Valuation adjustments (XVAs)
WHAT IS THIS? The XVAs are a family of adjustments that can be made to the price of a derivatives trade, reflecting counterparty risk (CVA), own-default risk (DVA), funding (FVA), capital (KVA) and margin (MVA). Their theoretical roots and practical implementation are still debated, but pragmatism also matters: banks that ignore XVAs are at risk of mispricing a trade; banks that include them are at risk of never winning a trade.
UK banks’ CVA charges ballooned by £8bn in volatile Q3
Bank of England figures show capital requirements at highest since early pandemic readings
XVAs and counterparty credit risk for an energy market in crisis
Europe’s current energy crisis, coming on the heels of global market volatility caused by the Covid-19 pandemic, has introduced additional complexities to valuation adjustments and counterparty credit risk modelling. Additionally, underdeveloped forward…
Podcast: Piterbarg and Antonov on alternatives to neural networks
Two novel approximation techniques can overcome the curse of dimensionality
Strong dollar pushes ANZ’s CVA charges up 57%
Risk-weighted assets rose A$1.4 billion in three months; biggest quarterly increase since mid-2019
FVA hedge omission from FRTB set to cause headaches
Lack of carve-out for market risk hedges could create hedging issues, experts say
Nomura loses $18m on derivatives CVAs and DVAs
Net result from own and counterparty credit spreads swings to negative
UBS cuts liquidity valuation adjustments to record low
Bank lowered bid-offer fair value discount to reflect current levels of market liquidity
CVA exposures to UK corporates jump ‘hundreds of millions’
Dash for credit protection triggered a doom loop in the CDSs of cross-currency swap counterparties
XVA solution of the year: Murex
Asia Risk Awards 2022
Data-driven wrong-way risk
A calculation method for regulatory CVA wrong-way risk based on credit and exposure is introduced
XVAs boost Helaba trading income but inflate hedging costs
Expense from non-trading hedges reaches highest since at least 2016
Is stochastic cross-currency basis a better way to model IM?
Using Monte Carlo model extension for forward IM calculation avoids excessive outputs for MVA
The contractual dividend bleed
Models for dividend protected options need to compensate for valuation mismatches
A new way to calculate conditional expectations
Gaussian distributions can sharpen one of the most commonly used tools in quant finance
CDS notionals made a comeback in 2021
A 5% rise to highest end-year figure since 2017 driven by swaps on junk debt
No soft landings in flight to safety from Russia
Impact of Ukraine invasion hit bank balance sheets hard; its effects look set to continue
Banks adopt Python for faster XVA data analysis and pricing
Some banks claim the coding language permits XVA pricing in milliseconds
JP Morgan takes $524m XVA loss on nickel, Russia trades
Margin calls, markdowns and rising funding costs result in biggest XVA loss since early 2020
Climate is changing for derivatives valuation adjustments
Banks back increased use of global warming criteria when calculating XVAs
Russian invasion stirs up ‘perfect storm’ for XVA desks
Declining credit quality of Russian companies and spike in inflation threaten CVA and FVA double-whammy for banks
Podcast: UBS’s Gordon Lee on conditional expectations and XVAs
Top quant explains why XVA desks need a neighbour and a reverend
XVA in Japan: the outlook for 2022
Hiroyuki Yoshizawa, executive director, pricing valuations and reference data at IHS Markit Group Japan explores why financial institutions that were early-accounting CVA adopters are now taking the next steps on their XVA journeys
Review of 2021: Default, revolt, reform
Archegos, GameStop, the last days of Libor – markets just about coped in a bleak and disorderly year
XVAs and counterparty credit risk for energy markets: addressing the challenges and unravelling complexity
In this webinar, a panel of quantitative researchers and risk practitioners from banks, energy firms and a software vendor discuss practical challenges in the modelling and risk management of XVAs and CCR in the energy markets, and how to overcome them.