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This research studies assessment and explanation of liquidity risk model at danger using of LaR four models which are fluctuation operator or conditional variance. These four models consist of two econometric groups (GARCH and ARCH) and two risk assessment groups (MA and EWMA). Results of the research indicate this fact that possibility of liquidity and liquidity risk forecasting exist in using of liquidity at risk model (LaR) with historical data of bank liquidity, it also shows that studied subset models in 95% confidence level have appropriate performance for liquidity at risk forecasting using of liquidity at risk model (LAR) and confirms that it is possible to predict econometrics liquidity risk and risk assessment in two ways. Liquidity time series of studied bank have very large fluctuation shocks in spread time even to the extent that bank liquidity is negative in some periods. Garch model as a variation operator can be divided the time series into clusters of multiple parts and decrease sudden shocks in both 95% and 99% confidence level is reliable and as a more efficient model than other measurement models presented its fluctuation in this study

Assessment and Explanation of Bank’s Liquidity Risk Forecasting Model Using of Liquidity at Risk Case Study: Agricultural Bank