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Journal of Risk and Insurance — Template for authors

Publisher: Wiley

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Guideline source

Categories	Rank	Trend in last 3 yrs
Finance	#52 of 288	down by 15 ranks
Accounting	#32 of 155	down by 2 ranks
Economics and Econometrics	#136 of 661	down by 11 ranks

Journal quality:

High

Last 4 years overview: 158 Published Papers | 571 Citations

Indexed in: Scopus

Last updated: 07/07/2020

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Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

1.512

16% from 2018

Impact factor for Journal of Risk and Insurance from 2016 - 2019
Year	Value
2019	1.512
2018	1.795
2017	1.606
2016	1.343

Graph view

3.6

3% from 2019

CiteRatio for Journal of Risk and Insurance from 2016 - 2020
Year	Value
2020	3.6
2019	3.7
2018	3.1
2017	3.0
2016	3.3

Graph view

Insights

Impact factor of this journal has decreased by 16% in last year.
This journal’s impact factor is in the top 10 percentile category.

Insights

CiteRatio of this journal has decreased by 3% in last years.
This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.055

35% from 2019

SJR for Journal of Risk and Insurance from 2016 - 2020
Year	Value
2020	1.055
2019	1.627
2018	1.197
2017	0.788
2016	1.355

Graph view

1.587

28% from 2019

SNIP for Journal of Risk and Insurance from 2016 - 2020
Year	Value
2020	1.587
2019	2.205
2018	1.803
2017	1.961
2016	1.641

Graph view

Insights

SJR of this journal has decreased by 35% in last years.
This journal’s SJR is in the top 10 percentile category.

Insights

SNIP of this journal has decreased by 28% in last years.
This journal’s SNIP is in the top 10 percentile category.

Journal of Risk and Insurance

Guideline source: View

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Wiley

Journal of Risk and Insurance

The Journal of Risk and Insurance is the flagship journal for the American Risk and Insurance Association. The JRI is the most well recognized academic risk management and insurance journal in the world and is currently indexed by the American Economic Association's Economic Literature Index, the Finance Literature Index, the Social Sciences Citation Index, ABI/Inform, Business and Company ASAP, Lexis-Nexis, Dow Jones Interactive, and others. All back issues, i.e., 1933-2001, are now available on JSTOR. The Journal of Risk and Insurance publishes rigorous, original research in insurance and risk management. This includes the following areas of specialization: 1. Industrial organization of insurance markets; 2. Management of risks in the private and public sectors; 3. Insurance finance, financial pricing, financial management; 4. Economics of employee benefits, pension plans, and social insurance; 5. Utility theory and demand for insurance; 6. Asymmetric information, moral hazard, and adverse selection; 7. Insurance regulation; 8. Econometric, actuarial, and statistical methodology; 9. Economics of insurance institutions; 10. Insurance cycles and economic cycles of insurance markets; Both theoretical and empirical submissions are encouraged. Empirical work must provide tests of hypotheses based on sound theoretical foundations. Read Less

Finance

Accounting

Economics and Econometrics

Economics, Econometrics and Finance

Last updated on	07 Jul 2020
ISSN	0022-4367
Impact Factor	High - 1.636
Open Access	Yes
Sherpa RoMEO Archiving Policy	Yellow
Plagiarism Check	Available via Turnitin
Endnote Style	Download Available
Bibliography Name	apa
Citation Type	Numbered [25]
Bibliography Example	Beenakker, C.W.J. (2006) Specular andreev reflection in graphene.Phys. Rev. Lett., 97 (6), 067 007. URL 10.1103/PhysRevLett.97.067007.

Top papers written in this journal

Journal Article • DOI: 10.2307/2678139 •

Stochastic Processes for Insurance and Finance

Larry Y. Tzeng, Volker Schmidt,

01 Mar 2001 - Journal of Risk and Insurance

Topics:

Stochastic discount factor (77%)77% related to the paper, Stochastic modelling (69%)69% related to the paper

994 Citations

Journal Article • DOI: 10.1111/J.1539-6975.2011.01413.X •

The Value of Enterprise Risk Management

Robert E. Hoyt¹, Andre P. Liebenberg² •

01 Dec 2011 - Journal of Risk and Insurance

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 or... 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. read more

Topics:

Enterprise value (58%)58% related to the paper, Enterprise risk management (57%)57% related to the paper

View PDF

748 Citations

Journal Article • DOI: 10.2307/253563 •

Against The Gods: The Remarkable Story of Risk

Brian J. Glenn, Peter L. Bernstein

01 Sep 1999 - Journal of Risk and Insurance

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 wit... 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. … read more

Topics:

Financial risk (55%)55% related to the paper

747 Citations

Open access • Journal Article • DOI: 10.1111/J.1539-6975.2006.00195.X •

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

Andrew J. G. Cairns¹, David Blake², •

01 Dec 2006 - Journal of Risk and Insurance

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 affect... 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. read more

Topics:

Longevity risk (59%)59% related to the paper, Bond (51%)51% related to the paper, Arbitrage (50%)50% related to the paper,

View PDF

704 Citations

Journal Article • DOI: 10.2307/2678130 •

Demography of risk aversion

Martin Halek, Joseph G. Eisenhauer

01 Mar 2001 - Journal of Risk and Insurance

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... 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. … read more

Topics:

Risk aversion (63%)63% related to the paper, Spectral risk measure (63%)63% related to the paper, Time consistency (54%)54% related to the paper,

684 Citations

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13. What is Sherpa RoMEO Archiving Policy for Journal of Risk and Insurance?

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Journal of Risk and Insurance. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour	Archiving policy
Green	Can archive pre-print and post-print or publisher's version/PDF
Blue	Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow	Can archive pre-print (ie pre-refereeing)
White	Archiving not formally supported

FYI:

Pre-prints as being the version of the paper before peer review and
Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Journal of Risk and Insurance?

The 5 most common citation types in order of usage for Journal of Risk and Insurance are:.

S. No.	Citation Style Type
1.	Author Year
2.	Numbered
3.	Numbered (Superscripted)
4.	Author Year (Cited Pages)
5.	Footnote

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Journal of Risk and Insurance — Template for authors

Related Journals

Journal Performance & Insights

Impact Factor

CiteRatio

1.512

3.6

Insights

Insights

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

1.055

1.587

Insights

Insights

Journal of Risk and Insurance

Journal of Risk and Insurance

Top papers written in this journal

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Abstract:

Topics:

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Topics:

Abstract:

Topics:

Abstract:

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What to expect from SciSpace?

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Plagiarism Reports via Turnitin

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Trusted by academicians

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