References of "Nadal de Simone, Francisco"
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See detailA Framework for Tracking Changes in the Intensity of Investment Funds’ Systemic Risk
Jin, Xisong UL; Nadal de Simone, Francisco

in Journal of Empirical Finance (2014), 29

This study applies to investment funds a novel framework which combines marginal probabilities of distress estimated from a structural credit risk model with the consistent information multivariate ... [more ▼]

This study applies to investment funds a novel framework which combines marginal probabilities of distress estimated from a structural credit risk model with the consistent information multivariate density optimization (CIMDO) methodology of Segoviano, and the generalized dynamic factor model (GDFM). The framework models investment funds’ distress dependence explicitly and captures the time-varying non-linearities and feedback effects typical of financial markets. It measures investment funds systemic credit risk in three forms: (1) credit risk common to all funds within each of the seven categories the Eurosystem reports to the ECB; (2) credit risk in each category of investment fund conditional on distress on another category of investment fund and; (3) the buildup of investment funds’ vulnerabilities over time which may unravel disorderly. In addition, the estimates of the common components of the investment funds’ distress measures contain early warning features, and the identification of their drivers is useful for macroprudential policy. As a result, this framework contributes to making macroprudential policy operational [less ▲]

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See detailBanking Systemic Vulnerabilities: A Tail-risk Dynamic CIMDO Approach
Jin, Xisong UL; Nadal De Simone, Francisco

in Journal of Financial Stability (2014)

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See detailTimeliness in Selected Structural Credit Risk Models
Jin, Xisong UL; Lehnert, Thorsten UL; Nadal de Simone, Francisco

E-print/Working paper (2013)

We empirically investigate and evaluate various approaches to structurally assess credit risk changes using a panel of selected European banking groups. The objective is to evaluate the models according ... [more ▼]

We empirically investigate and evaluate various approaches to structurally assess credit risk changes using a panel of selected European banking groups. The objective is to evaluate the models according to one metric, i.e., their ability to correctly and timely identify changes in credit risk indicators useful for macroprudential policy. We consider not only the standard approaches in the literature, but also include models that allow the asset volatility to be stochastic and models that allow for short- and long-term components of default risk. Surprisingly, we find that the GARCH structural credit risk model, despite its more sophisticated modeling approach, typically underperforms more basic models. Importantly for macro-prudential policy, combining the Merton model with the GARCH-MIDAS model performs best and reflects important market events earlier than the other approaches. [less ▲]

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See detailAn Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal
Jin, Xisong UL; Nadal de Simone, Francisco

Scientific Conference (2012, April 25)

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See detailMarket- and Book-Based Models of Probability of Default for Developing Macroprudential Policy Tools
Jin, Xisong UL; Nadal de Simone, Francisco

E-print/Working paper (2011)

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