因子關聯結構模型應用於信用風險分析

Abstract

標準因子模型是基於聯合高斯分配去衡量信用風險。鑒於發現當市場經濟蕭條，其違約的廠商家數增加且違約損失率也上升，反之則反。因此論文延伸因子關聯結構模型，第一是將廠商與共同因子之間的相關係數劃分為兩種不同的狀況，第二是將共同因子及條件因素負荷量考慮至違約損失率。實證結果顯示本模型預測廠商未來一年是否違約是相較於其他模型準確。本篇論文也探討當市場處於蕭條時期，影響廠商違約是系統性風險相較於非系統性風險為高。

A standard quantitative method to assess credit risk employs a factor model based on joint multivariate normal distribution properties. By extending the one-factor Gaussian copula model to produce a more accurate default forecast, this paper proposes the incorporation of a state-dependent recovery rate into the conditional factor loading and to model them sharing a unique common factor. The common factor governs the default rate and recovery rate simultaneously, implicitly creating their association. In accordance with Basel III, this paper shows that the tendency toward default during a hectic period is governed more by systematic risk than by idiosyncratic risk. Among those considered, the model with random factor loading and a state-dependent recovery rate is shown to be superior in terms of default prediction.