English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper, balance sheet liquidity data was analyzed comprising of 157 Class I and 234 Class II banks. Class I banks are categorized as those with tier 1 capital in excess of $4 billion and internationally active while Class II banks are the rest. A Cointegrated Vector Autoregressive (CVAR) approach was used on balance sheet liquidity data to ascertain the behavior of variables in relation to bank failure. The study also demonstrated the nature of each of the variables containing estimated Basel III and Traditional liquidity measures for Class I and II banks. The estimated Basel III liquidity standards were made up of the Liquidity Coverage Ratio (LCR) and the Net Stable Funding Ratio (NSFR) while the liquidity measures involved Government Securities Ratio (GSR) and Brokered Deposit Ratio (BDR). Results showed that a response of Net Stable Funding Ratio to a shock in Liquidity Coverage Ratio decreased in the first quarter and a steady continuous increase in the next quarters was observed. A shock on the Liquidity Coverage Ratio therefore would cause banks to increase their level of Net Stable Funding Ratio. This explains why the Liquidity Coverage Ratio is considered for a short term stress period of 30 calender days while the Net Stable Funding Ratio will be considered for a longer stress period of 1 year when fully implemented by banks.

Analysis of bank failure: An application of CVAR methodology on liquidity