Ebook Modeling Liquidity Risk, With Implications for Traditional Market Risk Measurement and Management
The recent turmoil in the capital markets has led experts and laymen alike to cast liquidity risk in the role of the culprit. Inexperienced and sophisticated players were all caught by surprise when markets dried up. Unsurprisingly, the first to go were the emerging markets in Asia and more recently in Russia. Then it spilled over into the US corporate debt market which was indeed much more surprising. Its most famous victim has been Long Term Capital Management (LTCM). Spreads appeared to widen out of the blue; but this could have been predicted.
More generally, it is a well acknowledged fact that the standard Value-at-Risk (VaR) concept used for measuring both market and credit risk for tradable securities lacks a rigorous treatment of liquidity risk. At best, the risk for large illiquid positions is adjusted upwards in an ad hoc fashion by utilizing a longer time horizon in the calculation of VaR that at best is a subjective estimate of the likely liquidation time of the position. This holding-period adjustment is usually carried out using the square root of time scaling of the variances and covariances rather than a recalculation of variances and covariances for the longer time horizon.
However, the combination of the recent rapid expansion of emerging market trading activities and the recurring turbulence in those markets has propelled liquidity risk to the forefront of market risk management research. New work in asset pricing has demonstrated how liquidity plays a key role in security valuation and optimal portfolio choice by effectively imposing endogenous borrowing and shortselling constraints, as argued by Longstaff (1998) and the references therein.
Liquidity also plays a major role in transaction costs as trades of large illiquid positions typically execute at a price away from the mid-price. BARRA’s Market Impact Model and other such models quantify the market impact cost, defined as the cost of immediate execution, for establishing and liquidating large positions. Jarrow and Subramanian (1997) consider the effect of trade size and execution lag on the liquidation value of the portfolio. They propose a liquidity adjusted VaR measure that incorporates the liquidity discount, volatility of liquidity discount, and the volatility of time horizon to liquidation. Although conceptually attractive, there is no available data or procedure to measure the model parameters such as mean and variances for quantity discounts or execution lags for trading large blocks.
In this article, we present a framework for treating liquidity risk using readily available data and integrating it with VaR calculations for market risk measurement of tradable securities. We make an important distinction between exogenous liquidity risk, which is outside the control of the market maker or trader, and endogenous liquidity risk, which is in the trader’s control and usually the result of sudden unloading of large positions which the market is unable to absorb easily. In a nutshell, we address a fundamental concern being raised currently in the markets, that current models ignore valuable information contained in the distribution of bid-ask spreads.
The rest of the paper is organized as follows. In section 2 we present our conceptual framework for understanding market risk, liquidity risk, and their interaction. In section 3 we describe the various components of overall market value uncertainty and techniques for their measurement, with emphasis on the neglected liquidity risk component and our approach to modeling it, and we also include worked examples for FX instruments. In section 4, we broaden the analysis from one instrument to an entire portfolio, and we display backtesting examples that reveal the very different results that can be obtained depending on whether liquidity risk is or is not incorporated. We conclude in section 5 with additional discussion of selected issues.
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