The analysis of outlying data points by robust Locally Weighted Scatter Plot Smooth: a model for the identification of problem banks
Source: International Journal of Operational Research, Volume 7, Number 1, 30 November 2009 , pp. 1-15(15)
Publisher: Inderscience Publishers
Abstract:Continuing bank failures point to the need for early warning problem bank identification models to guide the actions of regulators and investors. Several models have been shown to work well, but most require extensive data preparation/manipulation and custom computer programmes to analyse the data, which hinders widespread adoption. In this article, we show that robust Locally Weighted Scatter Plot Smooth, a type of Local Regression Smoothing, which requires minimal data preparation and can be run in many off the shelf statistical packages such as SAS and SPSS, can be just as effective as an early warning system.
Document Type: Research Article
Affiliations: 1: Department of Finance, Graduate School of Management, College of Business Administration, Kent State University, Kent 44242, OH, USA. 2: Department of Management and Information Systems, Graduate School of Management, College of Business Administration, Kent State University, Kent 44242, OH, USA. 3: Office of the Provost, Kent State University, Kent 44242, OH, USA
Publication date: November 30, 2009