Abstract
Data mining is an important new topic within the financial world with multiple applications in risk management, trading, marketing etc. For example banks apply data mining in various areas from credit scoring to the pricing of loans. In this chapter the focus is on the detection of observations different from the majority, called outliers. This can be of interest for market analysts, risk managers, regulators and traders. The exceptions might be caused by exceptional circumstances and can require extra hedging or can be seen as trading opportunities. They could as well give regulators an early warning and signal for potential trouble ahead.
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De Spiegeleer, J., Marquet, I., Schoutens, W. (2018). Outlier Detection of CoCos. In: The Risk Management of Contingent Convertible (CoCo) Bonds. SpringerBriefs in Finance. Springer, Cham. https://doi.org/10.1007/978-3-030-01824-5_6
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DOI: https://doi.org/10.1007/978-3-030-01824-5_6
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Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01823-8
Online ISBN: 978-3-030-01824-5
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