A presentation was given on 7 March 2018 as the Call for Paper winner for Risk's Quant Summit Europe 2018 Conference based on an original paper titled CDS Rate Construction Methods by Machine Learning Techniques jointly by Raymond Brummelhuis and Zhongmin Luo available...

This article is the second of two articles by the authors on the construction of CDS proxy rates. In the first article, the authors proposed a machine learning (ML) -based proxy-rate construction technique which uses classification to construct so-called Proxy-Names whose liquidly quoted CDS...

The 2007-09 financial crisis revealed that the investors in the financial market were more concerned about the future as opposed to the current capital adequacy for banks. Stress testing promises to complement the regulatory capital adequacy regimes, which assess a bank's current capital...

The presentation was delivered at the invitation by the Department of Statistics at London School of Economics and Political Science based on an original research paper titled CDS Rate Construction Methods by Machine Learning Techniques by Raymond Brummelhuis and Zhongmin Luo here:...

Regulators require financial institutions to estimate counterparty default risks from liquid CDS quotes for the valuation and risk management of OTC derivatives. However, the vast majority of counterparties do not have liquid CDS quotes and need proxy CDS rates. Existing methods cannot account...

To price and risk-manage OTC derivatives, financial institutions have to estimate counterparty default risks based on liquidly quoted CDS rates. For the vast majority of counterparties, liquid CDS quotes are not available and proxy CDS-rates need to be constructed. Existing methods ignore...

For a GARCH(1,1) process, we study the large deviation asymptotics at the horizon k and their consequences for extreme quantile estimation. The results are relevant for the estimation of multi-period Value at Risk and prove that the heuristic “square k” rule used in financial risk management...