Reach Us +441474556909
Asset Liquidity Adjusted VaR | OMICS International
ISSN: 2167-0234
Journal of Business & Financial Affairs
Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.
Meet Inspiring Speakers and Experts at our 3000+ Global Conferenceseries Events with over 600+ Conferences, 1200+ Symposiums and 1200+ Workshops on
Medical, Pharma, Engineering, Science, Technology and Business

Asset Liquidity Adjusted VaR

Dr. Viviane Y Naimy*

Professor of Finance, Faculty of Business Administration and Economics, Notre Dame University, Louaize, Lebanon

*Corresponding Author:
Dr. Viviane Y. Naimy
Professor of Finance, Faculty of Business Administration and Economics
Notre Dame University, Louaize, Lebanon
E-mail: [email protected]

Received November 17, 2014; Accepted November 18, 2014; Published December 15, 2014

Citation: Naimy VY (2014) Asset Liquidity Adjusted VaR. J Bus Fin Aff 3:129. doi:10.4172/2167-0234.1000129

Copyright: © 2014 Naimy VY. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Visit for more related articles at Journal of Business & Financial Affairs


Liquidity risk is divided into asset liquidity risk and funding liquidity risk. The first one, known as market/product-liquidity risk arises when a forced liquidation of assets creates unfavorable price movements. This risk varies across categories of assets and across time as a function of prevailing market conditions. It can be managed by setting limits on certain markets or products and by means of diversification. Liquidity risk can be factored into VaR measures by ensuring the horizon is at least greater than an orderly liquidation period.

Funding-liquidity risk or cash-flow risk refers to the inability to meet payments obligations, which may force early liquidation. This constitutes a problem for portfolios that are leveraged and subject to margin calls from the lender. Funding-risk can be controlled by setting limits on cash-flow gaps, by diversification, and by consideration of how new funds can be raised to meet cash shortfalls.

Liquidity needs are uncertain. A great deal of research is still going on to model liquidity risk and measure its effects when managing other types of risks. Discussion has begun on the creation of liquidity risk derivatives allowing parties to trade liquidity risk. The 2007 credit crisis has emphasized the importance of liquidity risk for financial institutions and regulators. Financial institutions are required to assess worst-case liquidity scenario and make sure that they can overcome that scenario by either converting assets into cash or borrowing fund externally. Basel III requirements are well tailored to ensure that banks do this [1].

The question in this editorial paper is to study how VaR can be adapted to deal with asset liquidity considerations [2].

The process of assessing asset liquidity risk starts with focusing on the various components of liquidation costs. The first and most easily measurable is the quoted bid-ask spread, defined in relative terms as S where

image      (1)

Spreads vary from a low of about 0.05% for major currencies, large US stocks, and on-the-run Treasuries to much higher values when dealing with less liquid currencies, stocks, and bonds. Spreads depend also on market conditions. Spreads reflect three different types of costs according to market microstructure theory: order-processing costs, asymmetric-information costs, and inventory carrying costs.

A simple way to measure the cost of liquidating a position in an asset in a normal market conditions, is to consider the cost equal

image      (2)

Where n is the number of positions,

αi is the position in the ith instrument, and

Si is the proportional bid-offer spread for the ith instrument.

Although diversification reduces market risk, it does not reduce liquidity trading risk. It is worth noting that Si increases with the size of position i. holding many positions tends to entail less liquidity risk. Therefore as mentioned above, setting position limits is a strategy to decrease trading risk [3].

Another measure of liquidity is the cost of liquidation in stressed market conditions within a defined time period.

image      (3)

Where μi and σi are the mean and standard deviation of the relative spread for the ith financial instrument held,

λ is the parameter that gives the required confidence level for the spread.

Equation (3) assumes that spreads of all instruments are perfectly correlated.

Once the spread are fixed, one simply could construct a liquidityadjusted VaR, LVAR, from the traditional VaR by adding the cost of unwinding positions in a normal market or a stressed market as suggested by Bangia et al. who in fact consider the uncertainty in the spread [4].

image      (4)

image      (5)

This assumes that the worst market loss and increase in spread will occur simultaneously. In general we observe a positive correlation between volatility and spreads. At the portfolio level, one theoretically could take into account correlations between spreads. In practice, summing the individual worst spreads provides a conservative measure of the portfolio worst spread but in fact it is not. Because when liquidity is tight and spreads widen, they tend to do so for all instruments. Therefore it makes sense to calculate the liquidity measures in equation (2) and (3) on a regular basis which are likely to be decreasing functions of the liquidation time period.


Select your language of interest to view the total content in your interested language
Post your comment

Share This Article

Relevant Topics

Article Usage

  • Total views: 11956
  • [From(publication date):
    December-2014 - Dec 19, 2018]
  • Breakdown by view type
  • HTML page views : 8146
  • PDF downloads : 3810

Post your comment

captcha   Reload  Can't read the image? click here to refresh

Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2018-19
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri and Aquaculture Journals

Dr. Krish

[email protected]

+1-702-714-7001Extn: 9040

Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals


[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry


[email protected]

1-702-714-7001Extn: 9042

© 2008- 2018 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version