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The purpose of this paper is to investigate the impact of discretionary loan loss provisions (DLLPs) and non-performing loans (NPLs) on the liquidity risk of both Islamic banks (IBs) and conventional banks (CBs) before and after the global crisis that hit nations belonging to the Gulf Cooperation Council (GCC).

This empirical study uses balanced panel data on 16 IBs and 58 CBs operating in the six Gulf Cooperation states covering 2000–2014. The data were obtained from the Bankscope database and the banks’ annual reports.

The results indicate that NPLs affect liquidity risk differently across the banks – specifically, there is a significant difference in the funding and managing of liquidity between the two bank types. The authors find that the influence of DLLPs does not vary across the banks in the overall analysis and before the crisis. This finding provides insights into the unique nature of banking risks in dual banking systems. The authors also find that after the crisis, the discretionary LLPs affected liquidity risk differently across the banks.

This study has several practical implications. First, the findings suggest that the Islamic Financial Services Board and other IBs regulators should reassess several regulations, principles and products in order to reduce their credit and liquidity risks. Second, the study emphasizes the need for banks to perform a careful assessment of the effects of their LLP policies. Finally, the findings are also relevant to bankers, as they provide empirical evidence on the effect of loan growth on bank liquidity, suggesting that bankers should improve their loan management.

First, this is the first study to examine discretionary LLPs, NPLs and liquidity risk in IBs; it is also the first comparative study between Islamic and CBs. Second, the study provides evidence on how the global crisis impacted the banking sector and identifies some of the main determinants of liquidity risk for both Islamic and CBs operating in GCC countries.

Basel III and the capital stress testing introduced new requirements and new definitions while retaining the structure of the pre-2010 requirements. The total number of requirements increased, making it difficult to determine which and how many constraints are binding. The purpose of this paper is to discuss the new financial regulations in the post-financial crisis period, focusing on the capital and liquidity regulations.

The authors explore the impact of financial regulations using various data sources – financial and accounting data from Y-9C Reports. Market data such as daily bond trading from TRACE through the Wharton Data Research Services and Treasury yield from the Bloomberg. The authors use regression analysis to examine the roles of capital adequacy and liquidity regulations.

The authors’ analysis in this paper suggest that Basel III, CET1 and Level 1 HQLAs requirements post-financial crisis have reshaped the balance sheets of large financial institutions, with some differential impacts on traditional versus capital markets banks. These changes appear to respond to the binding constraints (CET1 being a preponderance of required regulatory capital, Level 1 HQLAs a majority of required HQLAs and the expense of both) created by these new requirements, which also appear to have constrained asset growth at such institutions. Consistent with the authors’ view, their results suggest that the new requirements are less constraining for large traditional banks (such institutions show a rapid increase in CET1 capital to steady-state levels by 2012 and strong retail deposit rebuilding resulting in a relatively low required HQLA) and much more so, particularly the liquidity requirement, for the capital markets banks (such institutions show continuous building of CET1 capital over the post-crisis observation period, declines in the share of trading assets and increases in the share of HQLAs combined with efforts to increase retail deposits). Credit risk spreads rose dramatically during the financial crisis of 2008-2009. Although decreased, they remain higher and with greater dispersion (for both groups of banks) than pre-crisis. Preliminary regression analysis suggests that the market responds to changes in measured liquidity, rather than the regulatory capital ratios, when pricing bank risk (as reflected on bond spreads).

The estimation is based on historical relationship in the data. We must be cautious in extrapolating the results in a different environment.

There appears to be an arbitrage between HQLA and retail deposits. Capital markets banks and traditional banks follow different business models as evident in the analysis in this paper.

Market pricing suggests that the liquidity measures are more transparent and easier to understand. Capital ratios are not as easy to interpret.

Original research. To the authors’ knowledge, there is no paper that examines impacts of capital and liquidity regulations after the crisis at capital markets banks vs traditional banks – using both accounting data and market data.

The purpose of this study was to examine the 2007-2009 financial crisis to analyze how securitization relates to the Italian bank risk profile, both in terms of credit and liquidity risks.

To test our research hypotheses, we adopt ordered probit models, in which we regress the changes in credit risk and liquidity on a set of regressors, including two securitization dummy variables plus a vector of control variables.

Our results show that the impact of securitization on the originators risk-taking is not uniform. When credit risk is considered, the securitization effects seem to be statistically significant only during the crisis period. However, when we turn to analyze the bank’s liquidity position, our results show that securitization improves it both during the pre-crisis and the crisis years. Our results support the Basel III initiatives aimed to realize a better integration between the different types of risks (i.e. credit and liquidity risks).

The major limitation of our study is related to the analyzed geographic area.

First, our results support the Basel III initiatives aimed to realize a better integration between the different types of risks (i.e. credit and liquidity risks). In general, the broad policy implication of the paper is that in some contexts, such as the Italian market, securitization does not necessarily produce negative effects in terms of bank’s risk.

This study contributes to the empirical literature on the effects of securitization for banks in several ways. First, we consider the complexity of the bank’s risk profile; second, despite the importance of the Italian securitization market, there is a research void on it. Furthermore, unlike previous studies, our analysis covers the period 2000-2009, including the financial crisis years. Finally, to our knowledge, our methodology (ordered probit models) has not been used in the past in this context.

This chapter surveys papers and the related literature on the relationship between banks’ creditor structure and bank risk during the period of liquidity crises. Departing from the conventional banking literature, which points to deteriorating asset quality to be the culprit for the amplified bank risk in the midst of financial crises, the studies in the aftermath of the global financial crisis look into the liability side of the bank balance sheet as a potential source for the augmented bank risk during the financial crisis when there is a liquidity contraction. Recent studies theorize and provide empirical evidence that banking institutions with a greater share of large lenders and an economy with high noncore bank liabilities in the banking sector may experience heightened bank risk or country risk. We also search for policy implications from this survey.

Behavioral finance and market microstructure studies suggest that the investor sentiment and liquidity are related. This paper aims to examine the aggregate sentiment–liquidity relationship in emerging markets (EMs) for both the sample period and crisis period. Then, it verifies this relationship, using the asymmetric sentiment.

This study uses a sample consisting of stocks listed on the SSE Shanghai composite index (348 stocks), the JKSE (118 stocks), the IPC (14 stocks), the RTS (12 stocks), the WSE (106 stocks) and FTSE/JSE Africa (76 stocks). This is for the period ranging from February, 2002 until March, 2021 (230 monthly observations). We use the panel data and apply generalized method-of-moments (GMM) of dynamic panel estimators.

The empirical analysis shows the following results: first, it demonstrates a significant relationship between the aggregate investor sentiment and the stock market liquidity for the sample period and crisis one. Second, referring to the asymmetric sentiment, we have empirically given proof that the market is significantly more liquid in times of the optimistic sentiment than it is in times of the pessimistic sentiment. Third, using panel causality tests, we document a unidirectional causality between the investor sentiment and liquidity in a direct manner through the noise traders and the irrational market makers and also a bidirectional causality in an indirect channel.

The results reported in this paper have implications for regulators and investors in EMs. Firstly, the study informs the regulators that the increases and decreases in the stock market liquidity are related to the investor sentiment, not financial shocks. We empirically evince that the traded value is higher in the crisis. Secondly, we inform insider traders and rational market makers that the persistence of increases in the trading activity in both quiet and turbulent times is associated with investor participants such as noise traders and irrational market makers.

The originality of this work lies in employing the asymmetric sentiment (optimistic/pessimistic) in order to denote the sentiment–liquidity relationship in EMs for the sample period and the 2007–2008 subprime crisis.

The purpose of this paper is to examine the events leading up to the Great Recession, the US Federal Reserve’s response to what it perceived to be a short-term liquidity problem, and the programs it put in place to address liquidity needs from 2007 through the third quarter of 2008.

These programs were designed to channel liquidity to some of the largest institutions, most of which were primary dealers. We describe these programs, examine available evidence regarding their effectiveness and detail which institutions received the largest amounts under each program.

We argue that increasing financial fragility and potential insolvencies in several major institutions were evident prior to the crisis. While it is inherently difficult to disentangle issues of illiquidity from issues of insolvency, failure to recognize and address those insolvency problems delayed necessary adjustments, undermined confidence in the financial system and may have exacerbated the crisis.

Disentangling issues of illiquidity from issues of insolvency is inherently difficult and so it is not possible to specify a definitive counterfactual scenario. Nonetheless, failure to recognize and address the insolvency problems in several major institutions until more than a year after the crisis had begun delayed the necessary adjustment and undermined confidence in the financial system.

This paper is among the first to analyze data showing the amounts of lending and the distribution of these loans across institutions under the Fed’s special liquidity facilities during the first 18 months of the financial crisis.

The purpose of this paper is to explore the determinants of three different types of bank liquidity: funding liquidity, liquidity creation, and stock liquidity in emerging markets.

It uses an extensive set of data from all the listed banks of Brazil, Russia, India, China, and South Africa, collectively known as the BRICS countries, spanning the period 2002-2014. Multiple linear regression has been used to estimate the coefficients of the determinants.

In case of emerging markets, bank size is not a determinant of different types of liquidity, except funding liquidity. Besides, the recent financial crisis had an impact on funding liquidity as well as “cat nonfat” measure of liquidity creation but it did not affect “cat fat” measure and stock liquidity. The variation in funding liquidity is also explained by the profitability and the riskiness of the bank. Effective interest rate, national savings rate, and inflation rate are also the determinants of funding liquidity. Bank-specific determinants of liquidity creation include bank leverage and profitability, and macroeconomic determinants include stock market index, effective interest rate, and unemployment rate. The variation in stock liquidity of the bank is explained by profitability and price of stocks, trading volume, volatility of stock returns, and percentage change in real gross domestic product. Neither market capitalization nor stock market index is the determinant of stock liquidity of the banks.

This study uses the data from publically listed banks only.

The findings of this study may be used by the policy makers and bank managers in the emerging markets to design better policies and to strengthen the banking system to avoid financial turmoil in future.

Most of the existing studies focus on bank liquidity in developed countries and studies aiming on emerging countries are rare. The existing studies focus more on funding liquidity and liquidity creation but to the best of the authors’ knowledge, none of the studies analyze the determinants of banks’ stock liquidity. So, this study bridges the above mentioned gaps by focusing on bank liquidity in emerging markets, and exploring the determinants of the stock liquidity of the banks.

This study aims to investigate the existence of contagion between liquid and illiquid assets in the credit default swap (CDS) market around the recent financial crisis. The authors perform analyses based on vector autoregression model and the dynamic conditional correlation model. The estimation of vector autoregression models reveals that changes in liquid CDS (LCDS) spreads lead to changes in illiquid CDS spreads at least one week ahead during the financial crisis period, whereas the leading direction is reversed during the post-crisis period. Moreover, the results are robust after controlling for structural variables which are proven as determinants of CDS spreads and are empirically supported. This study interprets that information was incorporated first into the LCDSs because of the flight-to-liquidity during the recent crisis period but there is a default contagion effect by reflecting illiquidity-induced credit risk after the crisis. Finally, the dynamic conditional correlation analysis also confirms the main results.

This chapter aims to examine the position of the banking system and the effect of the COVID-19 pandemic on bank liquidity in six Western Balkan Countries. We aim to analyse the current financial parameters of the banking system to determine the impact of the pandemic’s various risks on the banking liquidity stability in response to the capital reserves of central banks of the respective countries. This chapter deals with cross-country comparison analysis of how the government responded including fiscal stimulus packages to prevent the financial downturn and the impact on liquidity retention. The methodology is based on a comparative data analysis using primary and secondary sources. Although it is too early to have full evidence of the depth of the pandemic impact, the findings show that because of the immediate actions undertaken by the liquidity management of each country and also as a result of the favourable liquidity position before the pandemic Crisis, the banking sector had sufficient reserves to overcome the risk of crisis. Moreover, all six Balkan Countries have adapted the regulatory framework in line with international emergency measures to maintain financial stability. The measures and instruments implemented by countries have generally complied with the Basel Committee’s instructions. The measures and instruments implemented by countries have generally complied with the Basel Committee’s instructions.

The purpose of this paper is to examine market microstructure differences in stock market quality for hospitality real estate investment trusts (REITs) during the pre- and post-financial crisis eras. It provides insight on different trading strategies based on the underlying liquidity and volatility of hospitality REITs as compared traditional REITs and the broader market.

The paper uses established microstructure measures for liquidity, trading volumes and risk assessment and compares daily and intraday trading patterns of REITs, hospitality REITs and the broad market.

The results suggest a quicker recovery of performance for hospitality REITs and some fundamental increases in liquidity measures post-crisis. The results of the study highlight the differences in trading volumes, liquidity and risk profile of hospitality REITs compared to traditional REITs both in the pre- and post-financial crisis periods.

The quicker recovery of hospitality REITs in key trading measures may suggest flight to quality during periods of high volatility.

This study fills the gap in the literature relative to microstructure studies and provides information to help hotel firms and portfolio managers choose an appropriate organizational structure and investment vehicle, respectively.