Fed paper breaks new ground on economic capital modelling
BOSTON, MASSACHUSETTS
-- A paper published in April, Using loss data to quantify operational risk, by Federal Reserve Bank of Boston officials, applies a modelling technique to data from external public op risk databases to help correct data problems inherent within those products.The paper addresses the problem of sample selection bias by "using an econometric model in which the truncation point for each loss (ie, the dollar value below which the loss is not reported) is modelled as an
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
Iosco chief defends margin transparency standards
More reporting will improve financial system’s resilience, argues Rodrigo Buenaventura
Credit loss database reveals holes in Basel’s IRB formula
Researcher has used two decades of data to propose improved internal model methodology
AI in capital markets: credit risk landscape
The first part of a discussion series exploring the dynamic landscape of predictive and generative AI
AI in capital markets: automation use cases
Part two of a three-part discussion series exploring the dynamic landscape of predictive and generative AI
AI in capital markets: model development and data
Part three of a three-part discussion series exploring the dynamic landscape of predictive and generative AI
Market knee-jerks keep VAR models on their toes
With a return to volatility, increased backtesting exceptions show banks’ algos are stretched
Why the survival of internal models is vital for financial stability
Risk quants say stampede to standardised approaches heightens herding and systemic risks
Clearing members welcome LME default fund cap
But 2022 nickel crisis still makes hedge funds doubt banks would foot the bill for default at all
