Abstract

Recent turmoil in financial markets endorses the need for rigorous handling and integration of asset liquidity risk into Value-at-Risk (VaR) models. In this work we develop and test measures of certain kinds of asset liquidity risk that is useful for completing the definition of market risk and for predicting liquidity-adjusted VaR under adverse market conditions. This paper presents a practical simulation framework for the modeling of asset liquidity risk for portfolios that consist of multiple long and short trading assets. We put forward a method whereby the holding periods are adjusted according to the specific needs of each trading portfolio by explicitly modeling a linearly-distributed liquidation scheme by means of a pertinent scaling multiplier. The empirical testing is achieved using daily return data of emerging Gulf-Cooperation-Council (GCC) stock markets. We simulate and analyze different relevant portfolios (of both long and short-sales trading positions) and determine the risk-capital exposure under varied illiquid and adverse market conditions.

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