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...

Transitioning to a low-carbon economy involves risks for the value of financial assets, with potential ramifications for financial stability. We quantify the systemic impact on financial firms arising from changes in the value of financial assets under three climate transition scenarios that...

In this paper, we perform analysis of systemic risk in the financial and energy sector in Europe. In our investigation, we work with daily time series of CDS spreads. We employ factor copula model with GAS dynamics of Oh and Patton (2016) for estimation purposes of dependency structures between...

This paper extends the extreme downside correlation (EDC) and extreme downside hedge (EDH) methodology to model the interdependence in the sensitivity of assets to the downside risk of other financial assets under severe firm-level and market conditions. The model is applied to analyze both...