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Modeling the Liquidity Gap in a Private Bank

Author

Listed:
  • Sadeghzadeh Yazdi , Ali

    (Semnan University)

  • Abounoori , Esmaiel

    (Semnan University)

  • Erfani , Alireza

    (Semnan University)

Abstract

The present study suggests a model for predicting liquidity gap, based on source and cost of funds approach concerning the daily time series data (25 March 2009 to 19 March 2018), in order to control and manage the liquidity risk. Using the family of autoregressive conditional heteroscedasticity models, the behavior of bank liquidity gap is modeled and predicted. The results show that the APGARCH with the Johnson-SU distribution is the most suitable model for explaining the liquidity gap behavior. Based on the rolling window method the more accurate model has been selected to be the APGARCH model with T-Student distribution which provides the least error in forecasting liquidity gap.

Suggested Citation

  • Sadeghzadeh Yazdi , Ali & Abounoori , Esmaiel & Erfani , Alireza, 2018. "Modeling the Liquidity Gap in a Private Bank," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(2), pages 153-176, April.
    • Handle: RePEc:mbr:jmonec:v:13:y:2018:i:2:p:153-176
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    References listed on IDEAS

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    Cited by:

    1. Marcjasz, Grzegorz & Narajewski, Michał & Weron, Rafał & Ziel, Florian, 2023. "Distributional neural networks for electricity price forecasting," Energy Economics, Elsevier, vol. 125(C).

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    More about this item

    Keywords

    Liquidity Forecast; Liquidity Risk; GARCH Family; Rolling Window;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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