• 제목/요약/키워드: Liquidity Measure

검색결과 25건 처리시간 0.03초

Asset Pricing and the Volume Effect

  • Park, Jin-Woo;Dukas, Stephen
    • 재무관리논총
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    • 제2권1호
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    • pp.127-144
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    • 1995
  • Previous literature in financial economics documents the existence of a liquidity premium in expected returns, measured by the bid-ask spread. This study provides a more comprehensive test of the egect of liquidity on common stock returns by including trading volume as an additional liquidity measure. we find that trading volume is a relevant measure of liquidity, and affects expected returns even aher controlling for the effects of systematic risk, firm size, and the relative bid-ask spread. We also find that trading volume complements the bid-ask spread as a liquidity measure, and provides additional information about the liquidity premium. The liquidity effect emerges in non-January months as a volume effect, in addition to the spread effect in January documented by Eleswarapu and Reinganum(1993).

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Liquidity and Skewness Risk in Stock Market: Does Measurement of Liquidity Matter?

  • CHEUATHONGHUA, Massaporn;WATTANATORN, Woraphon;NATHAPHAN, Sarayut
    • 유통과학연구
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    • 제20권12호
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    • pp.81-87
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    • 2022
  • Purpose: This study aims to explore the relationship between stock liquidity and skewness risk-tail risk (stock price crash risk) in an emerging market, in which problems on liquidity are more severe than in developed markets. Research design, data, and methodology: Based on the Thai market stock exchange over the period of 2000 to 2019, our sample include 13,462 firm-period observations. We employ a panel regression models regarding to five liquidity measures. These five liquidity measures cover three dimensions of liquidity namely the volume-based, price-based, and transaction cost-based measures for the liquidity-tail risk relationship. Results: We find a positively significant relationship between stock liquidity and tail risk in all cases. The finding here shows that the higher the stock liquidity, the larger the tail risk is. Conclusion: As the prior studies show inconclusive effect of stock liquidity on stock price crash risk, we demonstrate that mixed results found in prior studies are probably driven from the type of liquidity measure. The stock liquidity-tail risk association is present in the Stock Exchange of Thailand. The results remain the same regardless of the definition of tail risk and liquidity factors. An endogeneity issue is addressed by employing the two-stage least squares regression.

Testing the Liquidity Hypothesis in the Korean Retail Firms

  • Kim, Sang-Su;Lee, Jeong-Hwan
    • 유통과학연구
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    • 제15권5호
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    • pp.29-38
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    • 2017
  • Purpose - Prior theories predict a negative correlation between stock liquidity and dividend payout propensity. We test this hypothesis by examining the sample Korean retail firms. Research design, data, and methodology - We construct four different types of stock liquidity measures and investigate how these stock liquidity variables affect dividend payout propensity by employing the logit regression model. The retail firms listed in the KOSPI and KOSDAQ markets are analyzed from 1990 to 2015. Results - Our estimation results support the liquidity hypothesis if we adopt the stock turnover rate as the stock liquidity measure, particularly for the retail firms listed in the KOSPI markets and for non-conglomerate firms. Yet, our estimation results adopting the illiquidity measure of Amihud (2002), the proportion of non-trading day, and the volume of trading do not support the liquidity hypothesis. Conclusions - Our findings provide mixed results for the validity of stock liquidity hypothesis, which enriches the existing literature. In terms of turnover rate, the stock liquidity hypothesis holds robustly. Yet, we are not able to find any empirical evidence supporting the hypothesis if we use the other three measures of stock liquidity.

국내 주식시장에서 유동성 프리미엄의 장기적 변화에 대한 연구 (Long-term Trend of Liquidity Premium in the Korean Stock Market)

  • 전용호
    • 아태비즈니스연구
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    • 제10권2호
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    • pp.27-41
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    • 2019
  • Following the methodology of Ben-Rephael, Kadan and Wohl (2015), this paper examines whether firm-level liquidity premium exists and whether the premium exhibits a long-term trend in the Korean stock market. The results show that over the whole sample period (1998-2018), a liquidity premium of 0.083% exists in the cross-section of stocks. Interestingly, the pricing of liquidity declines significantly over the sample period. Sub-period analysis indicates that liquidity is priced mainly in the first sub-period (1998-2004) with a significant monthly premium of 0.304%, while the pricing of liquidity becomes weaker or insignificant in the second (2005-2011) and the third (2012-2018) period. I also find that the significance of the liquidity premium in the first period is attributed to small stocks. To explore underlying reasons that might affect the decline in the liquidity premium, I decompose liquidity premium into the product of firm-level liquidity and the sensitivity of expected stock returns on liquidity. The results reveal that the long-term decline is explained by both an increase in firm-level liquidity and a decrease in the sensitivity of expected returns on liquidity.

Liquidity and Solvency Management and its Impact on Financial Performance: Empirical Evidence from Jordan

  • DAHIYAT, Ahmad Abdelrahim;WESHAH, Sulaiman Raji;ALDAHIYAT, Mohammad
    • The Journal of Asian Finance, Economics and Business
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    • 제8권5호
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    • pp.135-141
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    • 2021
  • The study aims to examine the impact of liquidity and solvency management on the financial performance of Jordanian manufacturing companies listed on the Amman Stock Exchange, for a period of 10 years from 2010 to 2019. The size of the company was used as a control variable. The study employs Return on Assets (ROA) and Earnings Per Share (EPS) to measure financial performance. Current ratio (CR) and total debts to total assets were used as proxies for liquidity and solvency management, while logarithm of total assets was used to measure the size. Correlation and multi regression analyses have been applied to analyze the data. The results show a statistically significant impact of independent and control variables (liquidity and solvency management and the size of the company) on financial performance, while the detailed results of the hypotheses indicate that liquidity has an insignificant reverse impact on financial performance. With respect to other variables, there is a significant positive impact of size on performance and a significant negative impact of solvency on performance. The study suggests in light of results, increasing investments in companies' assets by focusing on internal financing, such that large-sized companies with low leverage will have a good performance.

기관투자자의 대량주식보유가 시장유동성에 미치는 영향 (The Effects of Institutional Block Ownership on Market Liquidity)

  • 조경식;정헌용
    • 경영과정보연구
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    • 제33권1호
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    • pp.83-97
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    • 2014
  • 본 연구는 우리나라 기업들을 대상으로 기관투자자의 대량주식보유가 시장유동성에 미치는 영향을 분석하였다. 기관투자자의 대량주식보유는 기관투자자 대량주식보유의 수와 그 보유비율을 사용하였다. 시장유동성은 Amihud(2002)의 비유동성 측정치를 사용하였다. 분석의 결과 첫째, 전체표본을 대상으로 분석한 결과에서, 기관투자자 대량주식보유의 수와 Amihud의 비유동성 측정치 사이에는 유의한 음(-)의 관계가 나타났다. 그러나 기관투자자 대량주식보유의 수를 중심으로 그룹을 세분화하여 분석한 결과, 기관투자자 대량주식보유의 수와 Amihud의 비유동성 측정치 사이에는 일관된 결과가 나타나지 않았다. 이것은 기관투자자 대량주식보유의 수가 시장유동성에 미치는 영향은 단순하지 않는 것을 의미한다. 둘째, 기관투자자 대량주식보유비율 합계와 Amihud의 비유동성 측정치 사이에서, 그룹3(11.71%~17.38%)과 그룹4(7.45%~11.65%)에서 유의한 음(-)의 관계를 보이는 것으로 나타났다. 이러한 결과는 기관투자자의 대량주식보유비율이 그룹3과 그룹4에 속하는 기업에서 시장유동성이 개선됨을 의미한다. 셋째, 기관투자자 대량주식보유의 수와 그 보유비율은 글로벌 금융위기 이전기간과 이후기간 보다는 당해기간(2008)에 더 유의하게 시장유동성에 영향을 미치는 것으로 나타났다.

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The Effect of Liquidity Creation on Bank Capital: A Case Study in Indonesia

  • FUAD, Ahmad;DISMAN, Disman;NUGRAHA, Nugraha;MAYASARI, Mayasari;FUAD, Ahmad
    • The Journal of Asian Finance, Economics and Business
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    • 제8권5호
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    • pp.649-656
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    • 2021
  • This paper aims to examine the moderating role of bank competition on the effect of liquidity creation on bank capital. We measure bank competition using the Lerner index approach, liquidity creation using the Catfat approach, and bank capital using the capital to total asset ratio approach. This test also considers control variables from bank-specific factors such as Return on Assets, Loan to Deposit Ratio, and Non-Performance Loans as well as macroeconomic factors such as Gross Domestic Product, inflation, and Bank Indonesia interest rates. The sampling technique used was purposive sampling. The data sample obtained was 96 banks from a population of 114 banks in Indonesia which consistently operated during the period 2008-2018. Hypothesis testing uses panel data regression analysis techniques through the first model of the Hayes method. The results show that the negative effect of liquidity creation on bank capital depends on competition. We found that bank competition at any level (low, medium, high) negatively moderates (weakens) the effect of liquidity creation on bank capital in all banks. This finding is consistent with the view that banks may strengthen their capital in response to bank competition which may decrease the level of bank liquidity creation.

Redefining Liquidity for Monetary Policy

  • Kim, Kyunghun;Lee, Il Houng;Shim, Won
    • East Asian Economic Review
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    • 제22권3호
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    • pp.307-336
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    • 2018
  • This paper proposes a monetary aggregate "Liquidity" that could serve as a useful indicator for gauging the appropriateness of monetary policy. If liquidity rises above a certain threshold, it is signaling that monetary policy is losing traction due to structural and other impediments even when the inflation gap remains open. This indicator supplements the financial cycle approach but adds value by providing a benchmark that is derived from the national account, and not based on its own trend. Over the last two decades, each time this measure rose above the threshold range, it was followed by a decline in GDP growth. The latter was greater when accompanied by a high physical asset value to GDP, e.g., an elevated property market.

Predicting Stock Liquidity by Using Ensemble Data Mining Methods

  • Bae, Eun Chan;Lee, Kun Chang
    • 한국컴퓨터정보학회논문지
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    • 제21권6호
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    • pp.9-19
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    • 2016
  • In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.

Determinants of Liquidity in Manufacturing Firms

  • VU, Thu Minh Thi;TRUONG, Tu Van;DINH, Dung Thuy
    • The Journal of Asian Finance, Economics and Business
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    • 제7권12호
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    • pp.11-19
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    • 2020
  • This study examines the factors that affect firm's liquidity in manufacturing companies listed in Vietnam. Factors studied include the board size, the board independence, the firm size, the firm age, and its return. We use different metrics to measure firm's solvency status, including the cash ratio, the quick ratio, and the cash conversion cycle. Accordingly, three econometric models are built to test hypotheses proposed by researchers in order to explain the relationship between the five factors above and liquidity's measures. The study used the data set of manufacturing companies listed on the Ho Chi Minh City Stock Exchange in the period from 2015 to 2019. The final sample group comprises 139 firms with 633 observations. The results show that in manufacturing firms, while the cash ratio and the quick ratio are positively associated to the board size, the board independence, and the firm's profitability, the net operating cycle is negatively correlated to the board size, the firm size, the board independence, and the profitability. Therefore, larger firms with larger board size and more independent members can help to improve capital management efficiency.There is no evidence for the relationship between the firm age and solvency measurements, between cash conversion cycle and firm's profitability.