Fat tails via utility-based entropy
Asset returns are well known to be fat-tailed, but widely used classical econometric techniques are not well suited for building such distributions. Craig Friedman, Yangyong Zhang and Wenbo Cao use a minimum relative utility-based entropy principle to estimate the fat-tailed conditional asset return distributions sought by traders and risk managers
Practitioners and researchers concerned with describing and managing risk or discovering trading strategies for alpha-capture often construct and study conditional probabilistic models of the behaviour of asset returns, given the values of various explanatory variables.
Fat tails via utility-based entropy
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
Fireside chat: Advancing FX clearing for safer settlement
Developments in FX clearing are supporting the creation of a safer, more scalable settlement infrastructure
FHLB Cincinnati explores AI to spot failing banks
Agentic model detects anomalies, monitors sentiment and drafts credit reports for analyst review
Iran strikes a stress test for CCP margin models
CME’s Span2 and Ice’s IRM2 are performing as advertised. The next few days could test their mettle
Most banks run physical climate scenarios beyond 2050
Risk Benchmarking data finds majority rely on geospatial asset mapping, while a third use third-party catastrophe models
Big banks love their climate vendors; small banks, not so much
Risk Benchmarking: Lenders with blue-chip loan books more likely to favour climate tools, research finds
Mob rule: populism’s rise pits banks against the people
Trump and fellow mavericks are reshaping politics, leaving banks scrambling to adjust to new and unpredictable risks
JSCC considers default fund consolidation
Japanese clearing house looks for efficiency gains amid expansion of clearing products and influx of international firms
EU clearing houses pressured to diversify cloud vendors
CROs and regulators see tech concentration risk as a barrier to operational resilience