The use of relative value credit analytics is not new, but the importance of this methodology has come into sharper focus and has been the subject of increased investor attention over the last 12 months. There are two main reasons why relative value credit strategy has become a hot topic in the last year. The first is an extraordinary surge of issuance seen in bond market. The second is the extreme volatility within the credit sector in the face of COVID-19. Both these phenomena have created significant opportunities for realisation of value, and although, by the time of writing, the markets have calmed down considerably from the turbulence seen 12 months earlier, the party is not over yet.

Portfolio managers and traders that use OTC derivatives often lack an accurate real-time view of the valuations and risk of their derivative positions, especially when trading exotic derivatives. Obtaining real-time risk metrics for a portfolio of derivatives has been challenging, as the commonly used valuation techniques for these products are computationally expensive and require significant machine time. Portfolio valuations and risk calculations typically require overnight runs in a data center or the cloud. This whitepaper reports the successful use of Artificial Neural Network models by Quantifi to model and deliver real-time pricing with an accuracy considered equivalent to conventional approaches such as numerical integration and Monte Carlo methods.

One of the key challenges of XVAs is that adjustments need to be calculated on a portfolio basis rather than trade-by-trade. This requires dealing with a large number of computations and orders of magnitude more calculations for accurate results. The calculation of XVAs is highly complex, combining the intricacies of derivative pricing with the computational challenges of simulating a full universe of risk factors. Given the strategic importance of XVA, banks require enhanced capabilities and modern infrastructures to calculate the required credit, funding, and capital adjustments. As banks look to reduce, mitigate, and optimize XVA and other capital charges, they are investing in XVA capabilities in an attempt to solve the computational challenge of simulating a full universe of risk factors.

Interbank Offered Rates (IBORs) play a pivotal role in the functioning of financial markets. The transition away from IBOR represents one of the biggest challenges facing financial services firms. The reform has been ongoing for more than two years, during which market-infrastructure providers, regulators, buy- and sell-side firms and trade associations have merged their efforts in steering some of the most complex transformation programmes the financial industry has undertaken. This paper explores the development of the IBOR reform. The first part details the status quo, some of the various aspects and challenges involved and outlines the effects of migrating from IBORs to risk-free rates. The second part of the paper outlines the preparations firms need to make to accommodate a smooth transition.

The COVID-19 (C19) pandemic has severely affected global markets, causing economic disruption at unprecedented speed and on a hitherto unknown scale. With the spread of the virus accelerating by mid-March 2020, the US economy has been severely impacted and there are understandable concerns about the damage caused to the worldwide economy. This paper explores the effects of the pandemic on the credit derivatives market and, more specifically, how recent bankruptcies affected North American high yield (NA HY) CDS index trading, including CDX.NA.HY indices and the options on them.

Historically, liquidity risk has been the poor cousin of market risk and credit risk. While the global financial crisis of 2008/2009 first pushed the issue of liquidity risk to the forefront of attention, the most recent market dislocation due to the COVID-19 pandemic has once again highlighted the salient significance of the topic. This is particularly so for institutional investment managers who have to meet margin calls, perform regular fund rebalancing, execute redemptions, among other potentially liquidity-threatening activities. Failure to afford liquidity risk management the focus and priority jeopardizes the health of an institution, perhaps fatally so.

This whitepaper provides an insight into the risks inherent to the cryptoasset market and can be broken into three parts. Section one of this paper looks at the significance of credit risk associated with exchanges, custody and prime brokerage services. The second section explores counterparty risk in a traditional financial institutional setting. The final section provides insights on how to extend the traditional credit risk framework to the cryptoasset industry. Overall, we aim to bridge the credit and counterparty risk considerations between incumbent and cryptoasset institutions.