Abstract
An important, yet neglected, aspect of risk management is liquidity risk; changes in value due to reduced availability of traded financial instruments. This ubiquitous risk has emerged as one of the key drivers of the developing “credit crunch” with global financial liquidity plummeting since the crisis began. Despite massive cash injections by governments, the crisis continues. Contemporary research has focussed on the liquidity component of single instruments’ value-at-risk. This work is extended in this article to measure portfolio value-at-risk, employing a technique which integrates individual instruments’ liquidity-adjusted VaR into a portfolio environment without a commensurate increase of statistical assumptions.
Highlights
The Basel Capital Accord, published in 1988, set down the agreement among the G-10 central banks to apply common minimum capital standards to their banking industries by the end of 1992 (BIS, 1988)
The forecast LVaRJS (Equation 7) was calculated for each equity portfolio, using parameters obtained from portfolio data and compared with the daily forecast 95 per cent LVaRsimple (Equation 6)
liquidityadjusted VaR (LVaR) using the JS methodology has been successfully incorporated into a portfolio framework
Summary
The Basel Capital Accord, published in 1988, set down the agreement among the G-10 central banks to apply common minimum capital standards to their banking industries by the end of 1992 (BIS, 1988). Cosandey, 2001: 116), but these are based upon single instrument VaR approaches and their application to portfolios is not uniform Less sophisticated approaches such as those that rely on conventional measures of leverage to estimate liquidity risk sometimes provide meaningless results (Bangia, 1999: 70). The existence of both endogenous and exogenous liquidity risk (which are quite different in both structure and manifestation), autocorrelation and scaling in time of return data and the aggregation of single-instrument liquidity VaR into portfolio liquidity VaR (Umut, 2004: 315) all involve non-trivial and computer-intensive implementation. The problems and limitations of the current research are explored and some questions are posed which are answered, which introduces a formal explanation of a new portfolio liquidity VaR measure.
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