This paper extends the extreme downside correlations and hedge (EDC and EDH) methodology of Harris et al. (2019) to model the tail risk co-movement of financial assets under severe firm-level and market conditions. The model is applied to analyze both systematic and systemic exposures in the...

The paper examines the relationships among market assets during stressful times, using two recently proposed econometric modeling techniques for tail risk measurement: the extreme downside hedge (EDH) and the extreme downside correlation (EDC). We extend both measures taking into account the...

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...

Financial technologies (fintechs) are continuously expanding, across different markets and financial services. While financial technologies bring many opportunities, such as reduced costs and extended inclusion, they also bring risks, among which include cyber risks, that are difficult to...

Financial institutions are increasingly leveraging on advanced technologies, facilitated by the availability of Machine Learning methods that are being integrated into several applications, such as credit scoring, anomaly detection, internal controls and regulatory compliance. Despite their high...