trading ratio
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2020 ◽  
Vol 13 (11) ◽  
pp. 279
Author(s):  
Harsimran Sandhu ◽  
Kousik Guhathakurta

In this paper, we establish the significance and effects of initial public offer (IPO) offer price ranges on subscription, initial trading, and post-IPO ownership structures. The primary market in India provides a unique setting for estimating the effect of various initial public offer (IPO) price ranges and IPO issue factors on the initial demand for an IPO among investors, measured by full IPO subscription/oversubscription, initial turnover (liquidity), and the post-IPO listing ownership structure among investors (ownership). For the IPO pre-listing stage, this study uses firth logistic regression to estimate the effect of various IPO offer price ranges (low to high) and various IPO issue factors on the full subscription/oversubscription of an IPO in each investor category. For the post-IPO listing stage, the study uses OLS regression to estimate the effect of various IPO offer price ranges (low to high) and various IPO issue factors on the initial trading ratio (IPO listing day trading) and the ownership percentage between institutional and individual investors. We find that all investor categories show a lesser likelihood for full subscription or oversubscription of an IPO issue at the lowest range of IPO offer prices. At the post-listing stage, the results indicate a diverse IPO offer price range in which individuals and institutions maximize their respective ownership holdings after the IPO listing. The results further show that lower promoter holdings diffuse higher ownership among individual shareholders by targeting lower IPO offer prices, thus increasing control.


Author(s):  
Najla Ibrahim Abdulrahman, Tahani Ewaed Alfarsi

This study aimed to identify the impact of liquidity on the profitability of commercial banks in Saudi Arabia during the period 2010 to 2019. The study was based on the descriptive analytical approach where this approach is based on data collection, description and analysis, by analyzing the financial statements of the sample banks study that will be obtained from a trading site, and then using the appropriate statistical method of data analysis based on SPSS, in order to identify the impact of liquidity on profitability. The study showed that there was a statistically significant effect at the level of liquidity (0.05) on the return on equity, while there was no effect of liquidity (trading ratio) on the return on assets. The study recommended: Saudi commercial banks should focus on aligning liquidity with profitability. to avoid falling into a financial deficit. It also needs to focus on profitability, which demonstrates the bank's ability to make profits. In addition to paying more attention to liquidity because of its impact on profitability, commercial banks also have appropriate policies to better manage their liquidity, while working to achieve profitability. Finally, work on more studies and research which are more widely available to include all banks in Saudi Arabia. Finally, some semi-liquid investments need to be maintained to ensure that there is no future liquidity crisis.


2020 ◽  
Vol 49 (3) ◽  
pp. 375-413
Author(s):  
Taekyung Kim ◽  
Shiyong Yoo

This study analyzes the direct and indirect effects of air pollution on the return and volatility of the KOSPI index through the trading ratio by investor type. The main results are as follows. First, air pollutants have a direct effect on volatility; coarse particulate matter (PM10) and fine particulate matter (PM2.5) have a negative effect on volatility. Second, air pollutants have a significant effect on the trading ratio by investor type; as the concentration of fine particulate matter (PM2.5) increases, the trading ratio of institutionals and those of foreigners decrease. Third, the effect of cumulative exposure of air pollutants on stock return and volatility is greater than that of daily exposure. Although there is no effect on daily exposure to air pollution, stock return decreases during cumulative exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and carbon monoxide (CO). The volatility changes significantly with cumulative exposure compared to daily exposure to coarse particulate matter (PM10), fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2) and sulfur dioxide (SO2). Fourth, air pollutants have an indirect effect on stock return and volatility through trading ratio by institutional and foreign investors. In particular, the effect of air pollution through the foreign investors’ trading ratio is a remarkable result revealed in this study.


Author(s):  
Shihabeldeen Mohamed Ahmed

    The study aimed to identify the indicators of liquidity. And their contribution to the construction of a model to determine the price of the market share in Sudan, to highlight the importance of profit indicators in determining the share price of the market, and to identify indicators of indebtedness and the extent of their contribution in determining the share price of the market. The problem of the study was the extent to which liquidity indicators contributed to determining the market price of the stock, and whether the profit indices contribute to determining the share price of the market. Do indicators of indebtedness contribute to determining the market price of the stock? For the purpose of achieving the objectives of the study and finding solutions to the problems of the study, the researcher tested the following hypotheses; first, there is a statistically significant relationship between liquidity indicators and market price. Second, there is a statistically significant relationship between the indices of profitability and market price; third, there is a statistically significant relationship between the indicators of activity and the price of the market share. To test these hypotheses, the study relied on the historical approach, descriptive analytical approach, and the method of deductive approach. The results of the study showed a positive correlation between (65.61%) and the independent variable in the simple regression method (trading ratio) at an error coefficient of 0.0045, (0.008954), the absence of a relationship between the dependent study variable (market share price) and the associated independent variables (in percentages of the debt) , At an error coefficient of (0.150625). The study recommended recommendations such as adopting the proposed applied study models to analyze the trading ratio, adopting the proposed applied study models to analyze profitability ratios, adopting the proposed applied study models to analyze the ratio of total debt to equity    


2011 ◽  
Vol 54 (5) ◽  
pp. 1599-1614 ◽  
Author(s):  
M. Lee ◽  
K. R. Douglas-Mankin

2008 ◽  
Vol 58 (1) ◽  
pp. 103-108 ◽  
Author(s):  
H. X. Zhang

An innovative approach for total maximum daily load (TMDL) allocation and implementation is the watershed-based pollutant trading. Given the inherent scientific uncertainty for the tradeoffs between point and nonpoint sources, setting of trading ratios can be a contentious issue and was already listed as an obstacle by several pollutant trading programs. One of the fundamental reasons that a trading ratio is often set higher (e.g. greater than 2) is to allow for uncertainty in the level of control needed to attain water quality standards, and to provide a buffer in case traded reductions are less effective than expected. However, most of the available studies did not provide an approach to explicitly address the determination of trading ratio. Uncertainty analysis has rarely been linked to determination of trading ratio. This paper presents a practical methodology in estimating “equivalent trading ratio (ETR)” and links uncertainty analysis with trading ratio determination from TMDL allocation process. Determination of ETR can provide a preliminary evaluation of “tradeoffs” between various combination of point and nonpoint source control strategies on ambient water quality improvement. A greater portion of NPS load reduction in overall TMDL load reduction generally correlates with greater uncertainty and thus requires greater trading ratio. The rigorous quantification of trading ratio will enhance the scientific basis and thus public perception for more informed decision in overall watershed-based pollutant trading program.


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