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dc.date.accessioned2021-09-24T14:37:17Z
dc.date.available2021-09-24T14:37:17Z
dc.identifier.urihttps://fif.hebis.de/xmlui/handle/123456789/1978
dc.description.abstractWe construct a simple tool that allows us to portray the loss distribution of asset portfolios, and of any tranche that is derived from the same underlying portfolio. We apply a firm-value model to capture the occurrence of obligor default. More precisely, we apply a structural one-factor correlated default model as in Vasicek (1987). The driving factor is a market factor, and company value is modeled as the interplay of the market factor and a company specific, idiosyncratic risk factor. This market model approach is the model of choice in most corporate finance applications. We model company value Vn,t of each obligor n ? 1, 2, ..., N at any time t before maturity as being driven by a generalized macroeconomic factor YtM that is common to all securities, and an idiosyncratic component. In the implementation, we do not need to apply simplifying assumptions to determine the loss distribution of the underlying portfolio. Instead, we are able to fully profit from the Monte Carlo Simulation procedure. Analytical approaches often rely on limiting assumptions, e.g. that the portfolio is composed of an infinite number of securities with identical characteristics. Thus, analytical models to some extent may be suitable for sensitivity analyses, but Monte Carlo Simulation is more appropriate for real-world applications. All individual securities in the portfolio can be accounted for by their specific exposure size, recovery rate, default probability, and maturity. Furthermore, Monte Carlo Simulation allows to differentiate between obligors and individual securities. The occurrence of joint obligor defaults is modeled by accounting for the sensitivity of each individual obligor to the common factor.
dc.rightsAttribution-ShareAlike 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.titleSurvey_KW_2009
dc.typeResearch Data
dc.identifier.urlhttps://www.ifk-cfs.de/fileadmin/downloads/publications/wp/09_11.pdf


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