Risk management for return enhancement
Lundin and Satchell present a non-linear asymmetric dependence method between two assets
Myriad dependence measures are actively implemented in financial market applications today. Pearson's productmoment correlation coefficient (as well as covariance) remains ubiquitous in practice, despite its inability to capture nonlinear dependence and its assumption of homoscedasticity.
CLICK HERE TO VIEW THE PDF
Rank correlation methods capture nonlinear dependence, though they do so by replacing sample magnitudes with ordinal ranking.
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.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
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. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net
More on Asset management
How Bloomberg got liquidity seekers to trust its machine learning models
Recent liquidity squeezes have proved the worth of advanced models, argues the tech giant. Now the task is to explain their inner workings to machine learning sceptics
Asset-liability management: Special report 2023
There is nothing new about the dynamics behind the asset-liability management (ALM) banking crisis of earlier this year: maturity transformation, liquidity risk and interest rate risk are at the heart of the traditional banking business model. But these…
How small and medium-sized banks can enhance deposits modelling frameworks
Recent events have called into question the reliability of deposits as a primary source of funding for small and medium-sized banks. Stickiness of deposits that generations of bankers had counted on suddenly seem ephemeral
ALM banking after the crisis: stress-testing for more robust liquidity management practices
A panel of industry experts discusses a new age of depositor behaviour and the expected evolution of regulations in the wake of the asset-liability management (ALM) banking crisis. They share insights on achieving integrated approaches to ALM, as well as…
Fleeting volatility vexes trend followers
Jumpy markets give quant firms the jitters as tried-and-tested strategies struggle in 2023
Chartis RiskTech Buyside50
The second annual RiskTech Buyside50 ranking from Chartis Research outlines notable trends in the buy side and ranks the key players operating within it, focusing on solutions, industry segments and the scope and breadth of investment lifecycle…
Hedge funds raise stakes in fight over dealer rule
Two prominent industry bodies file legal papers in key court case over SEC’s proposed extension of dealer definition
How Man Numeric found SVB red flags in credit data
Network analysis helps quant shop spot concentration and contagion risks
