Convex risk measures for the aggregation of multiple information sources and applications in insurance

We propose a novel class of convex risk measures, based on the concept of the Fréchet mean, designed in order to handle uncertainty which arises from multiple information sources regarding the risk factors of interest. The proposed risk measures robustly characterize the exposure of the firm, by filtering out appropriately the partial information available in individual sources into an aggregate model for the risk factors of interest. Importantly, the proposed risks can be expressed in closed analytic forms allowing for interesting qualitative interpretations as well as comparative statics and thus facilitate their use in the everyday risk management process of the insurance firms. The potential use of the proposed risk measures in insurance is illustrated by two concrete applications, capital risk allocation and premia calculation under uncertainty.     

我国林业扶贫工作的主要问题及优化措施研究

林业扶贫是当前我国扶贫工作的重要内容。通过介绍开展林业扶贫工作的政策背景、理论背景以及经济背景,分析林业扶贫工作开展过程中存在的基础设施落后、针对性差等问题,提出了因地制宜,互联网+林业扶贫,鼓励社会资本进入扶贫工作、志智双扶等应对措施。     

Direct intervention or indirect support? The effects of cooperative control measures on farmers’ implementation of quality and safety standards

In recent years, labor-intensive agricultural products from developing countries have exhibited inferior performance in international trade due to quality and safety incidents, among which pesticide residue is a major issue. Aiming to improve food quality and safety in the context of cooperatives, we introduced three categories of control measures: outcome control, process control and social control. Based on the Pre-Harvest Interval Standard (PHIS), we selected three indices, farmers’ implementation rate of PHIS, absolute distance to PHIS and relative distance to PHIS, to evaluate appropriateness of pesticides use, reduction of pesticide residue and safety improvements of agricultural products. By using random sampling survey data, we empirically analyzed the marginal effects of control measures and their combinations on food quality and safety standards. The empirical results show that implementing process control, namely, unified production standards or supply of unified agricultural inputs, can comprehensively improve farmers’ implementation rate of PHIS, absolute distance and relative distance to PHIS respectively by 34.9%, 3.2 days and 46.0% on average. While the effects of outcome control (safety inspection) and social control (bonus-penalty incentive or training) are restricted to other measures. Therefore, we suggest cooperatives should take farmers’ features, implementation conditions and the effects of control measures into consideration in order to make a sustainable management plan for improving food quality and safety and enhancing competitiveness in international markets.     

Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures

Using daily data from August 9, 2015, to July 7, 2020, this study examines the effects of economic policy uncertainty (EPU) on the returns of four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Ripple. To this end, two new measures of EPU (Twitter-based economic uncertainty and Twitter-based market uncertainty) are considered. A Granger causality test using the recursive evolving window approach shows a significant causality between the Twitter-based EPU measures and the BTC/USD exchange rate from October 2016 to July 2017. Moreover, a significant causality was noted from the EPU measures to the ETH/USD exchange rate from June 2019 to February 2020 and from the EPU measures to the XRP/USD exchange rate from January 2020 to February 2020. The Twitter-based EPU measures primarily positively affect the returns of the related cryptocurrencies during these periods. These results are robust to different measures of Twitter-based EPU and different econometric techniques. Potential implications, including the COVID-19 era, are also discussed.     

Operational risk quantified with spectral risk measures: a refined closed-form approximation

The quantification of operational risk has become an important issue as a result of the new capital charges required by the Basel Capital Accord (Basel II) to cover the potential losses of this type of risk. In this paper, we investigate second-order approximation of operational risk quantified with spectral risk measures (OpSRMs) within the theory of second-order regular variation (2RV) and second-order subexponentiality. The result shows that asymptotically two cases (the fast convergence case and the slow convergence) arise depending on the range of the second-order parameter. We also show that the second-order approximation under 2RV is asymptotically equivalent to the slow convergence case. A number of Monte Carlo simulations for a range of empirically relevant frequency and severity distributions are employed to illustrate the performance of our second-order results. The simulation results indicate that our second-order approximations tend to reduce the estimation errors to a great degree, especially for the fast convergence case, and are able to capture the sub-extremal behavior of OpSRMs better than the first-order approximation. Our asymptotic results have implications for the regulation of financial institutions, and may provide further insights into the measurement and management of operational risk.     

Conditional risk measures in a bipartite market structure

In this paper, we study the effect of network structure between agents and objects on measures for systemic risk. We model the influence of sharing large exogeneous losses to the financial or (re)insurance market by a bipartite graph. Using Pareto-tailed losses and multivariate regular variation, we obtain asymptotic results for conditional risk measures based on the Value-at-Risk and the Conditional Tail Expectation. These results allow us to assess the influence of an individual institution on the systemic or market risk and vice versa through a collection of conditional risk measures. For large markets, Poisson approximations of the relevant constants are provided. Differences of the conditional risk measures for an underlying homogeneous and inhomogeneous random graph are illustrated by simulations.     

粮食挂壁的原因分析及预防措施

粮食挂壁是由于粮堆内部湿热传导异常或粮堆与外界湿热传导异常,粮堆内局部水分较高和热量聚集粮食发热霉变形成的。文章分析了常见易发生挂壁的情形及预防措施,主要从仓房防潮性、隔热性、粮食水分变化、储粮微生物及害虫、粮食杂质聚集、异常粮情处理等方面进行分析,并提出了相应解决对策。     

新冠疫情对我国中小企业经济状况的影响及对策分析

2020年以来,新冠疫情对我国中小企业的影响巨大。论文从收入、成本、现金流三个方面分析了疫情下我国中小企业的现状及可采取的对策,以期助力中小企业渡过难关。     

浅谈如何做好建设工程项目成本控制

随着经济的快速发展,越来越多的建设工程项目出现在人们的视野中,建筑市场的竞争愈演愈烈,工程项目利润空间逐渐缩小。因此,建设工程项目成本控制的重要性日益凸显。论文介绍了建设工程项目成本控制需要遵循的原则,分析了建设工程项目成本管理存在的问题,探讨了建设工程项目成本控制的措施。     

Observing viewers’ self-reported and neurophysiological responses to message appeal in social media advertisements

PurposeMarketing research mainly uses self-reported method to record respondents' perceptions of creativity, and while self-reported method has its own merits, there exists some critique, particularly in terms of its ability to adequately capture the influence of message appeal on creativity. This paper studies how viewers’ responses to message appeals in social media advertisement compare in terms of self-reported responses versus responses taken through a neurophysiological method of Electroencephalograph (EEG).MethodologyTwo social media advertisements are displayed through a laboratory experiment to 17 subjects observing the subjects' neurophysiological reactions as well as their self-reported responses with regard to the commercials’ emotional, informational, and brand-related content.FindingsResults show that neurophysiological method offers unique details about emotional appeal, which the self-reported method fails to reflect. Furthermore, the neurophysiological measure identifies differences across the two target commercials in the emotional content part, which again are not identified through the self-reported method.OriginalityThis paper advances advertising research in social media literature by comparing content evaluation within advertisement through neurophysiological and self-reported measure. These findings have implications for marketers to use and measure message appeals in advertisement on social media to influence consumer response.