Measurement Of The Liquidity Risk Of Portfolios Based On VaR Model

Beside market-risk and credit-risk, Liquidity-risk is anther important risk of the financial asset. Standard VAR model is mainly used to deal with market-risk and credit –risk. There are already a lot of work both on theoretical and experience study. However the consideration on liquidity –risk is much less. How to include liquidity-risk into VAR model is an important question to those financial management researchers. They have already begun with their work on basis of the bid-ask spread, the time lag of the transaction or the market impact of liquidation. But in their models there always have rigid assumptions on important parameter or the distribution of the samples. The Liquidity-Adjusted Value-at -Risk (L-VaR) model developed in this paper use conditonal-sampling and endogenous liquidity horizon (period of liquidation) under the condition of optimal execution strategy to bring in liquidity-risk into standard VAR model, in purpose of making a more accurate assessment of the "risk" and "cost" of the financial asset during liquidation. Firstly, I use the average of the conditional samples during the period of liquidation as the pricing value of financial asset to include the "risk" during liquidation into VAR model, and the introduction of market impact function to measure the "cost" of liquidation_the down-falling of the market price due to large scale of liquidation; in order to make a more accurate assessment with much softer assumptions. Secondly, based on the introduction of the market impact function, I solve the problem of how to decide the optimal-liquidation-period_the time of liquidation, which corresponds to the least cost of liquidation. Meanwhile in the experience study, I use the data on stock market to make an assessment of two important parameters γ and η , and look into their fluctuation on different market conditions and their influence on liquidation period T and LVAR and find out although γ and η are quite different under different market condition, the T and LVAR are not very sensitive to their impact .It means that we can use different parameters according to different market condition to insure the accuracy of the result of the LVaR model. Finally I made a compare between the VAR and LVAR of some securities and find out that the LVAR developed in this paper is quite different from the standard VAR as the liquidity risk is included.