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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 of Risk Finance
Journal Prestige (SJR): 0.168
Number of Followers: 6  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1526-5943 - ISSN (Online) 2331-2947
Published by Emerald Homepage  [362 journals]
  • Risk assessment for financial accounting: modeling probability of default

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      Authors: Tobias Filusch
      Abstract: This paper aims to introduce and tests models for point-in-time probability of default (PD) term structures as required by international accounting standards. Corresponding accounting standards prescribe that expected credit losses (ECLs) be recognized for the impairment of financial instruments, for which the probability of default strongly embodies the included default risk. This paper fills the research gap resulting from a lack of models that expand upon existing risk management techniques, link PD term structures of different risk classes and are compliant with accounting standards, e.g. offering the flexibility for business cycle-related variations. The author modifies the non-homogeneous continuous-time Markov chain model (NHCTMCM) by Bluhm and Overbeck (2007a, 2007b) and introduces the generalized through-the-cycle model (GTTCM), which generalizes the homogeneous Markov chain approach to a point-in-time model. As part of the overall ECL estimation, an empirical study using Standard and Poor’s (S&P) transition data compares the performance of these models using the mean squared error. The models can reflect observed PD term structures associated with different time periods. The modified NHCTMCM performs best at the expense of higher complexity and only its cumulative PD term structures can be transferred to valid ECL-relevant unconditional PD term structures. For direct calibration to these unconditional PD term structures, the GTTCM is only slightly worse. Moreover, it requires only half of the number of parameters that its competitor does. Both models are useful additions to the implementation of accounting regulations. The tests are only carried out for 15-year samples within a 35-year span of available S&P transition data. Furthermore, a point-in-time forecast of the PD term structure requires a link to the business cycle, which seems difficult to find, but is in principle necessary corresponding to the accounting requirements. Research findings are useful for practitioners, who apply and develop the ECL models of financial accounting. The innovative models expand upon the existing methodologies for assessing financial risks, motivated by the practical requirements of new financial accounting standards.
      Citation: Journal of Risk Finance
      PubDate: 2021-01-05
      DOI: 10.1108/JRF-02-2020-0033
      Issue No: Vol. 21, No. 5 (2021)
       
  • Comparative analysis of interest rate term structures in the Solvency II
           environment

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      Authors: Mariano Gonzalez Sanchez, Sonia Rodriguez-Sanchez
      Abstract: Solvency-II is the current regulatory framework of insurance companies in the European Union. Under this standard, European Insurance and Occupational Pension Authority (EIOPA), as a regulatory board, has established that the Smith–Wilson (SW) model can be used as the model to estimate interest rate curve. This paper aims to analyze whether this model adjusts to the market curve better than Nelson–Siegel (NS) and whether the values set for the parameters are adequate. This empirical study analyzes whether the SW interest rate curve shows lower root mean squared errors than the NS curve for a sample of daily prices of Spanish Government bonds between 2014 and 2019. The results indicate that NS adjusts the market data better, the parameters recommended by the EIOPA correspond to the maximum values observed in the sample period and the current recommended curve for insurance companies underestimates company operations. This paper verifies that the criterion of the last liquid point does not allow for selecting an optimal sample to adjust the curve and criteria based on prices without arbitrage opportunities are more appropriate.
      Citation: Journal of Risk Finance
      PubDate: 2021-01-04
      DOI: 10.1108/JRF-04-2020-0067
      Issue No: Vol. 21, No. 5 (2021)
       
  • US policy uncertainty and stock returns: evidence in the US and its
           spillovers to the European Union, China and Japan

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      Authors: Thomas C. Chiang
      Abstract: Recent empirical studies by Antonakakis, Chatziantoniou and Filis (2013), Brogaard and Detzel (2015) and Christou et al. (2017) present evidence, which supports the notion that a rise in economic policy uncertainty (EPU) will lead to a decline in stock prices. The purpose of this paper is to examine US categorical policy uncertainty on stock returns while controlling for implied volatility and downside risk. In addition to the domestic impacts of policy uncertainty, this paper also presents evidence that changes in US policy uncertainty promptly propagates to the global stock markets. This study uses a GED-GARCH (1, 1) model to estimate changes of uncertainties in US monetary, fiscal and trade policies on stock returns for the sample period of January 1990–December 2018. Robustness test is conducted by using different set of data and modeling techniques. This paper contributes to the literature in several aspects. First, testing of US aggregate data while controlling for downside risk and implied volatility, consistently, shows that responses of stock prices to US policy uncertainty changes, not only display a negative effect in the current period but also have at least a one-month time-lag. The evidence supports the uncertainty premium hypothesis. Second, extending the test to global data reveals that US policy uncertainty changes have a negative impact on markets in Europe, China and Japan. Third, testing the data in sectoral stock markets mainly displays statistically significant results with a negative sign. Fourth, the evidence consistently shows that changes in policy uncertainty present an inverse relation to the stock returns, regardless of whether uncertainty is moving upward or downward. The current research is limited to the markets in the USA, eurozone, China and Japan. This study can be extended to additional countries, such as emerging markets. This paper provides a model that uses categorical policy uncertainty approach to explain stock price changes. The parametric estimates provide insightful information in advising investors for making portfolio decision. The estimated coefficients of changes in monetary policy uncertainty, fiscal policy uncertainty and trade policy uncertainty are informative in assisting policymakers to formulate effective financial policies. This study extends the existing risk premium model in several directions. First, it separates the financial risk factors from the EPU innovations; second, instead of using EPU, this study investigates the effects from monetary policy, fiscal policy and trade policy uncertainties; third, in additional to an examination of the effects of US categorical policy uncertainties on its own markets, this study also investigates the spillover effects to global major markets; fourth, besides the aggregate stock markets, this study estimates the effects of US policy uncertainty innovations on the sectoral stock returns.
      Citation: Journal of Risk Finance
      PubDate: 2020-12-10
      DOI: 10.1108/JRF-10-2019-0190
      Issue No: Vol. 21, No. 5 (2020)
       
  • An augmented macroeconomic linear factor model of South African industrial
           sector returns

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      Authors: Jan Jakub Szczygielski, Leon Brümmer, Hendrik Petrus Wolmarans
      Abstract: This study aims to investigate the impact of the macroeconomic environment on South African industrial sector returns. Using standardized coefficients derived from time-series factor models, the authors quantify the impact of macroeconomic influences on industrial sector returns. The authors analyze the structure of the resultant residual correlation matrices to establish the level of factor omission and apply a factor analytic augmentation to arrive at a specification that is free of omitted common factors. The authors find that global influences are the most important drivers of returns and that industrial sectors are highly integrated with the global economy. The authors show that specifications that comprise only macroeconomic factors and proxies for omitted factors in the form of residual market factors are likely to be underspecified. This study demonstrates that a factor analytic augmentation is an effective approach to ensuring an adequately specified model. The findings have a number of implications that are of interest to investors, econometricians and researchers. While the study focusses on a single market, the South African stock market, as represented by the Johannesburg Stock Exchange (JSE), it is a highly developed and globally integrated market. In terms of market capitalization, it exceeds the Madrid Stock Exchange, the Taiwan Stock Exchange and the BM&F Bovespa. Yet, a limited number of studies investigate the macroeconomic drivers of the South African stock market. Investors should be aware that while the South African domestic environment, especially political risk, has an impact on returns, global influences are the greatest determinants of returns. No industrial sectors are insulated from global influences and this limits the potential for diversification. This study suggests an alternative set of macroeconomic factors that may be used in further analysis and asset pricing studies. From an econometric perspective, this study demonstrates the usefulness of a factor analytic augmentation as a solution to factor omission in models that use macroeconomic factors to proxy for systematic influences that describe asset prices. The contribution lies in providing insight into a large and well-developed yet understudied financial market, the South African stock market. This study considers a much broader set of macroeconomic factors than prior studies. A methodological contribution is made by estimating and interpreting standardized coefficients to discriminate between the impact of domestically and internationally driven factors. This study shows that should coefficients not be standardized, inferences relating to the relative importance of factors will differ. Finally, the authors unify an approach of using pre-specified factors with a factor analytic approach to address factor omission and to ensure a valid and readily interpretable specification.
      Citation: Journal of Risk Finance
      PubDate: 2020-11-30
      DOI: 10.1108/JRF-09-2019-0186
      Issue No: Vol. 21, No. 5 (2020)
       
  • Children’s toy or grown-ups’ gamble' LEGO sets as an
           alternative investment

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      Authors: Savva Shanaev, Nikita Shimkus, Binam Ghimire, Satish Sharma
      Abstract: The purpose of this paper is to study LEGO sets as a potential alternative asset class. An exhaustive sample of 10,588 sets is used to generate inferences regarding long-term LEGO performance, its diversification benefits and return determinants. LEGO set performance is studied in terms of equal- and value-weighted portfolios, sorts based on set characteristics and cross-sectional regressions. Over 1966–2018, LEGO value-weighted index accounted for survivorship bias enjoys 1.20% inflation-adjusted return per annum, well below 5.54% for equities. However, the defensive properties of LEGO are considerable, as including 5%–25% of LEGO in a diversified portfolio is beneficial for investors with varying levels of risk aversion. LEGO secondary market is relatively internationalised, with investors from larger economies, countries with higher per capita incomes and less income inequality are shown to trade LEGO more actively. LEGO investors derive non-pecuniary utility that is separable from their risk-return profile. LEGO is not exposed to any of the Fama-French factors, however, set-specific size and value effects are also well-pronounced on the LEGO market, with smaller sets and sets with lower price-to-piece ratio exhibiting higher yields. Older sets are also enjoying higher returns, demonstrating a liquidity effect. This is the first study to investigate the investment properties of LEGO as an alternative asset class from micro- and macro-financial perspectives that overcomes many survivorship bias limitations prevalent in earlier research. LEGO trading is shown to be an important source of valuable data to enable original robustness checks for prominent theoretical concepts from asset pricing and behavioural finance literature.
      Citation: Journal of Risk Finance
      PubDate: 2020-11-30
      DOI: 10.1108/JRF-02-2020-0021
      Issue No: Vol. 21, No. 5 (2020)
       
  • Forward-looking financial risk management and the housing market in the
           United Kingdom: is there a role for sentiment indicators'

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      Authors: Frederik Kunze, Tobias Basse, Miguel Rodriguez Gonzalez, Günter Vornholz
      Abstract: In the current low-interest market environment, more and more asset managers have started to consider to invest in property markets. To implement adequate and forward-looking risk management procedures, this market should be analyzed in more detail. Therefore, this study aims to examine the housing market data from the UK. More specifically, sentiment data and house prices are examined, using techniques of time-series econometrics suggested by Toda and Yamamoto (1995). The monthly data used in this study is the RICS Housing Market Survey and the Nationwide House Price Index – covering the period from January 2000 to December 2018. Furthermore, the authors also analyze the stability of the implemented Granger causality tests. In sum, the authors found clear empirical evidence for unidirectional Granger causality from sentiment indicator to the house prices index. Consequently, the sentiment indicator can help to forecast property prices in the UK. By investigating sentiment data for house prices using techniques of time-series econometrics (more specifically the procedure suggested by Toda and Yamamoto, 1995), the research question whether sentiment indicators can be helpful to predict property prices in the UK is analyzed empirically. The empirical results show that the RICS Housing Market Survey can help to predict the house prices in the UK. Given these findings, the information provided by property market sentiment indicators certainly should be used in a forward-looking early warning system for house prices in the UK. To authors’ knowledge, this is the first paper that uses the procedure suggested by Toda and Yamaoto to search for suitable early warning indicators for investors in UK real estate assets.
      Citation: Journal of Risk Finance
      PubDate: 2020-09-21
      DOI: 10.1108/JRF-10-2019-0191
      Issue No: Vol. 21, No. 5 (2020)
       
  • Loan fair values and the financial crisis

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      Authors: Niranjan Chipalkatti, Massimo DiPierro, Carl Luft, John Plamondon
      Abstract: In 2009, effective the second-quarter, the financial accounting standards board mandated that all banks need to disclose the fair value of loans in their 10-Q filings in addition to their 10-K filings. This paper aims to investigate whether these disclosures reduced the level of information asymmetry about the riskiness of bank loan portfolios during the financial crisis. The paper examines the impact of these disclosures on the bid-ask spread of a panel of 246 publicly traded bank holding companies. The spread serves as a proxy for information asymmetry and the ratio of the fair value of a bank’s loan portfolio to its book value is a proxy for the credit and liquidity risk associated with the same. The reaction to the first-quarter filing serves as a control to assess the reaction at the time of the second-quarter filing. There is a significant negative association between bid-ask spread and the ratio indicating that the fair value information was useful in reducing information asymmetry during the financial crisis. A pattern was observed in the information dissemination related to the fair value of loans that is consistent with the literature that documents a delayed investor reaction to complex financial information. Investors may use the fair value information to better assess the risk profile of a BHC’s loan portfolio. Also, loan fair values provide managers with data to better implement stress test models and determine optimal capital buffers.
      Citation: Journal of Risk Finance
      PubDate: 2020-08-06
      DOI: 10.1108/JRF-04-2020-0081
      Issue No: Vol. 21, No. 5 (2020)
       
  • Valuation of initial margin using bootstrap method

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      Authors: Modisane Bennett Seitshiro, Hopolang Phillip Mashele
      Abstract: The purpose of this paper is to propose the parametric bootstrap method for valuation of over-the-counter derivative (OTCD) initial margin (IM) in the financial market with low outstanding notional amounts. That is, an aggregate outstanding gross notional amount of OTC derivative instruments not exceeding R20bn. The OTCD market is assumed to have a Gaussian probability distribution with the mean and standard deviation parameters. The bootstrap value at risk model is applied as a risk measure that generates bootstrap initial margins (BIM). The proposed parametric bootstrap method is in favour of the BIM amounts for the simulated and real data sets. These BIM amounts are reasonably exceeding the IM amounts whenever the significance level increases. This paper only assumed that the OTCD returns only come from a normal probability distribution. The OTCD IM requirement in respect to transactions done by counterparties may affect the entire financial market participants under uncleared OTCD, while reducing systemic risk. Thus, reducing spillover effects by ensuring that collateral (IM) is available to offset losses caused by the default of a OTCDs counterparty. This paper contributes to the literature by presenting a valuation of IM for the financial market with low outstanding notional amounts by using the parametric bootstrap method.
      Citation: Journal of Risk Finance
      PubDate: 2020-06-15
      DOI: 10.1108/JRF-10-2019-0203
      Issue No: Vol. 21, No. 5 (2020)
       
  • Blockchain systems for trade clearing

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      Authors: Wei-Tek Tsai, Yong Luo, Enyan Deng, Jing Zhao, Xiaoqiang Ding, Jie Li, Bo Yuan
      Abstract: This paper aims to apply blockchains (BCs) for trade clearing and settlement in a realistic clearinghouse. The purpose is to demonstrate the feasibility and scalability of this approach. The study uses account BCs and trading BCs as building blocks for trade clearing and settlement. Careful design is made to ensure that this approach is feasible and scalable. A design has been proposed that can process hundreds of thousands of trades for a clearinghouse and it addresses performance, privacy and scalability of realistic trade clearing and settlement. The design has been implemented and experimented in a clearinghouse for over two months and processes over 3B real transactions from an exchange. The first month was to experiment with the system with historical data, the second month was to experiment with real-time data during market trading hours. The system performed as designed and intended. This is the first large research paper that applied BCs for clearing in the world. The authors applied the system to a clearinghouse and processed over 3 billion transactions, equivalent to 13 years of London Stock Exchange transaction volume, demonstrating that BCs can handle a large number of transactions. The design can be duplicated to many clearinghouses in the world, and this also paves the way BCs can be used in large financial institutions. An implication is that other trading firms, clearinghouses and banks can apply the same technology for trade clearing, ushering the way BCs can be used in institutions. As clearing is a core function in business transactions, this has significant implications. The design can be discussed and improved in various communities. As this is the first application of BCs to large clearinghouses that uses unique BC designs. This has significant value. Many studies have been performed but few have been reported in the scientific community. The system has been implemented, experimented and demonstrated in public for months.
      Citation: Journal of Risk Finance
      PubDate: 2020-04-06
      DOI: 10.1108/JRF-02-2017-0022
      Issue No: Vol. 21, No. 5 (2020)
       
  • Forecasting multivariate VaR and ES using MC-GARCH-Copula model

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      Authors: Hemant Kumar Badaye, Jason Narsoo
      Abstract: This study aims to use a novel methodology to investigate the performance of several multivariate value at risk (VaR) and expected shortfall (ES) models implemented to assess the risk of an equally weighted portfolio consisting of high-frequency (1-min) observations for five foreign currencies, namely, EUR/USD, GBP/USD, EUR/JPY, USD/JPY and GBP/JPY. By applying the multiplicative component generalised autoregressive conditional heteroskedasticity (MC-GARCH) model on each return series and by modelling the dependence structure using copulas, the 95 per cent intraday portfolio VaR and ES are forecasted for an out-of-sample set using Monte Carlo simulation. In terms of VaR forecasting performance, the backtesting results indicated that four out of the five models implemented could not be rejected at 5 per cent level of significance. However, when the models were further evaluated for their ES forecasting power, only the Student’s t and Clayton models could not be rejected. The fact that some ES models were rejected at 5 per cent significance level highlights the importance of selecting an appropriate copula model for the dependence structure. To the best of the authors’ knowledge, this is the first study to use the MC-GARCH and copula models to forecast, for the next 1 min, the VaR and ES of an equally weighted portfolio of foreign currencies. It is also the first study to analyse the performance of the MC-GARCH model under seven distributional assumptions for the innovation term.
      Citation: Journal of Risk Finance
      PubDate: 2020-01-27
      DOI: 10.1108/JRF-06-2019-0114
      Issue No: Vol. 21, No. 5 (2020)
       
  • Journal of Risk Finance

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