scholarly journals Making cents of your energy dollar. Volume 2. Technical materials and references

1979 ◽  
Keyword(s):  
Dollar Volume

scholarly journals The impact of earnings management on market liquidity

2020 ◽  
Vol 17 (2) ◽  
pp. 389-396
Author(s):  
Do Thi Van Trang ◽  
Dinh Hong Linh
Keyword(s):  
Earnings Management ◽  
Stock Returns ◽  
Stock Price ◽  
Stock Exchange ◽  
Fixed Effect Model ◽  
Market Liquidity ◽  
Listed Firms ◽  
Daily Stock Returns ◽  
The Impact ◽  
Dollar Volume

This article investigates the impact of earnings management on market liquidity measured by the depth of the market. Managers have desired to provide amazing performance of companies, manage their earnings through non-discretionary accruals. Consequently, investors have trouble evaluating the stock value and misunderstanding of the market liquidity because of manipulated information.To this aim, the fixed-effect model (FEM) is implemented to analyze the financial information of 170 listed firms on the Vietnam Stock Exchange over the period 2013–2016. The empirical results emphasized that market liquidity is influenced by earnings management that means the higher level of earnings management, the better equity liquidity. The findings provide additional insight into the determinants of stock liquidity such as earnings management, firm size, daily trading dollar volume of stock, average daily trading dollar volume of the firm, daily returns of stock, daily stock returns, average closing stock price of the firm.

scholarly journals Has Ebola Infected The Market: A Contagious Reaction To A (Media) Health Care Crisis?

1970 ◽  
Vol 35 (2) ◽  
pp. 55-75
Author(s):  
Jose Gutierrez ◽  
Mary Funck
Keyword(s):  
Health Care ◽  
Market Participants ◽  
Headline News ◽  
Health Care Crisis ◽  
News Event ◽  
The Impact ◽  
Dollar Volume

We examine the impact of Ebola headline news days on media-highlightedstocks. An Ebola news day (negative or positive in nature) is associated with increasedtrading, higher share volume, higher dollar volume, and increased share turnover.OLS regressions on industry-specific portfolios reveal that airline, restaurant, andcruise ship returns reverse themselves one day after the Ebola news event, a resultthat is consistent with behavioral overreaction literature. Empirical findings could beused to prepare market participants for analogous epidemics.

Internet Reverse Auctions

2011 ◽  
pp. 43-56
Author(s):  
Thomas F. Gattiker
Keyword(s):  
Literature Review ◽  
The Internet ◽  
Reverse Auctions ◽  
Reverse Auction ◽  
A Company ◽  
Dollar Volume

Once a company implements an internet reverse auction platform, buyers often have considerable discretion as to whether or not to utilize it. This paper discusses many reasons for fire non-adoption of Internet reverse auctions. The focus is on factors that impact the fit between the Internet reverse auction technology and the characteristics of the particular purchasing task that the buyer must carry out (i.e., characteristics of the material or service to be purchased in the market that it is to be purchased from). Data (qualitative comments) were collected from buyers within one firm. The comments detail the reasons that buyers have not used reverse auctions for particular commodities. Of the 9 factors identified in the literature review, 4 were actually cited by buyers. These are: specifiability, level of competition for the buyer’s business, importance of non-price factors, and dollar volume

scholarly journals The Night and Day of Amihud’s (2002) Liquidity Measure

2020 ◽  
Author(s):  
Yashar H Barardehi ◽  
Dan Bernhardt ◽  
Thomas G Ruchti ◽  
Marc Weidenmier
Keyword(s):  
Measurement Error ◽  
Cross Sections ◽  
Trading Volume ◽  
Volume Measurement ◽  
Strongly Correlated ◽  
Trading Cost ◽  
Price Impacts ◽  
The Absolute ◽  
Night And Day ◽  
Dollar Volume

Abstract Amihud’s stock (il)liquidity measure averages daily ratios of the absolute close-to-close return to dollar volume, including overnight returns. Our modified measure uses open-to-close returns matching return and trading volume measurement windows. It is more strongly correlated with trading-cost measures (by 8%–37%) and better explains cross-sections of returns, doubling estimated liquidity premiums. Using nonsynchronous trading near close, we show overnight returns are primarily information driven: including them in Amihud’s proxy for price impacts of trading magnifies measurement error, understating liquidity premiums. Our modification helps wherever Amihud’s measure is required. Our measures are publicly available for 1964–2019 and can be updated.

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