Adjusting VAR to correct sample volatility bias
The calculation of value-at-risk often relies on using a sample variance for that of the forward-looking distribution. However, using an unbiased estimate of variance leads to biased estimates of VAR. David Frank proposes an adjustment that can be easily retrofitted into existing models to correct for this bias
CLICK HERE TO VIEW THE PDF
In this article, we propose a simple adjustment that can be used when computing value-at-risk (RiskMetrics Group 1996) if a sample standard deviation of returns rather than the true standard deviation is employed. Using the sample standard deviation as if it were the true standard deviation (the usual procedure) results in VAR estimates that are biased downwards. We
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
Big banks look to XVA desks to crush counterparty exposures
Risk Benchmarking: Two-thirds of global dealers run routine optimisation, compared with just 13% of smaller players
Regulators must think bigger to tackle tech risks, says Hong Kong SFC
Leung warns AI adoption and recent cyber scares show new threats require global co-operation
Investment workflows move beyond the trade
J.P. Morgan experts reveal how Vida’s digital tools enhance transparency, analytics, portfolio oversight and investment lifecycle management
Europe expects FRTB to bite on XVA hedges
Risk Benchmarking: One-third of European dealers fear new market risk rules will have major effect on hedges
Non-bank dealers urge rethink on FICC default fund reshuffle
Separating margin will cut bank capital, but non-banks warn they face disproportionate risk-sharing
Why a hybrid approach works best for AI in credit risk modelling
AI helps models look beyond quarterly reports, but CRO says governance curtails full automation
Eurex product co-head departs
Zubin Ramdarshan’s exit comes after exchange CEO Robbert Booij confirms departure
Off the grid? Dealers mull XVA cloud shift
Risk Benchmarking: 69% of European banks still run core XVA calculations predominantly on-premises, and 75% of global dealers
