کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9663633 | 1446235 | 2005 | 25 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Forecasting business profitability by using classification techniques: A comparative analysis based on a Spanish case
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
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چکیده انگلیسی
A comparative study of the performance of a number of classificatory devices, both parametric (LDA and Logit) and non-parametric (perceptron neural nets and fuzzy-rule-based classifiers) is conducted, and a Monte Carlo simulation-based approach is used in order to measure the average effects of sample size variations on the predictive performance of each classifier. The paper uses as a benchmark the problem of forecasting the level of profitability of Spanish commercial and industrial companies upon the basis of a set of financial ratios. This case illustrates well a distinctive feature of many financial prediction problems, namely that of being characterized by a high dimension feature space as well as a low degree of separability. Response surfaces are estimated in order to summarize the results. A higher performance of model-free classifiers is generally observed, even for fairly moderate sample sizes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 167, Issue 2, 1 December 2005, Pages 518-542
Journal: European Journal of Operational Research - Volume 167, Issue 2, 1 December 2005, Pages 518-542
نویسندگان
Javier de Andrés, Manuel Landajo, Pedro Lorca,