Bankruptcy prediction has been a topic of research for decades, both within the financial and the academic world. The implementations of international financial and accounting standards, such as Basel II and IFRS, as well as the recent credit crisis, have accentuated this topic even further. This paper describes both regularized and non-linear kernel variants of traditional discriminant analysis techniques, such as logistic regression, Fisher discriminant analysis (FDA) and quadratic discriminant analysis (QDA). Next to a systematic description of these variants, we contribute to the literature by introducing kernel QDA and providing a comprehensive benchmarking study of these classification techniques and their regularized and kernel versions for bankruptcy prediction using 10 real-life data sets. Performance is compared in terms of binary classification accuracy, relevant for evaluating yes/no credit decisions and in terms of classification accuracy, relevant for pricing differentiated credit granting. The results clearly indicate the significant improvement for kernel variants in both percentage correctly classified (PCC) test instances and area under the ROC curve (AUC), and indicate that bankruptcy problems are weakly non-linear. On average, the best performance is achieved by LSSVM, closely followed by kernel quadratic discriminant analysis. Given the high impact of small improvements in performance, we show the relevance and importance of considering kernel techniques within this setting. Further experiments with backwards input selection improve our results even further. Finally, we experimentally investigate the relative ranking of the different categories of variables: liquidity, solvency, profitability and various, and as such provide new insights into the relative importance of these categories for predicting financial distress.
Haspeslagh, Philippe; Slagmulder, Regine; Bloemhof, M. (2004)
The case describes the strategic planning process and performance management system implemented at DSM, a global chemical company. In particular, it describes how the company's value based business steering system is designed to create alignment between strategy formulation and execution through strategic value contracts. The case illustrates the performance management process in action at one of the business groups. It highlights managers' dilemma between continuing to pursue the current business strategy which is in line with corporate strategy, versus responding to the financial pressures exerted by the new value based management approach which would require a radical change in strategy. The case allows students to discuss the various elements of DSM's value based management (VBM)-inspired strategy and performance management processes, and how they impact one of the business groups' efforts to improve performance. The class can analyse the strengths and weaknesses of the company's approach to aligning its strategic planning and financial management processes by introducing strategic value contracts. Finally, the case shows how DSM distinguishes between performance indicators to monitor strategy implementation, and value drivers to measure economic value creation.
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