Computing the Gerber–Shiu function by frame duality projection

Inspired by some works of Kirkby, J. L. [2015. Efficient option pricing by frame duality with the fast Fourier transform. SIAM Journal on Financial Mathematics 6(1), 713–747; 2016. An efficient transform method for Asian option pricing. SIAM Journal on Financial Mathematics 7(1), 845–892], we present a systematic study on effectively computing the Gerber–Shiu function in the Lévy risk model, where the frame duality projection is used for approximation. By introducing an auxiliary function, we provide a smooth extension of the Gerber–Shiu function, which has closed-form Fourier transform and is differentiable over the whole real line under some conditions. The objective function is approximated by its frame duality projection onto a Riesz basis, and the projection coefficients are readily computed by the fast Fourier transform algorithm. Error analysis is made and the effectiveness of our results will be further illustrated in the numerical experiments.     

Contextual Framing and Monetary Incentives in Field Experiments on Risk Preferences: Evidence from German Farmers

Recent studies cast doubt on the ability of abstract experiments to predict decision‐making in the field. Thus, scholars have argued for more ‘realism’ by introducing context to field experiments. Yet, such realism may work against the induced values of monetary incentives in economic experiments. It is an open question whether contextual framing works best with or without inducing values, through methods such as the use of monetary incentives. Using a sample of 146 German farmers, we compare experimentally the predictive power of a framed lottery in an agricultural context vs. using an abstract version. For one half of the sample, lotteries are incentivised; for the other half, they are hypothetical. Although risk preferences differ between treatments, all four lottery tasks correlate poorly with farmers’ real‐world use of risk management instruments such as harvest or hail insurance. Subjects who start with an agricultural framing are willing to take significantly greater risks in the lotteries. More generally, our findings cast doubt on the ability of lottery tasks to predict risk‐taking in the field.     

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.     

A Multicriteria Approach for Modeling Small Enterprise Credit Rating: Evidence from China

ABSTRACT

As the engine of China’s economy, small enterprises have been the central to the country’s economic development. However, given the characteristics of the small enterprises loan (i.e., short borrowing period, large volume, small amount and incomplete information), it is extremely challenging for financial institutions to assess their creditworthiness. Thus, it seriously delays and restricts the financing access for small enterprises. In an attempt to relieve the financing difficulty of small enterprises, this article makes use of 687 small wholesale and retail enterprises in a regional commercial bank in China, to establish a credit rating indicator system composed of 17 indicators by using both partial correlation analysis and probit regression. It then utilizes TOPSIS together with fuzzy C-means to score the credit ratings of our sample of small enterprises. With the dual test of default discrimination and ROC curve, the prediction accuracy of the established indicator system has reached 80.10% and 0.917, respectively, indicating the robustness and validity of our credit rating system.     

A Historical Review of Postponement Research

This historical review traces the development of postponement research starting in the fifties. The focus is on seven related themes: connecting form and time postponement, conceptual extensions to postponement, decoupling points, design for postponement, customization and mass customization, factors favoring postponement implementation, and postponement in global settings. Within these themes, the review includes concepts such as postponement costs, decoupling points, part commonality, and the impact of demand correlations on the benefits of postponement. The review suggests that substantial progress has been made in postponement research.     

特许权价值、最优关闭策略和存款保险定价

随着存款保险制度的推出以及金融机构退出机制的完善，国家声誉将逐渐退出银行无形资本。在激励相容的金融监管趋势下，特许权价值等市场约束力量会显著影响到商业银行的风险承担。在此逻辑基础上，以我国16家上市商业银行为研究对象，一方面探讨特许权价值影响下不同产权结构的商业银行的最优救助机制，另一方面通过最优救助临界指标，利用银行重组模型，推导合理的存款保险风险差别费率。     

An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.     

How government regulation of interbank financing impacts risk for Chinese commercial banks

The rapid development of interbank financing in China has exposed financial institutions to increasing risk. In 2013, the China Banking Regulatory Commission implemented regulation on interbank financing for commercial banks. We assess the effectiveness of this regulation in reducing (i) the risk of commercial banks relative to non-bank financial institutions, where the latter are not subject to the regulation, and (ii) the risk of major commercial banks, which are more disposed to engage in interbank finance, relative to minor commercial banks. Our data are for the period 2006–2016 for 30 commercial banks (13 major, 17 minor) and 56 non-bank financial institutions. To control for other factors, we make use of a difference-in-difference estimation approach. Our measure of risk is the z-score, for which a higher value means a lower risk of bankruptcy. We find in support of the effectiveness of the regulation with z-scores for commercial banks rising relative to those of non-bank financial institutions and z-scores of major banks rising relative to those of minor banks following implementation of the regulation.     

Intranational Consumption Risk Sharing in South Korea: 2000–2016

This paper examines consumption risk sharing among 16 regions in South Korea over the 2000–2016 period. The empirical results show that 91.8 percent of shocks to gross regional domestic product are smoothed in South Korea. Capital markets, the tax‐transfer system and credit markets absorb 29.9, 28.9 and 33.0 percent of shocks to gross regional domestic product, respectively. Most notably, South Korea relies more on credit markets for risk sharing than capital markets, an opposite pattern to advanced countries like the USA, Canada and Australia. Furthermore, the patterns of consumption risk sharing are different before and after the 2007–2008 global financial crisis, and differences in regional industrial structure and local development can influence these patterns. This paper attempts to infer the connection between these findings and both the rapid economic growth of South Korea and the Asian and global financial crises.     

Risk assessment for public–private partnership projects: using a fuzzy analytic hierarchical process method and expert opinion in China

Public–private partnerships (PPP) have been widely used in China to procure public facilities and services. Complicated problems in PPP projects in China arise because of a variety of risk factors. A proper risk assessment model is needed to identify risks and provide risk response strategies for future Chinese PPP projects. The fuzzy analytic hierarchy process (F-AHP) method provides the ability to solve complex risk assessment of PPP projects. Current risk assessment models are limited to PPP projects in specific countries and do not consider unique risks in China, especially political, economic, social, and legal risks. This paper designed a risk evaluation index system for PPP projects based on the Delphi expert investigation method, and then established an optimized risk evaluation model for PPP projects in China using the F-AHP method. The risks identified are confirmed by interviewing experts from Chinese local government departments, private enterprise, third-party intermediary consulting and regulatory agencies, and academic organizations. The results show that the risks that ranked among the top ten are closely related to China’s political and economic policies and relationships among stakeholders. It can be concluded that government authorities play a critical role in providing a favorable political, social, and economic environment and an effective institutional framework for PPP projects. Furthermore, it is also important to deal with relationships among stakeholders based on the public–private ‘win–win’ principle. This study provides risk response strategies, addressing key issues from eight aspects: an impeccable legal and regulatory framework; a central coordinating and regulating PPP authority; supportive governmental authorities; institutional capacity-building; favorable economic conditions and viability; community, partner, and moral accountability; clear division of responsibilities through contracts; and effective advisory management. These effective measures may be useful in reducing the adverse effects of risk for PPP projects in China.