With the Great Recession and the regulatory reform that followed, the search for reliable means to capture systemic risk and to detect macrofinancial problems has become a central concern. In the United States, this concern has been institutionalized through the Financial Stability Oversight...

We propose a semiparametric measure to estimate systemic interconnectedness across financial institutions based on tail-driven spill-over effects in a ultra-high dimensional framework. Methodologically, we employ a variable selection technique in a time series setting in the context of a...

In order to integrate and facilitate the research, calculation and analysis methods around the Financial Risk Meter (FRM) project, the R package RiskAnalytics has been developed. Its main goal is to provide data processing and parallelized quantile lasso regression methods for risk analysis...

In this paper we propose a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter () of a linear quantile lasso regression. The FRM is calculated by taking the average of the penalization parameters over the 100 largest US publicly...

We introduce a novel simulation-based network approach, which provides full-edged distributions of potential interbank losses. Based on those distributions we propose measures for (i) systemic importance of single banks, (ii) vulnerability of single banks, and (iii) vulnerability of the whole...

Our paper investigates Indonesia's systemically important banks (SIBs) using theoretical approaches-CoVaR, marginal expected shortfall (MES), and SRISK-to compare with the Basel guidelines as benchmark. We use Indonesian banks' market and supervisory data over the 2008-2019 period. The research...

We examine pitfalls in the use of return-based measures of systemic risk contributions (SRCs). For both linear and non-linear return frameworks, assuming normal and heavy-tailed distributions, we identify non-exotic cases in which a change in a bank's systematic risk, idiosyncratic risk, size or...

This study shows that the statistical property of the commercial banks' rate of returns can be used to explain the resistance to using Value-at-risk (VaR) and stress tests to determine banks' capital adequacy. We showed that “fat-tail” risk requires more capital than the “normal tail”...

Using non-parametric and parametric models, we show that the bivariate distribution of an Asian portfolio is not stable along all the period under study. We suggest several dynamic models to compute two market risk measures, the Value at Risk and the Expected Shortfall: the RiskMetrics...

We consider an investor whose objective is to trade off tail risk and expected growth of the investment. We measure tail risk through portfolio's expected losses conditioned on the occurrence of a systemic event: financial market loss being exactly at, or at least at, its VaR level and...