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The purpose of this study is to estimate the convergence order of the Aumann–Serrano Riskiness Index.

This study uses the equivalent relation between the Aumann–Serrano Riskiness Index and the moment generating function and aggregately compares between each two statistical moments for statistical significance. Thus, this study enables to find the convergence order of the index to its stable value.

This study finds that the first-best estimation of the Aumann–Serrano Riskiness Index is reached in no less than its seventh statistical moment. However, this study also finds that its second-best approximation could be achieved with its second statistical moment.

The implications of this research support the standard deviation as a statistically sufficient approximation of Aumann–Serrano Riskiness Index, thus strengthening the CAPM methodology for asset pricing in the financial markets.

This research sheds a new light, both in theory and in practice, on understanding of the risk’s structure, as it may improve accuracy of asset pricing.

The purpose of this paper is to establish a grey cloud incidence clustering model to assess the drought disaster degree under 15 indexes in 18 cities of Henan province.

The grey incidence degree between each index and ideal index is used to determine the index weight and combined with the subjective weight, the comprehensive weight is given; the traditional possibility function is transformed into grey cloud possibility function by using the principle of maximum deviation and maximum entropy, which fully reflects the coexistence of multiple decision-making conclusions and constructs the grey cloud incidence clustering model.

The drought disaster degree of Henan province is divided into four grades under the selected 15 indexes. The drought grades show obvious regional differences. The risk levels of the east and southwest are higher, and the risk levels of the north and southeast are lower. This result is consistent with the study of drought disaster grades in Henan province, which shows the practicability and usefulness of the model.

It provides an effective method for the assessment of drought disaster grade and the basis for formulating disaster prevention and mitigation plan.

By studying the method of multiattribute and multistage decision-making with interval grey number information. The objective weight model of index value is designed, and the subjective weight is given by experts. On the basis of the two, the comprehensive weight of subjective and objective combination is proposed, which effectively weakens the randomness of subjective weight and reasonably reflects the practicality of index decision-making. The time weight reflects the dynamic of the index. The traditional possibility function is transformed into the grey cloud possibility function, which effectively takes advantage of the grey cloud model in dealing with the coexistence of fuzzy information, grey information and random information. Thus, the conflict between the decision-making results and the objective reality is effectively solved. The interval grey number can make full use of the effective information and improve the accuracy of the actual information.

This study aims to compare the diversification risk of the crypto portfolio with those of equity portfolios. For this purpose, the hypothetical index was constructed with 20 cryptocurrencies that hold the highest market capitalization in the Coin Market Cap database, named as the Crypto-Index 20.

The portfolio diversification techniques were used to identify risk linked with the six largest European equity indexes and compared with the Crypto-Index 20. Indexes were considered as an independent portfolio while analysis was completed separately for each of them. Data concerning stock prices and their trade volume were collected from the Thomson Reuters Eikon database while crypto prices and their trade volume from the Coin Market Cap database. The diversification risk of the stock indexes was measured separately for each portfolio with the same risk techniques and the same methodological process.

Research results indicate that Crypto-Index 20 on average was 76 times riskier than FTSE 100, 55 times riskier than FTSE MIB, 44 times riskier than IBEX 35, 10 times riskier than CAC 40 and 9 times riskier than DAX and MDAX. Crypto-Index 20 comprises a stronger positive correlation and is exposed to higher volatility than six selected European equity indexes.

This research provides practical implications for the investors on the diversification benefits and risks attached to the cryptocurrencies portfolio by comparing it with the traditional equity portfolios. From a policy perspective, regulators might obtain information on the risk properties involved into cryptocurrencies and the possibility of creating an optimal portfolio.

Although the microfinance sector in developing countries has seen an impressive development in recent years, many small-scale farmers in rural areas are still undersupplied with capital. One of the main reasons for this undercapitalization is the exposure to weather risks. Weather index insurance is assumed to bear high potential for accelerating agricultural lending. The index design hereby is of particular importance. The purpose of this paper is to estimate the influence of evapotranspiration and precipitation indices on the credit risk of farmers in Madagascar.

The authors base the analysis on a unique borrower data set provided by a commercial microfinance institution in Madagascar and weather data provided by CelsiusPro. In this context, evapotranspiration and precipitation indices both at aggregated bank level and at branch level are identified and their influence on credit risk of small-scale rice farmers is estimated.

The results show that the weather-related part of the credit risk of farmers can be better explained by an evapotranspiration then by a precipitation index. The precipitation index underestimates the weather influence on credit risk especially during the harvesting season. The results suggest a potential for weather index insurance which is based on an evapotranspiration index. The results are of similar importance for developed and developing countries.

The results suggest that, should insurance be considered as an appropriate risk management instrument for the farmers or the bank, weather index insurance has the potential to mitigate a certain part of the credit risk. The authors also find that the focus on precipitation-based index insurance products would underestimate the weather influence on credit risk. Furthermore, the results suggest that insurance products should be tailored to branches to be most effective.

To the authors’ knowledge, this is the first study that compares the explanatory values of evapotranspiration and precipitation indices in general and for the credit risk of small-scale farmers in particular.

Using cotton yield, and rainfall data from Tajikistan, the purpose of this paper is to investigate the magnitude of weather induced revenue losses in cotton production. Hereby the authors look at different risk aggregation levels across political regions (meso-level). The authors then design weather index insurance products able to compensate revenue losses identified and analyze their risk reduction potential.

The authors design different weather insurance products based on put-options on a cumulated precipitation index. The insurance products are modeled for different inter-regional and intra-regional risk aggregation and risk coverage scenarios. In this attempt the authors deal with the common problem of developing countries in which yield data is often only available on an aggregate level, and weather data is only accessible for a low number of weather stations.

The authors find that it is feasible to design index-based weather insurance products on the meso-level with a considerable risk reduction potential against weather-induced revenue losses in cotton production. Furthermore, the authors find that risk reduction potential increases on the national level the more subregions are considered for the insurance product design. Moreover, risk reduction potential increases if the index insurance product applied is designed to compensate extreme weather events.

The findings suggest that index-based weather insurance products bear a large risk mitigation potential on an aggregate level. Hence, meso-level insurance should be recognized by institutions with a regional exposure to cost-related weather risks as part of their risk-management strategy.

The authors are the first to investigate the potential of weather index insurance for different risk aggregation levels in developing countries.

This paper aims to empirically examine the performance of the high-ESG (environment, social and governance) portfolio vis-à-vis the low-ESG portfolio at the Indian stock market before and during the Covid19 pandemic.

The absolute rate of return and several risk-adjusted performance measures, for instance, Sharpe ratio, Modigliani–Modigliani measure, Treynor ratio, Jensen’s alpha, information ratio, Fama’s decomposition measure and Fama and French’s three-factor model, have been used in this study along with the t-test.

All three indices (CARBONEX, GREENEX and BSE 500) had better returns during Covid19 period as compared to the pre-Covid19 period. However, these returns were not statistically significant. During Covid19, the risk of the indices also rose, but they provided better returns for the additional risk taken. Finally, it is concluded that the performance of high-ESG and low-ESG stock portfolios did not differ significantly in both periods.

The study is relevant to individual and institutional investors, financial advisors, portfolio managers, corporations, policymakers, market regulators and society at large.

This study emphasized the need to expand the role of ESG investment in India for the benefit of people, communities and society as a whole.

This research is the first of its kind, to the best of the authors’ knowledge, that compares the performance of a high-ESG portfolio with a low-ESG portfolio both before and during the Covid19, particularly in the Indian context.

The purpose of this paper is to review the most recent scientific literature on the determinants explaining the demand for index-insurance, the impact of index-insurance and the existing links between insurance and credit. In this meta-analysis, the authors identify key discoveries on the potential of index-insurance in enhancing credit supply for smallholders and thus farm productivity.

Following a systematic literature search in Scopus and Web of Science, relevant empirical articles were identified by using the following criteria search algorithm: “insurance” and (“weather” or “micro” or “area?based” or “rain*” or “livestock” or “index”), and ((“empiric*” or “experiment” or “trial” or “RCT” or “impact”) or (“credit” or “loan*” or “debt” or “finance”)). The authors identified 1,133 related papers, 110 of which were selected as closely matching the study criteria. After removing duplicates and analysing each document, 45 papers were included in the current analysis. The framework for addressing insurance and credit issues, in the paper, entails three subsequent themes, namely, adoption of insurance, impact of insurance and links between insurance and credit.

It is not confirmed yet that demand for insurance is indeed hump-shaped in risk aversion and the functional form of this relationship should be tested in more detail. This also holds for the magnitude of the effect of trust and education on actual demand. Furthermore, it is unclear to what extent other risk mitigation strategies form complements or substitutes to index-insurance. Lastly, the interaction between basis risk and price is important to the design of index-insurance products. If basis risk and price elasticity are indeed highly correlated, products that diminish basis risk are crucial in increasing demand. On the impact of bundled products, e.g. combination of insurance and credit, limited empirical research has been conducted. For example, it is unknown to what extent credit suppliers would react to the insured status of farmers or what the preferences of farmers are when it comes to a mix of financial products. In addition, several researchers have suggested that microfinance institutions or banks could insure themselves against covariate risk, yet no empirical evidence about this insurance mechanism has been conducted so far.

The authors based the research on scientific literature uploaded in Scopus and Web of Science. Other potentially insightful grey literature was not included due to lack of accessibility. Given the research findings, there is plenty of opportunity for further research particularly with regard to the effects of bundled products, e.g. insurance plus credit, on demand for index-insurance, supply of credit, loan conditions and impact on farm productivity and farmers’ well-being.

Microfinance institutions, insurance companies, NGOs, research institutions and universities, particularly in developing countries, will be interested to learn about the systematic review of scientific research done in the area of insurance and credit for agriculture and the possibilities for application in their own practice of supplying these financial products.

A rigorous understanding of the potential of index-insurance and credit is essential for identifying the right mix of financial products that help smallholder farmers to increase farm productivity and their own well-being.

The paper is valuable due to its rigorous evaluation of existing theoretical and empirical research around issues explaining the degree of adoption and impact of index-insurance and that of bundled financial products (i.e. index-insurance plus credit). The paper has the potential to become essential reading for academics, practitioners and policy-makers interested in researching and putting in practice the best options leading to greater farm productivity and well-being in developing countries.

The purpose of this paper is to develop a quantitative risk assessment method for agricultural products cold chain logistics to assess the condition of the fresh agricultural products cold chain process objectively and accurately.

A risk assessment index system of agricultural products cold chain logistics is designed on the basis of the risk identification for the process of agricultural products cold chain logistics. This paper first uses catastrophe progression method and a new maximum deviation method to build an improved catastrophe progression assessment model for agricultural products cold chain logistics. In order to verify the reliability and validity of the model, two representative enterprises are selected as the case in the study.

The results in the empirical research indicate strong support for the assessment model and coincide with the reality. The risk assessment index system can also reflect the key risk factors from agricultural products cold chain logistics scientifically. In addition, the improved catastrophe progression assessment method proposed in this paper can be scientific and reasonable to predict risk.

This paper contributes to provide a new risk assessment model for agricultural products cold chain logistics. The new model overcomes the limitation of subjective empowerment and it increases the objectivity and scientificity in the process of cold chain logistics risk assessment. This paper also shows that practitioners involved in the field of products cold chain logistics can manage the potential risk by a set of scientific methods for assessing the risk before the accident.

The paper provides a practical guideline to practitioners, especially for cold chain logistics managers, relevant management departments, and cold chain logistics management consultants. It is proved that the new risk assessment method and the risk assessment index system of agricultural products cold chain logistics can help them assess the risk scientifically and reasonably.

Although the calculation is simple, the new model can overcome the limitation of subjective empowerment scientifically and reasonably, and thus has important practical value.

The purpose of this paper is to examine factors affecting the use of forage index insurance. Forage is a difficult crop to insure, and index insurance may be well suited for forage insurance and has been implemented in several countries, including Canada, the USA and France. Despite being a promising risk management tool, forage index insurance participation rates in Canada, and other countries are low relative to crop insurance participation rates for grain and oilseed producers.

A survey was conducted with 87 beef and cattle producers from Alberta and Saskatchewan, Canada. A probit regression model was used, and a number of variables were included to examine the use of forage index insurance.

In total, 6 of 11 variables in the model are found to be statistically significant in explaining forage producers’ use of forage index insurance. Results suggest that producers who maintain lower feed reserves are more likely to purchase forage index insurance. Also, producers with higher levels of knowledge of crop insurance and a more positive attitude toward forage insurance are more likely to use forage index insurance. Furthermore, producers are more likely to use forage index insurance if they perceive drought and weather risk as being of greater importance, and if they are younger. The importance of the variable forage index insurance premium price was statistically insignificant. This could be due to the effect of subsidization, reducing the importance of price for the decision to purchase. Similarly, the use of other subsidized risk management policies, including a whole-farm margin policy (e.g. the government program and AgriStability), did not reduce forage index insurance use. A possible explanation for this is that the subsidization of the policies may make it profitable to purchase both, despite the overlapping coverage.

These results may be useful for policy makers interested in increasing forage index insurance participation rates, as forage index insurance participation rates have historically been low relative to grain and oilseed producers.

This study is believed to be one of the first studies regarding the use of forage index insurance by forage producers. Producers can be exposed to catastrophic risks such as drought or other extreme weather events, and forage index insurance may be an effective means to manage these risks. Index insurance determines payments using an index that is correlated to producers’ actual yields. A downside of this method is basis risk, which is the mismatch between the insured index and the producer’s actual yield. Research has focused on basis risk and developing improved methods to reduce basis risk. However, less research has investigated the other important factors that may contribute to forage index insurance use. Producers may have a different risk management environment regarding forage production compared to other farm activities, and these differences have largely not been examined.

This study aims to investigate the interconnectedness across the risk appetite of distinct investor types in Borsa Istanbul. This study also examines the causal impact of global implied volatility indices on the risk appetite of these investor groups.

The authors use a novel time-varying frequency connectedness framework of Chatziantoniou et al. and a new time-varying Granger causality test with a recursive evolving procedure by Shi et al. over June 2008 and July 2022.

The results show a high level of interconnectedness across the risk appetite of different investor types. The sizable spillovers to domestic types of investors either occur from professional or foreign investors, indicating the long-term dominant effect of foreign and more qualified investors on the domestic investors in Borsa Istanbul. The authors provide significant evidence of causality from the global implied volatility to the Borsa Istanbul risk appetite indices, which are getting stronger after the COVID-19 outbreak.

Unlike the previous studies, the authors analyze the risk appetite sub-indices of various types of investors to reveal behavioral distinctions and interconnectedness across them. The authors use a novel econometric framework to assess investors’ risk appetite in different investment horizons in a time-varying system. Together with volatility index (VIX), the authors also use volatilities of oil (OVX), gold (GVZ) and currency (EVZ), considering the information transmission not only from stock markets but also energy, metals and currency markets. The present data set covers significant financial crises, socioeconomic events and the COVID-19 outbreak.