Adjusting value-at-risk for market liquidity
Liquidity remains a key risk factor in many portfolios, but quantifying it remains an open question. Here, David Cosandey offers a new macroeconomic approach to quantifying liquidity risk based upon trading volume, and incorporates it into VAR, testing his model against empirical data
The Asian and Russian crises of the late 1990s, and the Long-Term Capital Management (LTCM) debacle, demonstrated the need to better understand market liquidity risk. Several methodologies have been suggested that include market liquidity effects in value-at-risk. Some of them rely on bid-ask spreads (Bangia et al, 1999, and Monkkonen, 2000). These approaches raise the difficulty of gathering long
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 Cutting Edge
Floating exercise boundaries for American options in time-inhomogeneous models
A pricing model is extended to account for negative interest rates or convenience yields
Quantcast Master’s Series: Walter Farkas, ETH – University of Zurich
Swiss planning, large joint faculty and public presentations shape the programme
The relative entropy of expectation and price
The replacement of risk-neutral pricing with entropic risk optimisation
Quantcast Master’s Series: Jack Jacquier, Imperial College London
A shift towards market micro-structure and ML has reshaped the programme
Quantcast Master’s Series: Kihun Nam, Monash University
Melbourne-based programme winks at pension fund sector
Quantcast Master’s Series: Petter Kolm, Courant Institute
The NYU programme is taught almost exclusively by elite financial industry practitioners
Quantcast Master’s Series: Laura Ballotta, Bayes Business School
The business school prioritises the teaching of applicable knowledge with a keen eye on the real world
The importance of modelling futures dynamics in commodity index derivatives
Index-based and underlying-based pricing methods for commodity derivatives are presented