion, financial literacy, informal risk sharing, quality of service, risk exposure, age, and gender. We discuss the evidence of how each of these 12 factors influences demand, both within the microinsurance and the traditional insurance markets. A comparison with traditional markets shows an unexpected (negative) effect of risk aversion on microinsurance demand, with trust perhaps being the intervening factor. Other relevant results include the importance of liquidity (and/or access to credit), informal risk sharing, and peer effects on the decision to buy microinsurance. The influence of trust on insurance take-up and the unanticipated results for risk aversion are fertile areas for future research.

Market-consistent embedded value in non-life insurance: how to measure it and why

Purpose - The purpose of this paper is to transfer the concept of market-consistent embedded value (MCEV) from life to non-life insurance. This is an important undertaking since differences in management techniques between life and non-life insurance make management at the group level very difficult. The purpose of this paper is to offer a solution to this problem. Design/methodology/approach - After explaining MCEV, the authors derive differences between life and non-life insurance and develop a MCEV model for non-life business. The model framework is applied to a German non-life insurance company to illustrate its usefulness in different applications. Findings - The authors show an MCEV calculation based on empirical data and set up an economic balance sheet. The value implications of varying loss ratios, cancellation rates, and costs within a sensitivity analysis are analyzed. The usefulness of the model is illustrated within a value-added analysis. The authors also embed the MCEV concept in a simplified model for an insurance group, to derive group MCEV and outline differences between local GAAP, IFRS and MCEV. Practical implications - The analysis provides new and relevant information to the stakeholders of an insurance company. The model provides information comparable to that provided by embedded value models currently used in the life insurance industry and fills a gap in the literature. The authors reveal significant valuation difference between MCEV and IFRS and argue that there is a need for a consistent MCEV approach at the insurance-group level. Originality/value - The paper presents a new valuation technique for non-life insurance that is easy to use, simple to interpret, and directly comparable to life insurance. Despite the growing policy interest in embedded value, not much academic attention has been given to this methodology. The authors hope that this work will encourage further discussion on this topic in academia and practice.

Research on lapse in life insurance: what has been done and what needs to be done?

The intention of this paper is to review research on lapse in life insurance and to outline potential new areas of research in this field. We consider theoretical lapse rate models as well as empirical research on life insurance lapse and provide a classification of these two streams of research. More than 50 theoretical and empirical papers from this important field of research are reviewed. Challenges for lapse rate modeling, lapse risk mitigation techniques, and possible trends in future lapse behavior are discussed. The risks arising from lapse are of high economic importance. As such, lapsation is of interest not only to academics, but is also highly relevant for the industry, regulators, and policymakers.