The Journal of Risk Finance

Ghosh, Saibal

2020 The Journal of Risk Finance

doi: 10.1108/jrf-08-2019-0146

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.Design/methodology/approachGiven 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.FindingsThe 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.Originality/valueTo 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.

Eling, Martin; Kraft, Mirko

2020 The Journal of Risk Finance

doi: 10.1108/jrf-07-2019-0129

The purpose of this paper is to analyze the use of telematics in insurance and its consequences for the insurability of risks. Empirical results on monitoring policyholders or insured objects and its consequences for asymmetric information, as well as claims frequency and severity are discussed. Furthermore, potential future research questions that arise from the use of telematics in risk management and insurance are outlined.Design/methodology/approachThe paper systematically reviews existing studies and then investigates the consequences of telematics using Berliner’s insurability criteria. The results are based on 52 academic studies and industry papers published from 2000 to 2019.FindingsThe findings emphasize the effects of new information on information asymmetry and risk pooling, the implications of new technologies on loss frequency and severity, legal restrictions and ethical consequences of the use of telematics in the insurance field. Problems with the insurability impede the market development of innovations such as telematics tariffs.Originality/valueDespite its increasing relevance for businesses at present, research on telematics in insurance is limited. Some papers can be found in the IT domain, but relatively little research has been done in the business and economics literature. The authors illustrate where the research stands currently and outline directions for future research.

Kokoris, Athanasios; Archontakis, Fragiskos; Grose, Christos

2020 The Journal of Risk Finance

doi: 10.1108/jrf-05-2019-0078

This study aims to examine whether the methodology proposed by the European Supervisory Authorities (ESAs) within Delegated Regulation (European Union) 2017/653 for the calculation of market risk of certain packaged retail and insurance-based investment products (PRIIPs) is the most appropriate.Design/methodology/approachRisk models are put into effect to validate the appropriateness of the methodology announced by ESAs. ESAs have announced that the unit-linked (UL) products, labeled as Category II PRIIPs, will be subject to the Cornish–Fisher value-at-risk (CFVaR) methodology for their market risk assessment. We test CFVaR at 97.5% confidence level on 70 UL products, and we test Cornish–Fisher expected shortfall (CFES) at the same confidence level, which acts as a counter methodology for CFVaR.FindingsThe paper provides empirical insights about the Cornish-Fisher (CF) expansion being a method that incorporates the possibility of financial instability. When CFVaR by ESAs is calculated, it is shown that CF is in general a more robust risk model than the simpler historical ones. However, when CFES is applied, important points are derived. First, only in half of the occasions the CF expansion can be considered as a reliable method. Second, the CFES is a more coherent risk measure than CFVaR. We conclude that the CF expansion is unable to accurately estimate the market risk of UL products when excessive fat-tailed or non-symmetrical distributions are present. Hence, we suggest that a different methodology could also be considered by the regulatory bodies which will capture the excessive values of products in financial distress.Originality/valueLiterature, both theoretical and applied, regarding PRIIPs, is not extended. Although business and regulators research has begun to intensify in the last two years, to our knowledge this is one of the first studies that uses the CFES methodology for market risk assessment of Category II PRIIPs. In addition, we use a unique data set from a country in the headwinds of the recent financial crisis. This research contributes both to the academic and business community by enriching the existing literature and aiding risk managers in assessing the market risk of certain Category II PRIIPs. Considering the recent efforts of the regulatory authorities at the beginning of 2020 to implement certain amendments to the PRIIPs, we indicate relative risks related with the calculation of the market risk of the aforementioned products. Our findings could contribute to regulatory authorities’ persistent efforts in wrapping up this ongoing project.

Schellinger, Benjamin

2020 The Journal of Risk Finance

doi: 10.1108/jrf-11-2019-0221

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.Design/methodology/approachAgainst 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.FindingsThe 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.Research limitations/implicationsFurther 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.Practical implicationsIn 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.Originality/valueAs 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.

Molele, Mashukudu Hartley; Mukuddem-Petersen, Janine

2020 The Journal of Risk Finance

doi: 10.1108/jrf-07-2019-0123

The purpose of this paper is to examine the level of foreign exchange exposure of listed nonfinancial firms in South Africa. The study spans the period January 2002 and November 2015. Foreign exchange risk exposure is estimated in relation to the exchange rate of the South African Rand relative to the US$, the Euro, the British Pound and the trade-weighted exchange rate index.Design/methodology/approachThe study is based on the augmented-market model of Jorion (1990). The Jorion (1990) is a capital asset pricing model-inspired framework which models share returns as a function of the return on the market index and changes in the exchange rate factor. The market risk factor is meant to discount the effect of macroeconomic factors on share returns, thus isolating the foreign exchange risk factor. In addition, the study further added the size, value, momentum, investment and profitability risk factors in line with the Fama–French three-factor model, Carhart four-factor model and the Fama–French five-factor model to account for the fact that equity capital markets in countries such as South Africa are known to be partially segmented.FindingsForeign exchange risk exposure levels were estimated at more than 40% for all the proxy currencies on the basis of the standard augmented market model. However, after controlling for idiosyncratic factors, through the application of the Fama–French three-factor model, the Carhart four-factor model and the Fama–French five-factor model, exposure levels were found to range between 6.5 and 12%.Research limitations/implicationsThese results indicate the importance of controlling for the effects of idiosyncratic facto0rs in the estimation of foreign exchange risk exposure in the context of emerging markets of Sub-Saharan Africa (SSA).Originality/valueThis is the first study to apply the Fama–French three-factor model, Carhart four-factor model and the Fama–French five-factor model in the estimation of foreign exchange exposure of nonfinancial firms in the context of a SSA country. These results indicate the importance of controlling for the effects of idiosyncratic factors in the estimation of foreign exchange risk exposure in the context of emerging markets.

Tusiime, Ivan Mugarura; Wang, Man

2020 The Journal of Risk Finance

doi: 10.1108/jrf-05-2019-0076

The purpose of this paper is to examine whether oil price risk is a significant determinant of stock returns.Design/methodology/approachUsing monthly data on a sample of Islamic stocks listed on the New York Stock Exchanges and National Association of Securities Dealers Automated Quotations System (NASDAQ) over the period from January 1990 to December 2017, the study examines whether oil price risk is a significant determinant of stock returns using Fama–French–Carhart’s four-factor asset pricing model amplified with Brent oil price factor.FindingsThe results from the cross-sectional regression analysis indicate that the extent of the exposure is significantly positive using a full sample period. Moreover, results from size and momentum factors are highly significant whereas book-to-market has no significant impact on Islamic stock returns.Research limitations/implicationsThe results support the concept for diversification in equity investment and are thus important for investors, analysts and policymakers.Originality/valueThis study is the first of its kind to establish whether oil price risk is a factor that can determine returns of Islamic listed stocks using the most developed stock market in the world (New York Stock Exchanges and NASDAQ).