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

  •  Mirfeiz Falah Shams    
  •  Hamidreza Kordlouie    
  •  Mohsen Bandeh    
  •  Nader Naghshineh    


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.

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