英国和意大利小型企业的比较分析

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英文标题：
《A comparative analysis of the UK and Italian small businesses using
  Generalised Extreme Value models》
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作者：
Galina Andreeva, Raffaella Calabrese and Silvia Angela Osmetti
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最新提交年份：
2014
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英文摘要：
  This paper presents a cross-country comparison of significant predictors of small business failure between Italy and the UK. Financial measures of profitability, leverage, coverage, liquidity, scale and non-financial information are explored, some commonalities and differences are highlighted. Several models are considered, starting with the logis- tic regression which is a standard approach in credit risk modelling. Some important improvements are investigated. Generalised Extreme Value (GEV) regression is applied to correct for the symmetric link function of the logistic regression. The assumption of non-linearity is relaxed through application of BGEVA, non-parametric additive model based on the GEV link function. Two methods of handling missing values are compared: multiple imputation and Weights of Evidence (WoE) transformation. The results suggest that the best predictive performance is obtained by BGEVA, thus implying the necessity of taking into account the relative volume of defaults and non-linear patterns when modelling SME performance. WoE for the majority of models considered show better prediction as compared to multiple imputation, suggesting that missing values could be informative and should not be assumed to be missing at random.
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中文摘要：
本文对意大利和英国小企业倒闭的重要预测因素进行了跨国比较。探讨了盈利能力、杠杆率、覆盖率、流动性、规模和非财务信息等财务指标，突出了一些共性和差异。考虑了几种模型，首先是logis-tic回归，这是信用风险建模的标准方法。研究了一些重要的改进。应用广义极值（GEV）回归对logistic回归的对称连接函数进行校正。通过应用基于GEV链接函数的非参数加性模型BGEVA，放宽了非线性假设。比较了两种处理缺失值的方法：多重插补和证据权重（WoE）变换。结果表明，BGEVA可获得最佳预测性能，因此，在建模中小企业绩效时，有必要考虑违约的相对数量和非线性模式。与多重插补相比，所考虑的大多数模型显示出更好的预测，这表明缺失值可以提供信息，不应假设为随机缺失。
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分类信息：

一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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关键词：小型企业 比较分析 意大利 Quantitative Applications