Journal of Risk and Insurance 

About: Journal of Risk and Insurance is an academic journal published by Wiley-Blackwell. The journal publishes majorly in the area(s): Life insurance & Insurance policy. It has an ISSN identifier of 0022-4367. Over the lifetime, 2438 publications have been published receiving 71025 citations. The journal is also known as: Risk and insurance.

The Value of Enterprise Risk Management

Abstract: Enterprise risk management (ERM) has been the topic of increased media attention in recent years. The objective of this study is to measure the extent to which specific firms have implemented ERM programs and, then, to assess the value implications of these programs. We focus our attention in this study on U.S. insurers in order to control for differences that might arise from regulatory and market differences across industries. We simultaneously model the determinants of ERM and the effect of ERM on firm value. We estimate the effect of ERM on Tobin's Q, a standard proxy for firm value. We find a positive relation between firm value and the use of ERM. The ERM premium of roughly 20 percent is statistically and economically significant.

Against The Gods: The Remarkable Story of Risk

Abstract: Against the Gods: The Remarkable Story of Risk by Peter L. Bernstein. 1996. New York: John Wiley & Sons. Reviewer: Brian J. Glenn, St. Antony's College, University of Oxford; Insurance Law Center, University of Connecticut School of Law In Against the Gods: The Remarkable Story of Risk, Peter Bernstein presents the reader with an easy to read and often entertaining introduction to the history and theory behind financial risk analysis. The first half of the book is devoted to the development of statistics and utility theory. As Bernstein walks the reader through the history of probability, he brings to life not only the theories being developed, but also the colorful lives of some of the major figures involved, such as Cardano, Pascal, Fermat and several members of the Bernoulli family. Those who use statistics on a daily basis will find the book offers a rich and interesting history behind statistical methods that are otherwise cold and impersonal. In the second half of the book, Bernstein presents the reader with the theory that underlies financial risk analysis. Written in the same historical style as the first half, the second half of the book focuses on issues such as incomplete information, case selection, utility theory, and the appropriateness of quantitative analysis to estimating future events. These standard issues of probability theory are presented in a highly approachable manner. The non-statistician will find these chapters helpful. Those who already understand the material will find Bernstein's handling of it remarkably refreshing. A major issue with the book is the depiction of risk. Bernstein explains that, "The word "risk" derives from the early Italian riscare, which means "to dare." In this sense, risk is a choice rather than a fate. The actions we dare to take, which depend on how free we are to make choices, are what the story of risk is all about." (p. 8) Risk is consistently presented as something to be embraced, rather than something to be avoided. Risk is also depicted as a highly personal decision made in pursuit of financial gain, as opposed to a highly social-or indeed, societal-necessary evil to be shared. In his discussion of utility theory, for example, Bernstein notes that different people have different levels of risk tolerance, "And that's a good thing." he explains, since, "If everyone valued every risk in precisely the same way, many risky opportunities would be passed up ...Without the venturesome, the world would turn a lot more slowly. Think of what life would be like if everyone were phobic about lightening, flying in airplanes, or investing in start-up companies. We are indeed fortunate that human beings differ in their appetite for risk." (p. 105) The wise risk-taking financial entrepreneurs are the heroes in this book. Indeed, after a discussion of how Bernoulli assimilated methods of financial risk assessment, Bernstein declares that, "Risk is no longer something to be faced; risk has become a set of opportunities open to choice." (p. …

A Two-Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration

Abstract: In this paper we consider the evolution of the post-age-60 mortality curve in the UK and its impact on the pricing of the risk associated with aggregate mortality improvements over time: so-called longevity risk. We introduce a two-factor stochastic model for the development of this curve through time. The flrst factor affects mortality-rate dynamics at all ages in the same way, whereas the second factor afiects mortality-rate dynamics at higher ages much more than at lower ages. The paper then examines the pricing of longevity bonds with difierent terms to maturity referenced to difierent cohorts. We flnd that longevity risk over relativelyshort time horizons is very low, but at horizons in excess of 10 years it begins to pick up very rapidly. A key component of the paper is the proposal and development of a method for calculating the market risk-adjusted price of a longevity bond. The proposed adjustment includes not just an allowance for the underlying stochastic mortality but also makes an allowance for parameter risk. We utilise the pricing information contained in the November 2004 European Investment Bank longevity bond to make inferences about the likely market prices of the risks in the model. Based on these, we investigate how future issues might be priced to ensure an absence of arbitrage between bonds with difierent characteristics.

Demography of risk aversion

Abstract: This article uses life insurance data to estimate the Pratt-Arrow coefficient of relative risk aversion for each of nearly 2,400 households. Attitudinal differences toward pure risk are then examined across demographic subgroups. Additionally, differences in speculative risk-taking are examined across demographic groups based on survey responses and compared with the results on pure risk aversion. INTRODUCTION In the mid-1960s, John Pratt and Kenneth Arrow introduced the now-familiar measure of relative risk aversion, along with the hypothesis that relative risk aversion increases with wealth. Since that time, numerous researchers have attempted to estimate the magnitude of relative risk aversion for subsets of the population using a variety of techniques, and others have conducted empirical tests of the increasing relative risk aversion (IRRA) hypothesis. Most recently, attention has turned to comparing risk aversion across different demographic subgroups, particularly men and women. [1] Remarkably, these efforts have been largely independent of one another. Some of those seeking to estimate risk aversion parameters, for example, assumed a utility function exhibiting constant relative risk aversion (CRRA), effectively precluding tests of the IRRA hypothesis. On the other hand, most studies examining the relationship between risk aversion and demographic or wealth variables infer differences in risk aversion parame ters rather than calculating the parameters explicitly. Many use either hypothetical questions or experimental gambling data, and most restrict attention to forms of risk in which both gains and losses are possible. In the present study, the authors integrate and extend these three strands of research. First, the authors derive a reduced form equation for the Pratt-Arrow measure of relative risk aversion without imposing prior assumptions on the shape of the utility function. The authors then estimate the risk aversion parameter empirically for individual households using survey data on life insurance purchases. This gives us more than 2,300 numerical measurements of the Pratt-Arrow coefficient. These measurements are then used to examine differences in relative risk aversion across demographic groups based on age, gender, education, nationality, race, marital and parental status, religion, health and behavioral indicators, and employment status, income, and wealth. The availability of wealth data also allows us to test the IRRA hypothesis. Finally, the authors examine attitudes toward a second type of risk, by studying survey responses to a hypothetical question regarding employment and income risk. The first section briefly reviews the prior research. The second and third sections present the authors' theoretical model and empirical results, respectively, pertaining to relative risk aversion in the context of mortality risk. The fourth section discusses results pertaining to speculative risk, and the article ends with a brief conclusion. PREVIOUS RESEARCH For a concave utility function U defined over wealth of W, Pratt (1964) and Arrow (1965) suggested the elasticity of marginal utility with respect to wealth, or R(W) = -WU"(W)/U'(w), as an appropriate measure of relative risk aversion. Arrow showed that this measure is directly related to one's insistence on favorable odds when putting some fraction of wealth at risk, and Pratt demonstrated that R(W) is proportional to the insurance premium one is willing to pay to avoid a given risk. Both Pratt and Arrow hypothesized that R(W) increases with W; the hypothesis implies that at higher levels of wealth, individuals become less willing to subject a given percentage of wealth to risk. Subsequent empirical research has addressed three central questions: the magnitude of R(W), the IRRA hypothesis, and the relationship between risk aversion and demographic variables. Among the earliest empirical estimates were those by Friend and Blume (1975), who studied the demand for risky assets and concluded that R(W) generally exceeds unity and is probably greater than 2. …