Abstract
The factors that affect liquidity risk management of Islamic banks in Malaysia are studied in this chapter by assessing the short-term and long-term determinants of these banks’ liquidity holdings. Monthly data is employed over the period of 2007–2015 based on the Autoregressive Distributed Lag (ARDL) model that incorporates Sukuk, interbank market rate, required reserves, inflation rate, and credit default swap rate. The ARDL cointegration test reveals that total assets, deposits, inflation, government bonds, capital adequacy, and interbank interest rate show positive significant relations with liquidity. However, it is found that the CDS rate of the country, statutory reserves, and Sukuk stocks show negative significant relations with the liquidity. These results are consistent with previous studies’ findings. Furthermore, the Granger causality tests reveal that Malaysian Islamic banks’ liquidity is related to interbank rate which signs that the change in government bond rate has causal effect on liquidity of Islamic banks. Moreover, total assets are related to liquidity and deposits, CDS, required reserves, and capital. As well as total assets, liquidity has causal effect on credit, deposit, CDS, and interbank rate. The main result is that market liquidity influences banks’ liquidity, and banks’ liquidity responds to the profitability of Islamic banks. Granger analysis and impulse response analysis show that these banks’ liquidity management has a direct causal relation with market liquidity and indirect causal relation with funding liquidity.
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Notes
- 1.
See the document of the BIS, “Basel III: the net stable funding ratio” (http://www.bis.org/bcbs/publ/d295.htm).
- 2.
The IILM was established to facilitate cross-border liquidity management among Islamic financial institutions by making available a variety of instruments of acceptable features and characteristics. However, the IILM instruments have not reached a sustainable critical mass due to its infancy.
- 3.
- 4.
Cagamas Sukuk are issued by the National Mortgage Corporation of Malaysia (Cagamas) to fund the purchase of Islamic home financing from the financial system. https://www.cagamas.com.my/cagamas-debt-securities/sukuk.
- 5.
The Bloomberg Professional service (Bloomberg Terminal) is a software solution and flexible platform for financial professionals, academicians, and public authorities who need real-time data, news, and information. For more information, please see http://www.bloomberg.com.
- 6.
We used EV (which is a statistical, forecasting, and modelling tool with a simple object-oriented interface) and Stata 14 statistical package (Stata is a general-purpose data analysis and statistical software package used by researchers and professionals. It is a complete, integrated statistics package that provides a broad range of statistical analyses, plus data management, graphics, simulations, and custom programming. For more information, please see http://www.stata.com).
- 7.
Vector Decomposition (VDC) test results for liquidity of Malaysian Islamic banks are shared at Appendix 13.
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Dolgun, M.H., Ng, A. (2019). Liquidity Risk Management in Islamic Banks: Evidences from Malaysia. In: Zulkhibri, M., Abdul Manap, T., Muneeza, A. (eds) Islamic Monetary Economics and Institutions. Springer, Cham. https://doi.org/10.1007/978-3-030-24005-9_10
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