Pub Date : 2020-07-17DOI: 10.1108/jrf-09-2019-0183
Pablo Durán Santomil, L. O. González
The purpose of this paper is to analyze how enterprise risk management (ERM), the system of governance and the Own Risk and Solvency Assessment (ORSA) have been boosted with the entry of Solvency II.,For this analysis, the authors have undertaken a survey of chief risk officers (CROs) working in Spanish insurance companies.,The results show that Solvency II has definitely promoted ERM in the European insurance industry and improved the system of governance of the insurance companies, and that the perceived value of the ORSA for the companies is higher than the cost. It is clear that the quality of ERM implemented by companies is higher in those that face more complex risks and with greater interdependencies – that is, larger companies, foreign insurers and insurers with several lines of business – but is unaffected by the legal form of the entity (mutual/corporation).,This study conducts primary research with surveys of CROs and develops a measure of the quality of ERM implemented by insurance companies.
{"title":"Enterprise risk management and Solvency II: the system of governance and the Own Risk and Solvency Assessment","authors":"Pablo Durán Santomil, L. O. González","doi":"10.1108/jrf-09-2019-0183","DOIUrl":"https://doi.org/10.1108/jrf-09-2019-0183","url":null,"abstract":"The purpose of this paper is to analyze how enterprise risk management (ERM), the system of governance and the Own Risk and Solvency Assessment (ORSA) have been boosted with the entry of Solvency II.,For this analysis, the authors have undertaken a survey of chief risk officers (CROs) working in Spanish insurance companies.,The results show that Solvency II has definitely promoted ERM in the European insurance industry and improved the system of governance of the insurance companies, and that the perceived value of the ORSA for the companies is higher than the cost. It is clear that the quality of ERM implemented by companies is higher in those that face more complex risks and with greater interdependencies – that is, larger companies, foreign insurers and insurers with several lines of business – but is unaffected by the legal form of the entity (mutual/corporation).,This study conducts primary research with surveys of CROs and develops a measure of the quality of ERM implemented by insurance companies.","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"21 1","pages":"317-332"},"PeriodicalIF":3.0,"publicationDate":"2020-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-09-2019-0183","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49602302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-06DOI: 10.1108/jrf-07-2019-0135
Lukasz Prorokowski, O. Deev, Hubert Prorokowski
Purpose - The use of risk proxies in internal models remains a popular modelling solution. However, there is some risk that a proxy may not constitute an adequate representation of the underlying asset in terms of capturing tail risk. Therefore, using empirical examples for the financial collateral haircut model, this paper aims to critically review available statistical tools for measuring the adequacy of capturing tail risk by proxies used in the internal risk models of banks. In doing so, this paper advises on the most appropriate solutions for validating risk proxies. Design/methodology/approach - This paper reviews statistical tools used to validate if the equity index/fund benchmark are proxies that adequately represent tail risk in the returns on an individual asset (equity/fund). The following statistical tools for comparing return distributions of the proxies and the portfolio items are discussed: the two-sample Kolmogorov–Smirnov test, the spillover test and the Harrell’s C test. Findings - Upon the empirical review of the available statistical tools, this paper suggests using the two-sample Kolmogorov–Smirnov test to validate the adequacy of capturing tail risk by the assigned proxy and the Harrell’s C test to capture the discriminatory power of the proxy-based collateral haircuts models. This paper also suggests a tool that compares the reactions of risk proxies to tail events to verify possible underestimation of risk in times of significant stress. Originality/value - The current regulations require banks to prove that the modelled proxies are representative of the real price observations without underestimation of tail risk and asset price volatility. This paper shows how to validate proxy-based financial collateral haircuts models.
{"title":"Testing risk proxies for financial collateral haircuts: adequacy of capturing tail risk","authors":"Lukasz Prorokowski, O. Deev, Hubert Prorokowski","doi":"10.1108/jrf-07-2019-0135","DOIUrl":"https://doi.org/10.1108/jrf-07-2019-0135","url":null,"abstract":"Purpose - The use of risk proxies in internal models remains a popular modelling solution. However, there is some risk that a proxy may not constitute an adequate representation of the underlying asset in terms of capturing tail risk. Therefore, using empirical examples for the financial collateral haircut model, this paper aims to critically review available statistical tools for measuring the adequacy of capturing tail risk by proxies used in the internal risk models of banks. In doing so, this paper advises on the most appropriate solutions for validating risk proxies. Design/methodology/approach - This paper reviews statistical tools used to validate if the equity index/fund benchmark are proxies that adequately represent tail risk in the returns on an individual asset (equity/fund). The following statistical tools for comparing return distributions of the proxies and the portfolio items are discussed: the two-sample Kolmogorov–Smirnov test, the spillover test and the Harrell’s C test. Findings - Upon the empirical review of the available statistical tools, this paper suggests using the two-sample Kolmogorov–Smirnov test to validate the adequacy of capturing tail risk by the assigned proxy and the Harrell’s C test to capture the discriminatory power of the proxy-based collateral haircuts models. This paper also suggests a tool that compares the reactions of risk proxies to tail events to verify possible underestimation of risk in times of significant stress. Originality/value - The current regulations require banks to prove that the modelled proxies are representative of the real price observations without underestimation of tail risk and asset price volatility. This paper shows how to validate proxy-based financial collateral haircuts models.","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"21 1","pages":"299-316"},"PeriodicalIF":3.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-07-2019-0135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46599918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-06DOI: 10.1108/jrf-03-2020-0053
Robyn Owen, Marcus O’Dair
Purpose This paper aims to examine how blockchain technology is disrupting business models for new venture finance. Design/methodology/approach The role of blockchain technology in the evolution of new business models to monetize the creative economy is explored by means of a case study approach. The focus is on the recorded music industry, which is in the vanguard of new forms of intermediation and financialization. There is a particular focus on emerging artists. Findings This paper provides novel case study insights and concludes by considering how further research can contribute to building a theory of technology-driven business models which apply to the development, on the one hand, of new forms of financial intermediaries, more correctly referred to as “infomediaries,” and on the other hand, to new forms of direct monetization by artists. Originality/value This paper provides early insight into the emerging potential applications of blockchain technologies to streamline music industry business service models and improve finance streams for new artists. The findings have far-reaching implications across the creative sector.
{"title":"How blockchain technology can monetize new music ventures: an examination of new business models","authors":"Robyn Owen, Marcus O’Dair","doi":"10.1108/jrf-03-2020-0053","DOIUrl":"https://doi.org/10.1108/jrf-03-2020-0053","url":null,"abstract":"\u0000Purpose\u0000This paper aims to examine how blockchain technology is disrupting business models for new venture finance.\u0000\u0000\u0000Design/methodology/approach\u0000The role of blockchain technology in the evolution of new business models to monetize the creative economy is explored by means of a case study approach. The focus is on the recorded music industry, which is in the vanguard of new forms of intermediation and financialization. There is a particular focus on emerging artists.\u0000\u0000\u0000Findings\u0000This paper provides novel case study insights and concludes by considering how further research can contribute to building a theory of technology-driven business models which apply to the development, on the one hand, of new forms of financial intermediaries, more correctly referred to as “infomediaries,” and on the other hand, to new forms of direct monetization by artists.\u0000\u0000\u0000Originality/value\u0000This paper provides early insight into the emerging potential applications of blockchain technologies to streamline music industry business service models and improve finance streams for new artists. The findings have far-reaching implications across the creative sector.\u0000","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"1 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-03-2020-0053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46637984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-30DOI: 10.1108/jrf-11-2019-0222
Florian Klein, Hato Schmeiser
The purpose of this paper is to determine optimal pooling strategies from the perspective of an insurer's shareholders underlying a default probability driven premium loading and convex price-demand functions.,The authors use an option pricing framework for normally distributed claims to analyze the net present value for different pooling strategies and contrast multiple risk pools structured as a single legal entity with the case of multiple legal entities. To achieve the net present value maximizing default probability, the insurer adjusts the underlying equity capital.,The authors show with the theoretical considerations and numerical examples that multiple risk pools with multiple legal entities are optimal if the equity capital must be decreased. An equity capital increase implies that multiple risk pools in a single legal entity are generally optimal. Moreover, a single risk pool for multiple risk classes improves in relation to multiple risk pools with multiple legal entities whenever the standard deviation of the underlying claims increases.,The authors extend previous research on risk pooling by introducing a default probability driven premium loading and a relation between the premium level and demand through a convex price-demand function.
{"title":"Optimal pooling strategies under heterogeneous risk classes","authors":"Florian Klein, Hato Schmeiser","doi":"10.1108/jrf-11-2019-0222","DOIUrl":"https://doi.org/10.1108/jrf-11-2019-0222","url":null,"abstract":"The purpose of this paper is to determine optimal pooling strategies from the perspective of an insurer's shareholders underlying a default probability driven premium loading and convex price-demand functions.,The authors use an option pricing framework for normally distributed claims to analyze the net present value for different pooling strategies and contrast multiple risk pools structured as a single legal entity with the case of multiple legal entities. To achieve the net present value maximizing default probability, the insurer adjusts the underlying equity capital.,The authors show with the theoretical considerations and numerical examples that multiple risk pools with multiple legal entities are optimal if the equity capital must be decreased. An equity capital increase implies that multiple risk pools in a single legal entity are generally optimal. Moreover, a single risk pool for multiple risk classes improves in relation to multiple risk pools with multiple legal entities whenever the standard deviation of the underlying claims increases.,The authors extend previous research on risk pooling by introducing a default probability driven premium loading and a relation between the premium level and demand through a convex price-demand function.","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"21 1","pages":"271-298"},"PeriodicalIF":3.0,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-11-2019-0222","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41319120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-29DOI: 10.1108/jrf-01-2020-0012
M. Coppola, M. Russolillo, R. Simone
Purpose - This paper aims to measure the financial impact on social security system of a recently proposed indexation mechanism for retirement age by considering the Italian longevity experience. The analysis is motivated by the progressive increase in life expectancy at advanced age, which is rapidly bringing to the fore noticeable socio-economic consequences in most industrialized countries. Among those, the impact on National Social Security systems is particularly relevant if people live longer than expected; this will lead to greater financial exposure for pension providers. Design/methodology/approach - Referring to the Italian population for illustrative purposes, the authors contemplate different scenarios for mortality projection methods and for the implementation of pension age shift while accounting for gender and cohort gaps and model risk. Synthetic indicators to measure the impact of the indexation mechanism on social security system are introduced on the basis of pension cash flows. Findings - An indexation policy that manages gender gap while adjusting retirement age for varying life expectancy is proposed. As a result, sustainability of public retirement expenditure is improved. Originality/value - The paper is a concise scenario analysis of the reduction of costs and risks that pension providers would have if the system resorted to link retirement age to life expectancy. The ideas fostered by the paper follow a recent proposal of the Authors on a flexible retirement scheme that deals with model risk for mortality projection and accounts for gender gap in mortality rates.
{"title":"On the management of retirement age indexed to life expectancy: a scenario analysis of the Italian longevity experience","authors":"M. Coppola, M. Russolillo, R. Simone","doi":"10.1108/jrf-01-2020-0012","DOIUrl":"https://doi.org/10.1108/jrf-01-2020-0012","url":null,"abstract":"Purpose - This paper aims to measure the financial impact on social security system of a recently proposed indexation mechanism for retirement age by considering the Italian longevity experience. The analysis is motivated by the progressive increase in life expectancy at advanced age, which is rapidly bringing to the fore noticeable socio-economic consequences in most industrialized countries. Among those, the impact on National Social Security systems is particularly relevant if people live longer than expected; this will lead to greater financial exposure for pension providers. Design/methodology/approach - Referring to the Italian population for illustrative purposes, the authors contemplate different scenarios for mortality projection methods and for the implementation of pension age shift while accounting for gender and cohort gaps and model risk. Synthetic indicators to measure the impact of the indexation mechanism on social security system are introduced on the basis of pension cash flows. Findings - An indexation policy that manages gender gap while adjusting retirement age for varying life expectancy is proposed. As a result, sustainability of public retirement expenditure is improved. Originality/value - The paper is a concise scenario analysis of the reduction of costs and risks that pension providers would have if the system resorted to link retirement age to life expectancy. The ideas fostered by the paper follow a recent proposal of the Authors on a flexible retirement scheme that deals with model risk for mortality projection and accounts for gender gap in mortality rates.","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"21 1","pages":"217-231"},"PeriodicalIF":3.0,"publicationDate":"2020-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-01-2020-0012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49388883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-27DOI: 10.1108/jrf-05-2019-0085
Canicio Dzingirai, Nixon S. Chekenya
The life insurance industry has been exposed to high levels of longevity risk born from the mismatch between realized mortality trends and anticipated forecast. Annuity providers are exposed to extended periods of annuity payments. There are no immediate instruments in the market to counter the risk directly. This paper aims to develop appropriate instruments for hedging longevity risk and providing an insight on how existing products can be tailor-made to effectively immunize portfolios consisting of life insurance using a cointegration vector error correction model with regime-switching (RS-VECM), which enables both short-term fluctuations, through the autoregressive structure [AR(1)] and long-run equilibria using a cointegration relationship. The authors also develop synthetic products that can be used to effectively hedge longevity risk faced by life insurance and annuity providers who actively hold portfolios of life insurance products. Models are derived using South African data. The authors also derive closed-form expressions for hedge ratios associated with synthetic products written on life insurance contracts as this will provide a natural way of immunizing the associated portfolios. The authors further show how to address the current liquidity challenges in the longevity market by devising longevity swaps and develop pricing and hedging algorithms for longevity-linked securities. The use of a cointergrating relationship improves the model fitting process, as all the VECMs and RS-VECMs yield greater criteria values than their vector autoregressive model (VAR) and regime-switching vector autoregressive model (RS-VAR) counterpart’s, even though there are accruing parameters involved.,The market model adopted from Ngai and Sherris (2011) is a cointegration RS-VECM for this enables both short-term fluctuations, through the AR(1) and long-run equilibria using a cointegration relationship (Johansen, 1988, 1995a, 1995b), with a heteroskedasticity through the use of regime-switching. The RS-VECM is seen to have the best fit for Australian data under various model selection criteria by Sherris and Zhang (2009). Harris (1997) (Sajjad et al., 2008) also fits a regime-switching VAR model using Australian (UK and US) data to four key macroeconomic variables (market stock indices), showing that regime-switching is a significant improvement over autoregressive conditional heteroscedasticity (ARCH) and generalised autoregressive conditional heteroscedasticity (GARCH) processes in the account for volatility, evidence similar to that of Sherris and Zhang (2009) in the case of Exponential Regressive Conditional Heteroscedasticity (ERCH). Ngai and Sherris (2011) and Sherris and Zhang (2009) also fit a VAR model to Australian data with simultaneous regime-switching across many economic and financial series.,The authors develop a longevity swap using nighttime data instead of usual income measures as it yields statistically accurate results. The authors also
{"title":"Longevity swaps for longevity risk management in life insurance products","authors":"Canicio Dzingirai, Nixon S. Chekenya","doi":"10.1108/jrf-05-2019-0085","DOIUrl":"https://doi.org/10.1108/jrf-05-2019-0085","url":null,"abstract":"The life insurance industry has been exposed to high levels of longevity risk born from the mismatch between realized mortality trends and anticipated forecast. Annuity providers are exposed to extended periods of annuity payments. There are no immediate instruments in the market to counter the risk directly. This paper aims to develop appropriate instruments for hedging longevity risk and providing an insight on how existing products can be tailor-made to effectively immunize portfolios consisting of life insurance using a cointegration vector error correction model with regime-switching (RS-VECM), which enables both short-term fluctuations, through the autoregressive structure [AR(1)] and long-run equilibria using a cointegration relationship. The authors also develop synthetic products that can be used to effectively hedge longevity risk faced by life insurance and annuity providers who actively hold portfolios of life insurance products. Models are derived using South African data. The authors also derive closed-form expressions for hedge ratios associated with synthetic products written on life insurance contracts as this will provide a natural way of immunizing the associated portfolios. The authors further show how to address the current liquidity challenges in the longevity market by devising longevity swaps and develop pricing and hedging algorithms for longevity-linked securities. The use of a cointergrating relationship improves the model fitting process, as all the VECMs and RS-VECMs yield greater criteria values than their vector autoregressive model (VAR) and regime-switching vector autoregressive model (RS-VAR) counterpart’s, even though there are accruing parameters involved.,The market model adopted from Ngai and Sherris (2011) is a cointegration RS-VECM for this enables both short-term fluctuations, through the AR(1) and long-run equilibria using a cointegration relationship (Johansen, 1988, 1995a, 1995b), with a heteroskedasticity through the use of regime-switching. The RS-VECM is seen to have the best fit for Australian data under various model selection criteria by Sherris and Zhang (2009). Harris (1997) (Sajjad et al., 2008) also fits a regime-switching VAR model using Australian (UK and US) data to four key macroeconomic variables (market stock indices), showing that regime-switching is a significant improvement over autoregressive conditional heteroscedasticity (ARCH) and generalised autoregressive conditional heteroscedasticity (GARCH) processes in the account for volatility, evidence similar to that of Sherris and Zhang (2009) in the case of Exponential Regressive Conditional Heteroscedasticity (ERCH). Ngai and Sherris (2011) and Sherris and Zhang (2009) also fit a VAR model to Australian data with simultaneous regime-switching across many economic and financial series.,The authors develop a longevity swap using nighttime data instead of usual income measures as it yields statistically accurate results. The authors also","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"21 1","pages":"253-269"},"PeriodicalIF":3.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-05-2019-0085","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47760610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-20DOI: 10.1108/jrf-07-2019-0130
Xiaoying Chen, Ni Gao
Purpose Since the introduction of VIX to measure the spot volatility in the stock market, VIX and its futures have been widely considered to be the standard of underlying investor sentiment. This study aims to examine how the magnitude of contango or backwardation (MCB volatility risk factor) derived from VIX and VIX3M may affect the pricing of assets. Design/methodology/approach This paper focuses on the statistical inference of three defined MCB risk factors when cross-examined with Fama–French’s five factors: the market factor Rm–Rf, the size factor SMB (small minus big), the value factor HML (high minus low B/M), the profitability factor RMW (robust minus weak) and the investing factor CMA (conservative minus aggressive). Robustness checks are performed with the revised HML-Dev factor, as well as with daily data sets. Findings The inclusions of the MCB volatility risk factor, either defined as a spread of monthly VIX3M/VIX and its monthly MA(20), or as a monthly net return of VIX3M/VIX, generally enhance the explanatory power of all factors in the Fama and French’s model, in particular the market factor Rm–Rf and the value factor HML, and the investing factor CMA also displays a significant and positive correlation with the MCB risk factor. When the more in-time adjusted HML-Dev factor, suggested by Asness (2014), replaces the original HML factor, results are generally better and more intuitive, with a higher R2 for the market factor and more explanatory power with HML-Dev. Originality/value This paper introduces the term structure of VIX to Fama–French’s asset pricing model. The MCB risk factor identifies underlying configurations of investor sentiment. The sensitivities to this timing indicator will significantly relate to returns across individual stocks or portfolios.
{"title":"Revisiting Fama–French’s asset pricing model with an MCB volatility risk factor","authors":"Xiaoying Chen, Ni Gao","doi":"10.1108/jrf-07-2019-0130","DOIUrl":"https://doi.org/10.1108/jrf-07-2019-0130","url":null,"abstract":"\u0000Purpose\u0000Since the introduction of VIX to measure the spot volatility in the stock market, VIX and its futures have been widely considered to be the standard of underlying investor sentiment. This study aims to examine how the magnitude of contango or backwardation (MCB volatility risk factor) derived from VIX and VIX3M may affect the pricing of assets.\u0000\u0000\u0000Design/methodology/approach\u0000This paper focuses on the statistical inference of three defined MCB risk factors when cross-examined with Fama–French’s five factors: the market factor Rm–Rf, the size factor SMB (small minus big), the value factor HML (high minus low B/M), the profitability factor RMW (robust minus weak) and the investing factor CMA (conservative minus aggressive). Robustness checks are performed with the revised HML-Dev factor, as well as with daily data sets.\u0000\u0000\u0000Findings\u0000The inclusions of the MCB volatility risk factor, either defined as a spread of monthly VIX3M/VIX and its monthly MA(20), or as a monthly net return of VIX3M/VIX, generally enhance the explanatory power of all factors in the Fama and French’s model, in particular the market factor Rm–Rf and the value factor HML, and the investing factor CMA also displays a significant and positive correlation with the MCB risk factor. When the more in-time adjusted HML-Dev factor, suggested by Asness (2014), replaces the original HML factor, results are generally better and more intuitive, with a higher R2 for the market factor and more explanatory power with HML-Dev.\u0000\u0000\u0000Originality/value\u0000This paper introduces the term structure of VIX to Fama–French’s asset pricing model. The MCB risk factor identifies underlying configurations of investor sentiment. The sensitivities to this timing indicator will significantly relate to returns across individual stocks or portfolios.\u0000","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2020-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-07-2019-0130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46697062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-15DOI: 10.1108/jrf-10-2019-0203
M. Seitshiro, H. P. Mashele
Purpose 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. Design/methodology/approach 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). Findings 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. Research limitations/implications This paper only assumed that the OTCD returns only come from a normal probability distribution. Practical implications 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. Originality/value 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.
本文的目的是提出在低未偿名义金额的金融市场上场外衍生品(OTCD)初始保证金(IM)估值的参数bootstrap方法。即不超过200亿兰特的场外衍生工具未偿还名义总额。设计/方法/方法假设OTCD市场具有具有均值和标准差参数的高斯概率分布。bootstrap value at risk模型被用作产生bootstrap initial margin (BIM)的风险度量。研究结果提出的参数引导方法有利于模拟和真实数据集的BIM数量。当显著性水平增加时，这些BIM数量会合理地超过IM数量。研究局限/启示本文仅假设OTCD收益仅为正态概率分布。实际影响场外交易合约对交易对手所作交易的即时交易规定，在降低系统风险的同时，可能会影响未结算场外交易合约下的整个金融市场参与者。因此，通过确保抵押品(IM)可用于抵消OTCDs交易对手违约造成的损失来减少溢出效应。原创性/价值本文通过使用参数bootstrap方法对具有低未偿名义金额的金融市场的IM进行估值，从而为文献做出了贡献。
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Pub Date : 2020-05-28DOI: 10.1108/jrf-08-2019-0146
Saibal Ghosh
While several facets of financial misconduct have been explored, one aspect which has largely bypassed the attention of researchers is the factors affecting such misconduct behavior in banks. To investigate this in detail, this paper aims to use disaggregated data on Indian banks for an extended period to understand the factors driving such behavior.,Given the longitudinal nature of the data, the author uses fixed effects regression methodology which enables us to control for unobserved characteristics that might affect the dependent variable.,The analysis indicates that both bank- and board-specific factors are important in driving financial misconduct, although their importance differs across ownership. In particular, while size and capital are relevant for public banks, liquidity is more of a concern for private banks as compared with their public counterparts. In addition, the relevance of bank boards is important only in case of private banks. These results hold after controlling for the structure of the banking industry and the macroeconomic environment.,To the best of the author’s knowledge, this is one of the earliest studies for India to carefully examine the interface between financial misconduct and bank behavior in a systematic manner.
{"title":"Financial misconduct in Indian banks: what matters and what doesn’t?","authors":"Saibal Ghosh","doi":"10.1108/jrf-08-2019-0146","DOIUrl":"https://doi.org/10.1108/jrf-08-2019-0146","url":null,"abstract":"While several facets of financial misconduct have been explored, one aspect which has largely bypassed the attention of researchers is the factors affecting such misconduct behavior in banks. To investigate this in detail, this paper aims to use disaggregated data on Indian banks for an extended period to understand the factors driving such behavior.,Given the longitudinal nature of the data, the author uses fixed effects regression methodology which enables us to control for unobserved characteristics that might affect the dependent variable.,The analysis indicates that both bank- and board-specific factors are important in driving financial misconduct, although their importance differs across ownership. In particular, while size and capital are relevant for public banks, liquidity is more of a concern for private banks as compared with their public counterparts. In addition, the relevance of bank boards is important only in case of private banks. These results hold after controlling for the structure of the banking industry and the macroeconomic environment.,To the best of the author’s knowledge, this is one of the earliest studies for India to carefully examine the interface between financial misconduct and bank behavior in a systematic manner.","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"21 1","pages":"57-76"},"PeriodicalIF":3.0,"publicationDate":"2020-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-08-2019-0146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62161509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-13DOI: 10.1108/jrf-11-2019-0221
Benjamin Schellinger
This paper aims to elaborate on the optimization of two particular cryptocurrency portfolios in a mean-variance framework. In general, cryptocurrencies can be classified to as coins and tokens where the first can be thought of as a medium of exchange and the latter accounts for security or utility tokens depending upon its design.,Against this backdrop, this empirical study distinguishes, in particular, between pure coin and token portfolios. Both portfolios are optimized by maximizing the Sharpe ratio and, subsequently, compared with alternative portfolio strategies.,The empirical findings demonstrate that the maximum utility portfolio of coins, with a risk aversion of λ = 10, outweighs alternative frameworks. The portfolios optimized by maximizing the Sharpe ratio for both coins and tokens indicate a rather poor performance. Testing the maximized utility for different levels of risk aversion confirms the findings of this empirical study and confers them more robustness.,Further investigation is strongly recommended as tokens represent a new phenomenon in the cryptocurrency universe, for which only a limited amount of data are available, which restricts the sampling. Furthermore, future study is to include more sophisticated optimization models using different constraints in portfolio creation.,In light of the persistently substantial volatility in cryptocurrency markets, the empirical findings assert that portfolio managers are advised to construct a global minimum variance portfolio. In the absence of sophisticated optimization models, private investors can invest according to the market values of cryptocurrencies. Despite minor differences in the risk and reward ratios of the portfolios tested, tokens tend to be more speculative, especially, if the Tether token is excluded, which may require enhanced supervision and investor protection by regulating authorities.,As the current literature investigates on diversification effects of blended cryptocurrency portfolios rather than making an explicit distinction, this paper reflects one of the first to explore the investability and role of diversifying coins and tokens using a classic Markowitz approach.
{"title":"Optimization of special cryptocurrency portfolios","authors":"Benjamin Schellinger","doi":"10.1108/jrf-11-2019-0221","DOIUrl":"https://doi.org/10.1108/jrf-11-2019-0221","url":null,"abstract":"This paper aims to elaborate on the optimization of two particular cryptocurrency portfolios in a mean-variance framework. In general, cryptocurrencies can be classified to as coins and tokens where the first can be thought of as a medium of exchange and the latter accounts for security or utility tokens depending upon its design.,Against this backdrop, this empirical study distinguishes, in particular, between pure coin and token portfolios. Both portfolios are optimized by maximizing the Sharpe ratio and, subsequently, compared with alternative portfolio strategies.,The empirical findings demonstrate that the maximum utility portfolio of coins, with a risk aversion of λ = 10, outweighs alternative frameworks. The portfolios optimized by maximizing the Sharpe ratio for both coins and tokens indicate a rather poor performance. Testing the maximized utility for different levels of risk aversion confirms the findings of this empirical study and confers them more robustness.,Further investigation is strongly recommended as tokens represent a new phenomenon in the cryptocurrency universe, for which only a limited amount of data are available, which restricts the sampling. Furthermore, future study is to include more sophisticated optimization models using different constraints in portfolio creation.,In light of the persistently substantial volatility in cryptocurrency markets, the empirical findings assert that portfolio managers are advised to construct a global minimum variance portfolio. In the absence of sophisticated optimization models, private investors can invest according to the market values of cryptocurrencies. Despite minor differences in the risk and reward ratios of the portfolios tested, tokens tend to be more speculative, especially, if the Tether token is excluded, which may require enhanced supervision and investor protection by regulating authorities.,As the current literature investigates on diversification effects of blended cryptocurrency portfolios rather than making an explicit distinction, this paper reflects one of the first to explore the investability and role of diversifying coins and tokens using a classic Markowitz approach.","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"21 1","pages":"127-157"},"PeriodicalIF":3.0,"publicationDate":"2020-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/jrf-11-2019-0221","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45173961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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