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    Quantitative Research Webinar Series: Modeling Through-the-Cycle Correlations

    October 2016

    Many financial institutions prefer to take longer-term views when assessing the risks of their credit portfolio. While forward-looking or Point-in-Time (PIT) parameters might be more reflective of the current economic environment, frequent updates may create fluctuations in risk measures.

    Jimmy Huang, Associate Director of Portfolio Research at Moody’s Analytics will discuss two approaches that financial institutions can consider to estimate Through-the-Cycle (TTC) correlation parameters.

    Webinar Highlights:

    Average PIT measures across years to obtain a longer-term TTC average

    Calibration of a TTC correlation measure that generates a default distribution in-line with the institution’s actual default distribution

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    Through-the-Cycle Correlations

    In some instances, financial institutions prefer to take longer-term views when assessing the risks of their credit portfolio. While forward-looking or Point-in-Time (PIT) parameters might be more reflective of the current economic environment, their frequent updates may create fluctuations in risk measures, such as economic capital and unexpected loss, which may not be desirable in some applications. This paper outlines two approaches that financial institutions can consider to estimate Through-the-Cycle (TTC) correlation parameters. The first approach averages PIT measures across years to obtain a longer-term TTC average. The second approach calibrates a TTC correlation measure that generates a default distribution in-line with the institution's actual default distribution.

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