关于建立中国存款保险制度的构想

存款保险制度是市场经济国家为了保护存款人利益 ,维护金融稳定 ,加强对存款类金融机构的监管而建立的一种保险制度。中国目前已基本具备建立存款保险制度的条件。随着中国成为WTO的正式成员 ,建立这种制度的需求日益迫切。本文从发达市场经济国家建立存款保险制度的运行情况和相互比较入手 ,分析了中国建立存款保险制度已具备的若干条件和必须注意的几个问题 ,并就建立中国的存款保险制度提出了建设性方案     

Short-time at-the-money skew and rough fractional volatility

The Black–Scholes implied volatility skew at the money of SPX options is known to obey a power law with respect to the time to maturity. We construct a model of the underlying asset price process which is dynamically consistent to the power law. The volatility process of the model is driven by a fractional Brownian motion with Hurst parameter less than half. The fractional Brownian motion is correlated with a Brownian motion which drives the asset price process. We derive an asymptotic expansion of the implied volatility as the time to maturity tends to zero. For this purpose, we introduce a new approach to validate such an expansion, which enables us to treat more general models than in the literature. The local-stochastic volatility model is treated as well under an essentially minimal regularity condition in order to show such a standard model cannot be dynamically consistent to the power law.     

Data mining framework based on rough set theory to improve location selection decisions: A case study of a restaurant chain

Location selection plays a crucial role in the retail and service industries. A comprehensive location selection model and appropriate analytical technique can improve the quality of location decisions, attracting more customers and substantially impacting market share and profitability. This study developed a data mining framework based on rough set theory (RST) to support location selection decisions. The proposed framework consists of four stages: (1) problem definition and data collection; (2) RST analysis; (3) rule validation; and (4) knowledge extraction and usage. An empirical study focused on a restaurant chain to demonstrate the validity of the proposed approach. Twenty location variables relevant to five location aspects were examined, and the results indicated that latent knowledge can be identified to support location selection decisions.     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

创新生态系统如何驱动企业微创新——一个组态视角的fsQCA分析

近年来,微创新是创新研究领域的热点,如何驱动企业微创新是相关研究亟需回答的问题。整合创新生态系统3个层面六大要素,运用模糊集定性比较分析（fsQCA）方法,以18个微创新案例为样本,探讨创新生态系统驱动企业微创新的复杂因果机制。结果发现：第一,单个创新生态系统要素并不构成企业高微创新的必要条件。第二,存在3条高微创新驱动路径,即机会识别主导下的用户驱动型、机会识别主导下的环境与用户参与驱动型,以及机会识别主导下的环境、组织学习与领先用户驱动型。此外,非高微创新驱动路径仅有一条,且与高微创新驱动路径存在非对称关系。第三,机会识别能力作为核心条件出现在高微创新的3个组态及非高微创新一个组态中,说明机会识别能力对企业微创新具有重要作用。     

什么样的数字创新生态系统能提高区域创新绩效——基于NCA与QCA的研究

什么样的数字创新生态系统有助于提高区域创新绩效是亟待解决的热点问题。采用必要条件分析（NCA）和模糊集定性比较分析（fsQCA）两种方法,对我国内地31个省（区、市）进行实证分析。研究发现：①数字企业、政府、高校及科研机构、数字创新基础设施、数字人才和金融服务是数字创新生态系统的关键构成,但单个要素并不是提高区域创新绩效的必要条件;②4种数字创新生态系统要素组态有助于提高区域创新绩效,构成的数字创新生态系统分别是政府引导的智力聚集型、企业开拓的环境支撑型、主体多元的综合发展型和企业主导的资本驱动型;③各地应因地制宜,选择合适的数字创新生态系统,培育区域创新新动能,助推“数字中国”新发展。     

西安市《第三套全国中小学生系列广播体操》实施情况的调查分析

《第三套全国中小学生系列广播体操》于2008年9月开始在全国推广,通过对西安市中小学校《第三套全国中小学生系列广播体操》实施情况的分析,指出西安市中小学校《第三套全国中小学生系列广播体操》实施的成功所在;同时分析影响《第三套全国中小学生系列广播体操》实施所存在的一些问题,为更好的促进本套操的实施提出建议性对策。     

数字赋能企业商业生态系统跃迁升级的机理及路径研究

数字技术应用融合叠加商业模式创新催生商业生态新业态,实现跃迁升级。本文结合扎根理论与模糊集定性比较分析（fsQCA）方法,阐释数字赋能企业商业生态系统跃迁升级的机理,探究多重组态路径。从生态视角揭示了数字资源通过与传统要素资源融合释放数据价值,并驱动形成价值循环体系、实现价值共创、塑造商业群落,最终实现企业商业生态系统跃迁升级。基于fsQCA的多组态分析发现,数字赋能企业商业生态系统跃迁升级历经两个阶段分别为价值共创和商业群落生成。其中,价值共创实现有两条组态路径,即产品创新与要素融合相组合,技术融合同低产品创新、低数据资产相组合,且产品创新构成了价值共创的核心条件。商业群落生成的组态路径表现出以下特征：价值共创和价值链接协同下分别和网络组织、数据赋能相组合,网络组织和数据赋能互为替代,即在一方缺失时,分别与价值共创或价值链接组合实现商业群落构建。研究结论为企业商业生态系统的结构与功能持续优化,实现数字商业生态资源的充分共享及最优利用,提供了关键方法和思路。     

基于SPA数据结构的四川省贫困地区农村居民消费结构研究——对7个国家级贫困县（市、区）的调查与分析

文章将农村住户总支出看成是一种系统,并运用集对理论（SPA）,对四川省贫困地区农村居民消费结构的16项消费支出及其消费水平进行同异反态势分析,探讨贫困地区农户消费需求重点,并提出保障其消费水平的政策建议。