Cracking VAR with kernels
Value-at-risk analysis has become a key measure of portfolio risk in recent years, but how can we calculate the contribution of some portfolio component? Eduardo Epperlein and Alan Smillie show how kernel estimators can be used to provide a fast, accurate and robust estimate of component VAR in a simulation framework
The notion of component value-at-risk (CVAR) originated in the papers of Garman (1996, 1997) and Litterman (1997a, 1997b) and has been used by banks as a practical risk analysis tool since at least Epperlein & Sondhi (1997). The goal is to calculate how much some component of a portfolio contributes to the portfolio's total VAR. We denote the profit and loss (P&L) of the portfolio as PL and the P&L of the ith component as PLi.
Click Here To Download PDF
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact info@risk.net to find out more.
You are currently unable to copy this content. Please contact info@risk.net to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@risk.net
More on Risk management
Mitigating model risk in AI
Advancing a model risk management framework for AI/machine learning models at financial institutions
BoE warns over risk of system-wide cyber attack
Senior policy official Carolyn Wilkins also expresses concern over global fragmentation of bank regulation
Treasury clearing timeline ‘too aggressive’ says BofA rates head
Sifma gears up for extension talks with incoming SEC and Treasury officials
Strengthening technology resilience and risk controls against multidomain disruption
The consequences of multidomain disruption and best practice strategies to enhance digital resilience
Op risk data: Mastercard schooled in £200m class action
Also: Mitsubishi copper crunch, TD tops 2024 op risk loss table. Data by ORX News
Diversification of LDI liquidity buffers sparks debate
Funds using credit assets to top up collateral waterfall, but some risk managers are sceptical
Transforming stress-testing with AI
Firms can update their stress-testing capability by harnessing automated scenario generation, says fintech advocate
Basel stops short on wrong-way risk
New guidelines a step in right direction, but experts warn they won’t prevent another Archegos