Liquidity Risk Measures Research Articles

LIQUIDITY RISK, INCOME DIVERSIFICATION, AND BANK FINANCIAL PERFORMANCE

Banking industry must have healthy financial performance in order to function properly as an intermediary organization between those who have capital and those who need it. Intense competition between banks, the emergence of the covid-19 pandemic and declining bank profits have forced banks to be more careful in managing risks and diversifying their income. This study aims to see the effect of liquidity risk and income diversification on banking financial performance. The research data comes from 36 listed companies on the Indonesian Stock Exchange (IDX) or with 108 observations of banking companies for the period 2019 - 2021. The dependent variable of this study is financial performance proxied by ROA (Return-on-Assets). Liquidity risk and income diversification are dependent variables. LDR (Loan-to-Deposit Ratio) is used to measure liquidity risk. Three ratios namely NII (Non- Interest-Income/Gross-Revenue-ratio), NII1 (Fee & Commission-Income/Revenue-ratio) and NIITA (Non-Interest-Income/Total-Assets-ratio) are used to measured income diversification. This study uses multiple regression analysis of panel data. The results of the study show that liquidity risk has a positive effect on bank financial performance. NII1 (Fee & Commission-Income/Revenue-ratio) has significant positive results on financial performance while the NII (Non-Interest-Income/Gross-Revenue-ratio) and NIITA (Non-Interest-Income/Total-Assets-ratio) do not have effect on financial performance of the bank.

Asymmetric liquidity risk and currency returns before and during COVID-19 pandemic

Motivated by the asymmetric nature of liquidity and currency return, we set out a new liquidity-adjusted extreme risk asset pricing model. Our model estimates asymmetric risk using downside beta, downside co-skewness, and excess co-kurtosis. The empirical finding strongly supports the extreme liquidity risk measures to explain the carry trade. Thus confirming that to capture better the extreme risk exposure in liquidity and currency return, it is necessary to highlight asymmetries across up and down markets using downside co-skewness and excess kurtosis. Further, we found their effect to be more pronounced during the COVID-19 period. Therefore, ignoring these exposures, especially during crises, will lead to risk and return profile, deviating from its true nature.

LIQUIDITY RISK AND PERFORMANCE OF NON-FINANCIAL FIRMS LISTED ON THE NIGERIAN STOCK EXCHANGE

This study has examined the effect of liquidity risk on performance of non-financial firms listed on the Nigerian Stock Exchange. The main objective was to assess the degree of influence liquidity risk measured by (standard deviation of quick ratio and current ratio) have on performance (return on assets) of the non-financial firms in Nigeria. Data from all the 87 non-financial firms listed on NSE were extracted through financial reports and analyzed using descriptive statistics, correlation and regression through STATA version 16. The findings revealed that current ratio have negative and significant effect on performance, while the quick ratio was not significant in influencing performance. The result implies that an increase in liquidity risk (difficulty in running the operations and offsetting short term maturing obligations), leads to a significant decrease in performance of the firms. The result also confirms that the standard deviation of current ratio provides better measurement of liquidity risk. It was however concluded that, liquidity risk has negative and significant effect on performance of firms in Nigeria. The study recommends that more attention should be given to liquidity management to minimize the risk of insolvency or bankruptcy of firms in Nigeria as such will help in reducing liquidity risk issues and improve performance of the non[1]financial firms in Nigeria.

Research on the Corporate Bond Risk Factors

The global bond market is greater than the global equity market meanwhile it grows gradually in recent years. Issuing corporate bonds is an ideal channel for enterprises to raise funds in the course of COVID-19 and also provides resilience in the market. Moody's, Standard & Poor's and Fitch are well-known global credit rating agencies and suggest investors purchasing investment-grade bonds for reasonable risks and returns. But local credit rating agencies have limited capacities to appraise local bonds. In the COVID-19 crisis, widen yield spreads represent likelihood of default which can be a measure of credit risk. Besides, government interventions (i.e., Quantitative Easing Program) can effectively eliminate credit risks and Confucian culture is a factor in assessing credit risks of corporate bonds. As for liquidity risk, Chinese bond market is less liquid than the US bond market and financial bonds are the most liquid in the Chinese market. The liquidity risk is caused by inaccurate information and market risk tolerance whereas market risk tolerance integrates credit and liquidity, the main measurement of liquidity risk is transaction cost which means that higher transaction cost can impede liquidity in the bond market. Finally, market risk comprises of COVID-19 pandemic, market design and biodiversity risk. The epidemic tightens the financial condition of developing countries and depreciates the currency of the bond market which raises term structure of interest rate up. A well-designed financial market system can help stabilize fluctuations during financial crisis. Besides, biodiversity risk is relevant to the operation apartment of companies.

Effect of Liquidity Risk on the Financial Performance of Quoted Deposit Money Banks in Nigeria

This study examines the effect of liquidity risk on the financial performance of quoted deposit money banks in Nigeria. The ratio of loans and advances to total assets and the ratio of loans and advances to total deposits were used to measure liquidity risk, while Return on Assets (ROA) was used to measure financial performance. Data were collected from the annual financial reports of each of the deposit money banks. The study utilized panel regression to analyse the data from a sample of eleven (11) quoted deposit money banks on the Nigerian Exchange Group from 2014- 2021. The results of the panel regression revealed that the loans and advances to total assets and loans and advances to deposit have a significant effect on the performance of the quoted deposit money banks in Nigeria. The study recommends that quoted deposit money banks management should diversify their loan portfolio to reduce concentration risk. By diversifying the loan portfolio, banks can spread the risk and reduce the impact of defaults on their performance. The current loans to deposit of 65% ordered by the Central Bank of Nigeria should be sustained. However, bank management should manage their deposit growth to ensure that they have sufficient funds to support their loan and advance activities. This can be achieved by setting appropriate deposit rates.

Corporate Liquidity in Coronacrisis: Experience of Serbian Economy

The appearance of coronavirus in the spring of 2020 has significantly revalued risk exposures in the business environment, which required new approaches in the measurement of financial risks. This paper defines and explains a new approach to the measurement of liquidity risk in companies in a time of an economic crisis. This approach is more responsive to stressful circumstances in the business environment and measures the time in an economic crisis when a company can still pay maturing liabilities out of its own inventory of liquid assets, where sales of a company on the market are limited or completely prohibited, as this was the case for some industries during the first wave of Covid -19 in spring 2020. The objective of this paper was to define a new metric for the measurement of corporate liquidity, which is sensitive to this environment and shows the propensity of a company to the risk of illiquidity if an economic crisis appears. This paper, in the next step, leverages the newly defined metric of corporate liquidity and calculates the average liquidity of all companies, as well as the average liquidity by business sectors in the Serbian economy, to discuss corporate liquidity in a crisis. The results show that the average liquidity of the Serbian economy in crisis at the end of 3Q 2020 was 78,02 days, i.e., the average company in the Serbian economy was able to survive 78,02 days in stress by the end of 3Q 2020 if its sales on the market were prohibited. Implications for Central European audience: The model in this paper is in the interest of every company and bank to measure the liquidity risk of business partners in times of an economic crisis and to predict which business partners may have liquidity problems in crisis and may therefore not be able to pay their open liabilities. The contribution of this paper to liquidity risk measurement in companies in times of stress is high as the currently available literature does not offer an alternative approach.

Rentabilidad y riesgo de liquidez con índices basados en capital flotante en la Bolsa de Valores de Chile

Introduction/objective: This paper explored the relationship between liquidity risk and stock returns in the Chilean stock market, using three measures of liquidity risk widely used in other research and three measures to which the free float variable is added. Methodology: The analysis is performed using panel data regression for the period 2010-2019, the sample considers 46 Chilean companies with a total of 5,509 monthly observations. Results: These show a relationship between profitability and liquidity risk, but only for two of the measures used. Liquidity risk measures based on free float do not show results in this line. Conclusions: This work is another indication that financial risks are difficult to classify in a specific model and liquidity risk is no exception. All the previous evidence, as well as this research, indicates that liquidity risk can be measured and captured by different indices and models.

A Multistage Stochastic Programming Model with Multiple Objectives for the Optimal Issuance of Corporate Bonds

Large corporations usually cover their capital and operating expenses by issuing bonds with fixed rates and different maturities. This paper proposes a multistage stochastic programming (MSP) model with multiple objectives to optimize bond issuance by satisfying the three common objectives of corporate managers, as follows: (i) Minimizing expected discounted cost under cash liquidity and financial leverage risk constraints. (ii) Minimizing financial leverage risk under expected discounted cost and cash liquidity risk constraints. (iii) Minimizing cash liquidity risk under expected discounted cost and financial leverage risk constraints. We measure liquidity risk as conditional payment‐at‐risk (CPaR), according to the corporation’s financial characteristics. Financial leverage risk is captured by conditional financial leverage‐at‐risk (CFLaR), which we design based on conditional value‐at‐risk (CVaR). Through empirical analysis of a company in China, we explore the efficient frontier curves for the three above objectives and provide the corresponding issuance compositions of an optimal bond portfolio. Our MSP model offers guidance for corporations on achieving a trade‐off between cost and risk when issuing corporate bonds.

Liquidity risk and regulation in the Organization of the Islamic Cooperation (OIC) banking industry

The recurring crises have evidenced poor liquidity risk management and ineffective regulation in banking. Consequently, banking regulations have undergone continuous reforms to bolster stability in the banking system. Nonetheless, theoretical and empirical evidence provide conflicting results that warrant comprehensive research, particularly for emerging Islamic banking. This study examines the role of banking regulation on the liquidity risk of 245 conventional banks and 68 Islamic banks from selected 14 Organization of the Islamic Cooperation (OIC) from 2000 to 2017 utilising the dynamic panel GMM (generalized method of moments) technique. We measure liquidity risk using the Net Stable Funding Ratio (NSFR) and the total financing-to-total deposits and short-term funding (LDEP). Meanwhile, the regulatory measures are asset restriction (AR), private monitoring (PM), supervisory power (SP) and capital requirements (CR). The findings suggest that regulation has a limited impact on bank liquidity risk. The CR supports the value creation of regulation through the reduction in banks’ liquidity risks, while PM and SP are agency costs of regulation that lead to higher liquidity risks. The impact of CR is lower on liquidity risk in Islamic banking than conventional ones, probably due to limited Islamic liquidity risk management facilities. Thus, regulators should strengthen Islamic liquidity risk instruments and markets to facilitate Islamic banking growth.

Liquidity Risk and Asset Pricing in Pakistan Stock Exchange

This paper empirically investigates the impact of liquidity risk on stock returns in Pakistan and determines investors’ attitude under bull and bear market conditions. Specifically, the liquidity adjusted capital asset pricing model(CAPM) is modified by including the interaction between the liquidity risk and the indicators of bull- and bear-market periods to investigate whether the pricing of liquidity risk differs in both upward and downward market trends. The analysis is carried out for a large panel of Pakistani manufacturing firms listed at the Pakistan Stock Exchange for the period January 2000 – December 2015. We use alternative liquidity risk measures to check the robustness of the liquidity risk effect. We observe that higher liquidity risk yields higher excess stock returns, implying pricing of liquidity risk during the examined period. The results also reveal that the liquidity risk is positively and significantly related to excess returns in the high-liquidity-risk beta portfolios, whereas it is negatively or insignificantly related to excess returns of low-liquidity-risk beta portfolios. The results also provide evidence that stocks affected by liquidity risk yield positive expected returns in both bull and bear market conditions. However, we find significant differences in the pricing of liquidity risk under upward and downward market trends. The robustness check confirms that the findings on the pricing of liquidity risk are not driven by any specific measure of liquidity.

Analisis Faktor – Faktor yang Mempengaruhi Risiko Likuiditas

Liquidity risk is the ability of a bank to fulfill a predetermined obligation at maturity. Measurement of liquidity risk can be seen in the short and long term through: DER, FDR, Inflation, NPF. The data used are secondary data based on observations of the liquidity risk of Islamic banks and conventional banks from 2007 to 2016. Data collection is also obtained from the Sharia Banking Statistics Report published by the Financial Services Authority and Bank Indonesia. Descriptive research methods and data analysis techniques using multiple regression analysis model) with the ECM (Error Correction Model) approach. Overall, both the short and long term DER variables on Liquidity Risk show a significant relationship, as well as the FDR variable on Liquidity Risk shows a significant relationship, the inflation variable on liquidity risk shows a significant relationship, the NPF variable on liquidity risk in the short term it shows no significant relationship, on the other hand, the NPF variable on liquidity risk in the long term shows a significant relationship

LIQUIDITY RISK AND STOCK RETURN IN LATIN AMERICAN EMERGING MARKETS

This study analyzes the impact of liquidity risk on stock returns in four Latin American markets (Chile, Columbia, Mexico, and Peru) between January 1998 and July 2018. Several previous studies have focused on measuring this effect in developed markets and a few in emerging markets, such as Latin American stock markets. In the present study, five liquidity risk measures with a multiple regression model; three have been widely used in previous studies and two were from recently proposed measures. We found evidence of an inverse relationship between liquidity risk and stock performance, which indicates that there exist rewards for investing in less liquid positions and therefore originate new investment strategies. In general, lesser developed or smaller markets have a disadvantage for this type of study, due to lack of access to historical information on stock purchase and sales.

How Efficient Are Indian Banks in Managing the Risk-Return Trade-Off? An Empirical Analysis

Risk taking is an inherent element of the banking business. Banks make conscious decisions regarding risk taking as they expect to make more return if they take more risk. The primary objective of this study is to empirically investigate the efficiency of Indian banks in generating return relative to the risk they take. If the efficiency measurement is not adjusted for different risk preferences, then a bank earning lower return at lower risk may be misclassified as less efficient compared to peers earning the same level of return, but operating at a higher level of risk. This paper uses measures of liquidity risk, credit risk, market risk, and insolvency risk to develop a risk-return stochastic frontier in order to examine the risk efficiency of banks, a novel attempt in the Indian context. The paper further analyzes the efficiency of banks with respect to bank specific characteristics and risk management regimes. The models are estimated using data from a sample of 47 major banks for the period 2009–2018. The study reveals that Indian banks, on average, exhibited lower efficiency in trading risk against return during the sample period.

Analisis Faktor-Faktor yang Memengaruhi Risiko Likuiditas pada Bank Umum Syariah di Indonesia

This research was conducted to analyze what factors affecting the liquidity risk in Islamic Banks in Indonesia. In this study, the measurement of liquidity risk will be seen from other factors that can affects liquidity risk including Cash Ratio (CsR), Size of Bank (SOB), Third Party Funds (DPK), Capital Adequacy Ratio (CAR), Net Working Capital (NWC), and Investment (INV). The research method used in this research is a quantitative descriptive analysis uses the Eviews 9 program. The object of this analysis is twelve Islamic Banks in Indonesia which have been operating from 2014-2018. The analysis technique used is multiple regression analysis with Random Effect Model (REM) regression model. The results of this study indicate that CsR, SOB, and NWC have a significant effect on liquidity risk. While DPK, CAR, and INV have an insignificant effect on liquidity risk.

Funding Liquidity Risk and the Dynamics of Hedge Fund Lockups

AbstractWe exploit the expiring nature of hedge fund lockups to create a new measure of funding liquidity risk that varies within funds. We find that hedge funds with lower funding risk generate higher returns, and this effect is driven by their increased exposure to equity-mispricing anomalies. Our results are robust to a variety of sampling criteria, variable definitions, and control variables. Further, we address endogeneity concerns in various ways, including a placebo approach and regression discontinuity design. Collectively, our results support a causal link between funding risk and the ability of managers to engage in risky arbitrage.

Application of Exogenous Liquidity Risk Models to Analyze Single Assets

Exogenous liquidity risk measurement is a measurement of liquidity risk that affects all market participants and is not affected by the actions of any other actors. Exogenous liquidity risk measurement is usually called the Cost of Liquidity (COL). The main problem is how the level of liquidity of one currency against other currencies and the effect of liquidity risk on VaR (Value at Risk) on a single asset. This thesis examines the importance of liquidity risk on a single asset. Combining basic VaR and liquidity risk will result in more effective calculations. The model used is to add the basic VaR value with the Cost of Liquidity (COL) or also called Liquidity VaR (L-VaR). The calculation results show the different effects of liquidity for each country's currency. Indonesian Rupiah (IDR) is the currency that has the highest liquidity component compared to the Japanese Yen (JPY) and the Thai Baht (THB). The lower the liquidity component of a currency, the currency is very liquid, and the Japanese Yen (JPY) is the most liquid currency compared to the Indonesian Rupiah (IDR) and the Thai Baht (THB).

Liquidity risk in the Saudi banking system: Is there any Islamic banking specificity?

This paper examines the liquidity risk of Islamic and conventional banks (referred to as IBs and CBs, respectively) by looking at the impact of bank-specific variables on three complementary liquidity risk measures in the Saudi banking system, in which both types of banks operate. Applying the least squares dummy variable corrected (LSDVC) approach over the period from the first quarter of 2008 to the second quarter of 2018, our analysis suggests that the liquidity risk indicators for IBs have been affected in a different way to those of CBs: (i) Using the financing-to-deposits indicator, larger IBs typically have on average a narrower funding gap than smaller ones. The largest CBs, meanwhile, have more vulnerable funding structures than the largest IBs. Islamic and CBs that are more oriented toward traditional intermediation activities have a wider funding gap. (ii) In terms of the interbank ratio indicator, IBs with stronger capital may need to rely more on interbank funding and may be more likely to be net borrowers than the less-capitalized IBs. CBs that can secure more net interest income tend to have better liquidity positions than IBs. (iii) In terms of the liquidity-ratio indicator, IBs with stronger capital tend to hold less liquid assets as a proportion of their short-term liabilities than smaller ones. Moreover, we show an opposing behavior for the two types of banks for capital ratio and ROA. If CBs are better capitalized and realizing more revenue on assets, they tend to have a greater liquidity ratio than IBs with the same characteristics.

Liquidity and volatility in the U.S. Treasury market

We model the joint dynamics of intraday liquidity, volume, and volatility in the U.S. Treasury market, especially through the 2007–09 financial crisis and around important economic announcements. Using various specifications based on Bauwens and Giot (2000)’s Log-ACD(1,1) model, we find that liquidity, volume, and volatility are highly persistent, with volatility having a lower short-term persistence than the other two. Market liquidity and volume are important to explaining volatility dynamics but not vice versa. In addition, market dynamics change during the financial crisis, with all variables exhibiting increased responsiveness to their most recent realizations. Our models also reveal different market dynamics around announcements. Finally, we introduce new measures of liquidity risk that are useful for continually monitoring liquidity conditions and the risk of liquidity stress in the market.

Assessment of liquidity risk management in Islamic and conventional banks - an empirical study

The aim of this study was to assess liquidity risk management (LRM) practices in Jordanian Islamic and conventional banks during the period (2013-2017). Data used were comprised from six banks, which consisted of three Islamic and three conventional banks in Jordan. Data from the banks financial annual reports covering from 2013-2017 were used to calculate the ratios used as a substitute for liquidity risk in conventional banking as well as Islamic banking in Jordan. The study found the relationship of the size of financial institution, return on asset, return on equity, and capital adequacy ratio with liquidity risk measurement is positive and important both in Islamic banks and conventional banks. Researchers found the practices of LRM are not optimal, yet were based on some considerations explained in this study. Further, progressive actions needs to be taken by the regulators and the banking players to improve the LRM practices.

The impact of liquidity risk on bank profitability: some empirical evidence from the European banks following the introduction of Basel III regulations

Research Question: The study investigates the impact of liquidity on bank profitability following implementation of the Basel III regulations. Motivation: The theoretical framework of the paper draws upon previous research (Athanasoglou et al., 2008; Arif & Nauman Anees, 2012 and Dietrich et al., 2014) and assumes liquidity ratios to have a varying influence on bank profitability, depending upon a bank's specific and macroeconomic indicators. Idea: This study considers multiple proxies of bank liquidity, including Liquidity Coverage Ratio, a new measure inspired by the Basel III framework, and Loan-to-deposit and Financing gap ratio. Alongside traditionally-applied profitability measures, Earnings before Taxes, Depreciation and Amortisation are assumed to be alternative proxies. Data: In the study, a data set of 45 European banks with 180 observations during 2014-2017 and 37 observations for 2018 has been analysed. Tools: The study proposes a quantitative model based upon Ordinary Least Squires techniques complemented by Weighted Least Squares regressions analysis. Findings: The alternative liquidity risk measures have a significant and positive impact only on some profitability proxies, and an insignificant effect on others. The Basel III liquidity measure, LCR, was an insignificant contributor to all return proxies, which requires further investigation. The results also indicate that an increase in bank size and net provision for loan losses decreases profitability proxies. We also found mixed results concerning the effects of deposits and securities gains and losses on bank profits, and provided possible explanation.