دانلود مقاله انگلیسی:تجزیه و تحلیل مقایسه ای از کسب و کارهای کوچک بریتانیا و ایتالیایی با استفاده از مدل کلی ارزش افراطی
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  • A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models

    A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models

    سال انتشار:

    2016


    عنوان انگلیسی مقاله:

    A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models


    ترجمه فارسی عنوان مقاله:

    تجزیه و تحلیل مقایسه ای از کسب و کارهای کوچک بریتانیا و ایتالیایی با استفاده از مدل کلی ارزش افراطی


    منبع:

    Sciencedirect - Elsevier - European Journal of Operational Research, 249 (2015) 506-516. doi:10.1016/j.ejor.2015.07.062


    نویسنده:

    Galina Andreeva a,∗, Raffaella Calabrese b, Silvia Angela Osmetti c


    چکیده انگلیسی:

    Article history:Received 23 January 2014Accepted 28 July 2015Available online 10 August 2015Keywords:Decision support systems Risk analysisCredit scoringSmall and Medium Sized Enterprises Default predictionThis 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 in- formation are explored, some commonalities and differences are highlighted. Several models are considered, starting with the logistic regression which is a standard approach in credit risk modelling. Some important improvements are investigated. Generalised Extreme Value (GEV) regression is applied in contrast to the lo- gistic regression in order to produce more conservative estimates of default probability. 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 Evi- dence (WoE) transformation. The results suggest that the best predictive performance is obtained by BGEVA, thus implying the necessity of taking into account the low 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.© 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
    Keywords: Decision support systems | Risk analysis | Credit scoring | Small and Medium Sized Enterprises | Default prediction


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 11
    حجم فایل: 331 کیلوبایت

    قیمت: 1000 تومان


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