Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach

In order to challenge the existing literature that points to the detachment of Bitcoin from the global financial system, we use daily data from August 17, 2011–February 14, 2020 and apply a risk spillover approach based on expectiles. Results show reasonable evidence to imply the existence of downside risk spillover between Bitcoin and four assets (equities, bonds, currencies, and commodities), which seems to be time dependent. Our main findings have implications for participants in both the Bitcoin and traditional financial markets for the sake of asset allocation, and risk management. For policy makers, the findings suggest that Bitcoin should be monitored carefully for the sake of financial stability.     

一种飞行器集群管理和任务分离的组网方法

组网是卫星、无人机等飞行器集群实现协同的基础。传统自组织组网技术针对地面随机移动场景设计，不适用于拓扑和传输根据任务变化的飞行器集群场景，为此设计了一种管理与任务分离的组网方法，将网络分为管理面和任务面两个逻辑层面，管理面负责拓扑发现、路由建立、任务规划等基础组网功能，任务面负责任务执行过程中的数据传输功能。管理面和任务面实行不同的组网策略，从而使得网络的传输性能根据管理和任务执行的不同需求进行优化，以减少协议开销及降低传输自干扰。     

Network structure,portfolio diversification and systemic risk

We investigate the effect of portfolio diversification on banking systemic risk, where the network effect is incorporated. We analyze three kinds of interbank networks, namely, random networks, small-world networks and scale-free networks. We show that the effect of portfolio diversification on banking systemic risk depends on interbank network structures and shock types. First, systemic risk increases first and then reduces with the increase of the level of portfolio diversification in the case of the individual shock. Second, in the case of the systemic shock, systemic risk reduces with the increases of the level of portfolio diversification. Third, banking systems with scale-free network structures are the most stable, and those with small-world network structures are the most vulnerable.     

Multilayer financial networks and systemic importance: Evidence from China

In this paper, we develop a multilayer network structure and reveal the relationship between network structure and systemic risk. Unlike many previous studies, our model considers both liability and cross-holding of shares between financial institutions simultaneously. We propose a new systemic risk measurement by exploring the dynamic mechanism of financial contagion in the multilayer network. We display the network structure of Chinese financial institutions, including connectivity and diversity, and identify the systemic importance of them. We demonstrate that the multilayer network plays a non-linear role in financial risk spreading. Using the panel regression model and several experiment evidences, we show that the systemic risk can be explained more effectively by the linkage diversity more than the connectivity at both the institutional level and the system level. Our results highlight the importance of considering contagion mechanisms that go beyond a simple single-layer network structure.     

Is the system reliability profitable for retailing and consumer service of a dynamical system under cross-price elasticity of demand?

Retailing strategy is one of the most crucial factors for industries. A proper retailing strategy can help to enhance consumer service and increase the industry's profit. An improved approach to retailing is suggested in this research to deliver superior customer service while maximizing profits in a dynamic system. The study analyzes a retailing strategy for a demand with cross-price elasticity upon the retail price. A product's cross-price elasticity and the system reliability are critical factors in retailing. Understanding the cross-price elasticity of demand between products helps retailers to make pricing decisions that maximize profits by maintaining demand. Imperfect products are produced due to an imperfect production system. The imperfect ones must be adjusted with some costs to make them perfect for better retailing. The system failure rate is crucial for retailing under cross-price elasticity of demand patterns. Production system reliability, cross-price elasticity of demand, and consumer service are all essential factors that can impact a company's success in the market. The production rate is considered time- and system failure rate-dependent. Contradictory to the literature, a dynamical system is proposed for improved retail management, which is solved using the Euler-Lagrange theory. Finally, one can achieve the expected maximum profit for this retail system with optimum selling prices for different products by reducing the system failure rate. Some numerical illustrations with graphical representations are provided to validate the current study. Numerical examples show that applying cross-price elasticity of demand for more than two identical products provides 35% more profit for the retail industry than a single type of product.     

MODELING SOVEREIGN RISKS: FROM A HYBRID MODEL TO THE GENERALIZED DENSITY APPROACH

Motivated by the European sovereign debt crisis, we propose a hybrid sovereign default model that combines an accessible part taking into account the evolution of the sovereign solvency and the impact of critical political events, and a totally inaccessible part for the idiosyncratic credit risk. We obtain closed‐form formulas for the probability that the default occurs at critical political dates in a Markovian setting. Moreover, we introduce a generalized density framework for the hybrid default time and deduce the compensator process of default. Finally, we apply the hybrid model and the generalized density to the valuation of sovereign bonds and explain the significant jumps in long‐term government bond yields during the sovereign crisis.     

The acerbity of the social: how to include the social in governmental risk assessments

This paper addresses the expansion of risk practices through a case study of a government led project in Sweden purposed to develop a method to include social events in mandatory risk practices. Social heterogeneity was to be transformed into straightforward causality in order to turn the social into a manageable object. In this regard, the project was quite successful. By inviting social scientists into the process, otherwise often marginalized within risk practice, causality and quantifiable risk factors could be established and the model became a rigorous and legitimate scientific model. Although experts were granted significant autonomy and became experts far beyond their own area of expertise, the success of the model lies rather in allowing experts authority within confined boundaries. Grand narratives and critical perspectives are disregarded as too abstract and if social scientists are to infuse aspects of social critique they must adapt to these circumstances: they must become instrumentalists.     

基于GM(1,1)模型的造纸业上市公司财务研究——以冠豪高新为例

财务风险是企业调整发展战略、提升管理水平的重要参考指标之一。财务风险预测模型的建立能够预测企业在中短期内的财务风险,为企业敲响警钟。以造纸业上市公司冠豪高新为例,选取近五年财务杠杆系数为风险指标,建立GM(1,1)风险预测模型,结果显示该公司短期内财务风险呈下降趋势,调查发现这主要得益于产品成本的降低以及营销策略的改变。     

Semistatic hedging and pricing American floating strike lookback options

We price an American floating strike lookback option under the Black–Scholes model with a hypothetic static hedging portfolio (HSHP) composed of nontradable European options. Our approach is more efficient than the tree methods because recalculating the option prices is much quicker. Applying put–call duality to an HSHP yields a tradable semistatic hedging portfolio (SSHP). Numerical results indicate that an SSHP has better hedging performance than a delta-hedged portfolio. Finally, we investigate the model risk for SSHP under a stochastic volatility assumption and find that the model risk is related to the correlation between asset price and volatility.