Applying data visualization and knowledge discovery in databases to segment the market for risky financial assets

Leece, David

doi:10.1002/(sici)1099-1468(199908)20:5<267::aid-mde938>3.0.co;2-4

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…As an example,Leece (1999) uses cluster analysis to segment market for risky ſ nancial assets and his analysis reveals that previous study may have missed some important interactions in the data.6 Kunz (2007) presents a rich application of choice model based on latent variable models and principal component analysis to visualize competitive market structures based in individual consumer choice data.…”

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confidence: 99%

Patterns of Debt Use in Small Businesses: A Non-Parametric Analysis

Chakraborty

Mallick²

2010

International Journal of Banking and Finance

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This paper uses non-parametric techniques to examine patterns of debt use by small firms and how such patterns differ across firm categories. The methodological goal is to use the richness of the firm level data and allow convincing presentations with minimum of assumptions. The procedures used provide easily comprehendible graphical descriptions of the data. The procedures augment what can be discerned from descriptive statistics by accounting for differential weights and allowing for clustering that is a native feature of cross-sectional data. We also investigate how firms could benefit if credit availability improves. Though a model-based analysis would be required to provide a detailed analysis, our analysis suggests that greater credit availability will benefit all firms. Firms with low levels of equity will be better off as their credit constraints will be less binding, while firms with high levels of equity will benefit from acquiring more debt.

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confidence: 99%