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INSURANCE (26 journals)

Showing 1 - 26 of 26 Journals sorted alphabetically
Annals of Actuarial Science     Full-text available via subscription   (Followers: 2)
Assurances et gestion des risques     Full-text available via subscription  
Astin Bulletin     Full-text available via subscription   (Followers: 1)
Banks in Insurance Report     Hybrid Journal   (Followers: 1)
Blätter der DGVFM     Hybrid Journal   (Followers: 2)
British Actuarial Journal     Full-text available via subscription   (Followers: 1)
Geneva Papers on Risk and Insurance - Issues and Practice     Hybrid Journal   (Followers: 14)
Geneva Risk and Insurance Review     Hybrid Journal   (Followers: 8)
Health Affairs     Full-text available via subscription   (Followers: 83)
Insurance Markets and Companies     Open Access   (Followers: 1)
Insurance: Mathematics and Economics     Hybrid Journal   (Followers: 10)
International Journal of Business Continuity and Risk Management     Hybrid Journal   (Followers: 28)
International Journal of Forensic Engineering     Hybrid Journal   (Followers: 3)
International Journal of Forensic Engineering and Management     Hybrid Journal   (Followers: 3)
International Journal of Health Economics and Management     Hybrid Journal   (Followers: 12)
International Social Security Review     Hybrid Journal   (Followers: 8)
Journal for Labour Market Research     Open Access   (Followers: 10)
Journal of Derivatives & Hedge Funds     Hybrid Journal   (Followers: 9)
Journal of Risk and Insurance     Hybrid Journal   (Followers: 18)
Journal of Risk Finance     Hybrid Journal   (Followers: 6)
Risk Management     Hybrid Journal   (Followers: 15)
Risk Management & Insurance Review     Hybrid Journal   (Followers: 11)
Scandinavian Actuarial Journal     Hybrid Journal   (Followers: 2)
SourceOECD Finance & Investment/Insurance & Pensions     Full-text available via subscription   (Followers: 3)
The Geneva Reports     Free   (Followers: 2)
Zeitschrift für die gesamte Versicherungswissenschaft     Hybrid Journal   (Followers: 1)
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Journal Cover
Risk Management
Journal Prestige (SJR): 0.189
Citation Impact (citeScore): 1
Number of Followers: 15  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1460-3799 - ISSN (Online) 1743-4637
Published by Springer-Verlag Homepage  [2658 journals]
  • Correction to: Achieving financial stability during a liquidity crisis: a
           multi‑objective approach

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      PubDate: 2021-08-27
       
  • A refined measure of conditional maximum drawdown

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      Abstract: Risks associated to maximum drawdown have been recently formalized as the tail mean of the maximum drawdown distribution, called Conditional Expected Drawdown (CED). In fact, the special case of average maximum drawdown is widely used in the fund management industry also in association to performance management. It lacks relevant information on worst case scenarios over a fixed horizon. Formulating a refined version of CED, we are able to add this piece of information to the risk measurement of drawdown, and then get a risk measure for processes that preserves all the good properties of CED but following more prudential regulatory and management assessments, also in term of marginal risk contribution attributed to factors. As a special application, we consider the conditioning information given by the all time minimum of cumulative returns.
      PubDate: 2021-08-24
       
  • IRB PD model accuracy validation in the presence of default correlation: a
           twin confidence interval approach

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      Abstract: The BIS indicated in July 2020 an unprecedented rise in default risk correlation as a result of pandemics-induced credit risks’ accumulation. A third of the world banking assets credit risk measurement depends on the Basel internal-ratings-based (IRB) models. To ensure financial stability, we wish IRB models to be accurate in default probability (PD) forecasting. There naturally arises a question of which model may be deemed accurate if the data demonstrates the presence of the default correlation. The existing prudential IRB validation guidelines suggest a confidence interval of up to 100 percentage points’ length for such a case. Such an interval is useless as any model and any PD forecast seem accurate. The novelty of this paper is the justification for the use of twin confidence intervals to validate PD model accuracy. Those intervals more concentrate around the two extremes (default and its absence), the higher the default correlation is.
      PubDate: 2021-08-09
      DOI: 10.1057/s41283-021-00079-2
       
  • Business strategy, market power, and stock price crash risk: Evidence from
           China

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      Abstract: Business strategies play a vital role in a firm’s success but, if not properly executed, can lead to financial irregularities and mispricing, influencing the firm’s performance and leading to stock price crash risk. The present study examines the impact of firm’s business strategy and market power on stock price crash risk. Following Miles and Snow’s (2003) model, we classified Chinese firms listed on the Shenzhen and Shanghai stock exchanges into defenders (conservative) and prospectors’ (aggressive) business strategies over a period of 2006–2019. We employed industry and year fixed effects regression to show that prospectors who follow aggressive strategies are more prone to stock price crash risk than defenders who follow conservative strategies. Additionally, we show that firms with high market power also contribute to increased stock price crash risk. Our results are also robust to alternative control variables and different statistical models like the two-stage least squares method.
      PubDate: 2021-08-09
      DOI: 10.1057/s41283-021-00080-9
       
  • A visual risk identification and early warning research for college net
           loan based on microblog texts

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      Abstract: By analyzing microblog texts, a visual early warning research of college net loans is conducted in this paper to effectively reduce the negative impact of illegal Internet loans (abbreviated as "net loans") on college students' lives. Two calculation models are proposed in our research: One is the Identification Model of Risk Degree (IMRD) based on the security level of microblog texts about net loans. The other is the Calculation Model of Relationship Closeness (CMRC) based on three dimensions: user's relevant relationship, interaction strength, and interest similarity. IMRD is used to identify the risk of microblog net loan texts, and determine whether to early warn or not. CMRC is utilized to acquire a net loan communication map by describing the closeness level between net loan microblog publishers and their followers, and analyzing the possibility of retweeting. A visual monitoring and early warning platform is constructed based on these two models. With this platform, further spread of net loan information can be prevented by analyzing the graph and cutting off key nodes in time. The early warning mechanism of this research can effectively alleviate the negative influence of illegal net loans.
      PubDate: 2021-06-29
      DOI: 10.1057/s41283-021-00078-3
       
  • Is the ESG portfolio less turbulent than a market benchmark portfolio'

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      Abstract: Given that there is no consensus on the fact that ESG portfolios are characterized by very high returns and very low risks compared to conventional portfolios, this study aims to empirically verify whether the series of returns of an ESG portfolio is less volatile than the returns of a benchmark market portfolio. To verify this hypothesis, we used the Markov-switching GARCH models in order to model the process of the series of daily returns of the ESG portfolio “MSCI USA ESG Select,” as well as those of the market benchmark portfolio daily returns series “S&P 500,” during the period June 01, 2005 to December 31, 2020 as well as that excluding the COVID19 crisis and from June 1, 2005 to October 29, 2019. It can be concluded that the ESG portfolio “MSCI USA ESG Select” is relatively less turbulentcompared to the market benchmark portfolio “S&P 500.”
      PubDate: 2021-06-25
      DOI: 10.1057/s41283-021-00077-4
       
  • Irrational risk-taking of professionals' The relationship between risk
           exposures and previous profits

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      Abstract: The risk attitude of investors is a key factor determining financial asset prices and market trends. Changes in risk attitude may be due to the interference of macro-level (business cycle) and micro-level (individual experience) effects. We investigate the impact of individual experience on the subsequent risk-taking attitude of professionals via the analysis of the trading activity of 351 non-financial firms and (non-bank) financial institutions (insurance companies, financial intermediaries, etc.) covering 57,039 FX forward transactions in a highly volatile period between January 2008 and November 2012. Panel regressions for all firms and institutions do not show significant behavioral patterns. When investigating each client separately, however, we find that 39.7% of the clients having enough transactions to analyze statistically tend to increase their risk exposure irrationally after large gains or losses which can be the manifestation of the break-even and house-money effects well-documented in the literature for non-professionals. This irrational behavior may destroy value, so both market players and regulators should pay attention to monitor and control it.
      PubDate: 2021-06-11
      DOI: 10.1057/s41283-021-00076-5
       
  • Alpha enhancement in global equity markets with ESG overlay on
           factor-based investment strategies

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      Abstract: Studies show that companies with a strong Environment, Social and Governance (ESG) profile are more competitive than their peers, as they use resources, human capital and innovation more efficiently. High ESG-rated companies have lower exposure to systematic risk factors and low expected cost of capital, leading to higher valuations in a DCF model framework. They are typically more transparent, particularly with respect to their risk exposures, risk management and governance standards and have better long-term vision. The paper finds that higher Alpha can be harvested by restricting investment exposure to the ESG theme combined with various style characteristics, as they display low systematic and idiosyncratic tail risks. It shows that an ESG overlay on such factor-based strategies, particularly on ‘multi-factor’, ‘value’ and ‘low volatility’ in that order, reduces both systematic and idiosyncratic risks further. ESG overlay on ‘quality’ factor provides the highest return among ESG target indices, however, the underlying ‘quality’ factor provides even higher excess return. These findings can provide some insight on return enhancement to investors investing in the global equity markets.
      PubDate: 2021-06-08
      DOI: 10.1057/s41283-021-00075-6
       
  • Covid-19 and high-yield emerging market bonds: insights for liquidity risk
           management

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      Abstract: Around the apogee of the pandemic crisis in late March 2020, trading liquidity has evaporated out of high-yield (HY) bond markets across developing states. Concerned about this phenomenon, we assess emerging market (EM) debt liquidity as a combination of three metrics: (i) bid–ask spreads; (ii) relative liquidity score incorporating market depth, trading volumes, and time needed to liquidate an asset; and (iii) round-trip transaction costs—evidencing that all have worsened by the end of the first quarter of 2020. We complement our analysis by tracking the dynamics of the option-adjusted spreads of the EM HY bonds and document that the recovery trends of the credit and liquidity components in bonds spreads have decoupled in the aftermath of the Covid-triggered global meltdown. We evidence relevant differences in bond liquidity between chosen countries, representative of geopolitical regions. All the considered liquidity measures provide a coherent picture of the pandemic impact and allow for insights regarding the recovery from the crisis turmoil and the risk management of the EM HY bond portfolios throughout a systemic crisis.
      PubDate: 2021-04-30
      DOI: 10.1057/s41283-021-00074-7
       
  • Are stock prices driven by expected growth rather than discount rates'
           Evidence based on the COVID-19 crisis

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      Abstract: We use the Gordon (Rev Econ Stat 41(2):99-105, 1959) constant growth model to gauge the effects from innovations in implied growth versus discount rates. During the COVID-19 downturn and the Global Financial Crisis (GFC), stock returns were largely affected by a change in the long-run implied growth rate and only to a lesser extent by a change in discount rate, the latter typically used to explain stock returns in the classical asset pricing literature. We reach this conclusion by using ordinary least-squares (OLS) regressions of stock returns on the unobservable Gordon factors, which we estimate from firm-level valuation ratios D/P, P/E, and P/B. The effects from a decrease in implied growth outweigh those from an increase in discount rate by a factor of approximately 1.6 to 1.7. Also, firms with a decrease in implied growth show a stock return that is approximately 6.6% more negative than that of firms with no decrease in implied growth. Investors can infer valuable information from the joint interpretation of underlying market fundamentals as derived from the Gordon model.
      PubDate: 2021-04-14
      DOI: 10.1057/s41283-021-00070-x
       
  • Do risk management committee characteristics influence the market value of
           firms'

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      Abstract: This study aims to examine the effects of the risk management committee’s characteristics on the market performance of non-financial listed firms in Malaysia between 2015 and 2017. The regression result shows that risk management committee (RMC) size, independence, expertise and female RMC members have a substantial negative influence on firm performance. By employing a different measurement of expertise, further analysis shows that RMC members with risk management expertise have a significantly positive relationship with firm performance. The results suggest that RMC members with specific risk management expertise can promote efficient risk monitoring, thus, enhancing the value of firms compared to RMC members with only general financial and accounting backgrounds. Nevertheless, the results are the same for the female members of the RMC even though different measurements are used. The robust negative result is supported by the tokenism interpretation for female members in the risk management committee.
      PubDate: 2021-04-11
      DOI: 10.1057/s41283-021-00073-8
       
  • Determinants of corporate exposure at default under distressed economic
           and financial conditions in a developing economy: the case of Zimbabwe

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      Abstract: We design ordinary least squares (OLS) regression models to estimate the credit conversion factor (CCF) in order to precisely predict the EAD at the account level for defaulted private nonfinancial corporations having credit lines under distressed economic and financial conditions in a developing economy. Our primary focus is on identifying and interpreting the CCF determinants for the defaulted privately owned corporates with credit lines. We apply the models to a unique real-life cross-sectional dataset of defaulted Zimbabwean private corporations. Our empirical results show that the committed amount, the credit usage, the drawn amount, the time to default, the total assets, the ratio of bank debt to total assets, the current ratio, the earnings before interest and tax to total assets ratio, the real gross domestic product growth rate, and the inflation rate are all substantial drivers of the CCF for Zimbabwean private corporates with credit lines. We observe that accounting information is essential in analysing the CCF for private corporations with credit lines under downturn conditions in a developing country. Furthermore, we reveal that the CCF models' forecasting results and the corresponding EAD estimates are augmented by including macroeconomic variables.
      PubDate: 2021-03-31
      DOI: 10.1057/s41283-021-00071-w
       
  • On management risk and price in the mutual fund industry: style and
           performance distribution analysis

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      Abstract: This study shows how investing in mutual funds involves an additional risk, which we call management risk as a consequence of the uncertainty in the results of active management. To address this issue, we analyze a sample of 2539 US equity mutual funds. For comparative purposes, we differentiate among index funds and actively managed mutual funds with different investment styles. We observe that performance distribution shows negative mean, negative skewness, and excess kurtosis. Results also show that management risk is not rewarded with higher abnormal performance. Moreover, higher active management prices are linked to funds with higher management risk and negative asymmetry. Therefore, investors seem to be risk-seeking since they are paying more to participate in high asymmetric bets. Finally, we attempt to solve this puzzle from the behavioral finance perspective.
      PubDate: 2021-03-29
      DOI: 10.1057/s41283-021-00072-9
       
  • The maximum-return-and-minimum-volatility effect: evidence from choosing
           risky and riskless assets to form a portfolio

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      Abstract: The healthcare sector has the highest mean and a low correlation with the business cycle, while Treasury Bills (T-Bills) have the lowest variance in our study. In this paper, we examine the conjecture of whether investors should choose an asset with the highest expected return and an asset with the smallest variance even when the mean–variance rule says “NO”. We examine the conjecture by comparing the performance of portfolios with and without healthcare and 6-M T-bills in the US market. Our findings support the conjecture that investors prefer to invest in portfolios with both healthcare and 6-M T-bills. In addition, we find an arbitrage opportunity in the markets and our findings reject market efficiency. Based on our findings, academics could incorporate both maximum-return and minimum-volatility assets to construct a maximum-return-and-minimum-volatility aggressive-and-yet-defensive trading approach that stochastically dominates most of other assets/portfolios. Thus, our findings can be called the maximum-return-and-minimum-volatility anomaly or the maximum-return-and-minimum-volatility puzzle, or the maximum-return-and-minimum-volatility paradox.
      PubDate: 2021-03-29
      DOI: 10.1057/s41283-021-00069-4
       
  • Risk assessment of VAT invoice crime levels of companies based on DFPSVM:
           a case study in China

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      Abstract: In recent years, with the implementation of the policy of “Replacing Business Tax with Value-Added Tax” and “Streamlining Administration, Delegating Powers and Improving Regulation and Services” in China, criminals have been issuing false invoices, and such cases have shown a trend of high frequency in the category of economic crimes. Tax departments and public security departments are facing increasingly a serious crime situation that has created a new challenge. By studying the current trend of false invoice crime, the difficulties of investigation in such cases are analyzed. Using the tax information of enterprises that have conducted false invoice as the breakthrough point, the machine learning method is introduced to build a risk pre-warning assessment model based on the Support Vector Machine (SVM) method to detect enterprises issuing false invoices. Three steps were designed in this paper. First, a risk pre-warning assessment model was established to detect enterprises issuing false invoices. Second, enterprises were classified into three groups according to the risk levels: A, B, and C. Third, collected data were used to make an empirical analysis, and the results show that the accuracy rate of the model is 97%. In China, due to the high crime rate of tax fraud cases, it is important to obtain data from tax and public security departments to establish a model that can detect such crimes as early as possible. The police and tax authorities can use this model to jointly combat such crimes.
      PubDate: 2021-03-13
      DOI: 10.1057/s41283-021-00068-5
       
  • Achieving financial stability during a liquidity crisis: a multi-objective
           approach

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      Abstract: Following the financial crisis of 2007, regulators undertook an ample process of redefinition of the necessary objectives to achieve financial stability. Nevertheless, it is highly likely that the achievement of a specific stability goal precludes the possibility of pursuing other stability goals during financial turmoil. Once considered in this way, financial stability can be immediately translated into a multi-objective decision-making problem. In this paper, we analyze some possible trade-offs faced by a regulator in order to preserve financial stability during a liquidity crisis. To this end, we employ a model of liquidity cascades applied to credit networks and we determine the best among different policy options relying on the MOORA (multi-objective optimization on the basis of ratio analysis) method.
      PubDate: 2021-02-12
      DOI: 10.1057/s41283-021-00067-6
       
  • CEO overconfidence, firm-specific factors, and systemic risk: evidence
           from China

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      Abstract: This study aims to measure the contribution of banks, financial services institutions, and insurance companies to China’s systemic risk during the 2004–2018 period. This study also evaluates the effect of CEO (chief executive officer) overconfidence and firm-level factors on systemic risk. We employ ΔCoVaR (delta conditional value-at-risk) as a measure of systemic risk and earnings forecast bias to measure CEO overconfidence. We use a fixed effects panel regression approach to evaluate the effect of CEO overconfidence, firm-level factors, and systemic risk. Our findings show that banks that are managed by overconfident CEOs enhance the firm’s contributions to systemic risk. Empirical results also show that the firm’s size, leverage ratio, and loan ratio increase the firm’s contributions to systemic risk. Furthermore, return on assets is found to have an inverse relation with systemic risk. The results of this study are important for constructing financial regulations and policies to mitigate the impact of these factors on systemic risk in China.
      PubDate: 2021-02-08
      DOI: 10.1057/s41283-021-00066-7
       
  • China’s growing influence and risk in Asia–Pacific stock markets:
           evidence from spillover effects and market integration

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      Abstract: This study examines China’s influence in the Asia–Pacific stock markets by focusing on spillover effects and market integration and employs how the financial crises and financial liberalization affect the relationship among these markets. Based on the series of studies of Diebold and Yilmaz (2009, 2012, 2015), this study employs the generalized vector autoregressive framework to examine the spillover effects among the main Asia–Pacific stock markets. The multifactor R-squared measure proposed by Pukthuanthong and Roll (2009) is employed to examine the market integration of Chinese stock market. The results indicate that spillover effects and market integration tend to increase, indicating that China stock market is playing a more important role in the Asia–Pacific stock markets. This study provides more evidence that financial crises and financial liberalization can strengthen spillover effects and market integration.
      PubDate: 2020-10-30
      DOI: 10.1057/s41283-020-00065-0
       
  • Measuring the contribution of Chinese financial institutions to systemic
           risk: an extended asymmetric CoVaR approach

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      Abstract: This study proposes an extension of the Asymmetric CoVaR method in Espinosa et al. (J Bank Finance 58: 471–485, 2015) to capture the time-varying asymmetric responses of the financial system to positive and negative shocks to individual institutions. Building on the extended method and considering a set of Chinese financial institutions, we assess the extent to which distress within different institutions contribute to systemic risk. To provide a formal ranking of risk contributions, we implement the significance and dominance tests with bootstrap Kolmogorov–Smirnov statistics. The estimates of the extended Asymmetric CoVaR method reveal an asymmetric pattern that characterizes the tail interdependence in the Chinese financial system and this pattern changes dynamically over time. Particularly, the impact on the system of a fall in individual market value is only slightly larger than that of an increase during tranquil years. However, the entire system becomes extremely sensitive to downside losses than to upside gains during crises. The result also raises concern about privately owned banks in that they are systemically riskier than state-owned banks and other institutions. Using panel regressions, we also find firm characteristics such as institution size and volatility are important predictors of systemic risk contribution.
      PubDate: 2020-10-20
      DOI: 10.1057/s41283-020-00064-1
       
  • Cybersecurity hazards and financial system vulnerability: a synthesis of
           literature

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      Abstract: In this paper, we provide a systematic review of the growing body of literature exploring the issues related to pervasive effects of cybersecurity risk on the financial system. As the cybersecurity risk has appeared as a significant threat to the financial sector, researchers and analysts are trying to understand this problem from different perspectives. There are plenty of documents providing conceptual discussions, technical analysis, and survey results, but empirical studies based on real data are yet limited. Besides, the international and national regulatory bodies suggest guidelines to help banks and financial institutions managing cyber risk exposure. In this paper, we synthesize relevant articles and policy documents on cybersecurity risk, focusing on the dimensions detrimental to the banking system’s vulnerability. Finally, we propose five new research avenues for consideration that may enhance our knowledge of cybersecurity risk and help practitioners develop a better cyber risk management framework.
      PubDate: 2020-08-18
      DOI: 10.1057/s41283-020-00063-2
       
 
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