scholarly journals An Analysis of the Relationship between Stock Prices and Trading Volume

2008 ◽  
Vol null (26) ◽  
pp. 1-26
Author(s):  
곽병관
Keyword(s):  
Stock Prices ◽  
Trading Volume ◽  
The Relationship

The Study on the Plasticity Theoretical Models of the Volatility of Stock Prices

2012 ◽  
Vol 518-523 ◽  
pp. 5963-5967
Author(s):  
Rong Zhu ◽  
Zuo Quan Zhang ◽  
Xiao Yue Li ◽  
Xuan Wu ◽  
Su Zhang
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Theoretical Models ◽  
Equilibrium Price ◽  
Analysis Software ◽  
Volume Changes ◽  
Price Fluctuation ◽  
Basic Model ◽  
The Relationship

This paper analyzes the characteristics of the stock price fluctuation compared with elastic-plastic theory in mechanics and introduces the concept of stock equilibrium price, plasticity of stock price analogically. A basic model of the stock plasticity under the relationship between stock price fluctuation and trading volume changes is also built. Tested by 20 kinds of stocks from Shanghai and Shenzhen stock markets in China by using the econometric analysis software Eviews3.0 afterwards, the basic model is improved, and three developed models are built from it. Finally, this paper obtains more scientific and reasonable stock price plasticity model after the comparative analysis of the four previous models.

Autocorrelation and Volume in the Chinese Stock Market

2004 ◽  
Vol 07 (02) ◽  
pp. 289-309 ◽  
Author(s):  
Nicolaas Groenewold
Keyword(s):  
Stock Prices ◽  
Trading Volume ◽  
Stock Exchanges ◽  
Data Sets ◽  
Chinese Stock Market ◽  
Chinese Market ◽  
Market Makers ◽  
Using Data ◽  
The 1960S ◽  
The Relationship

This paper reports an empirical analysis of the relationship between return autocorrelation, trading volume and volatility, following the seminal paper by Campbell, Grossman and Wang (1992) using data for A shares traded on the Shanghai and Shenzhen stock exchanges for the period 1992–2002. Campbell et al. argue that autocorrelation of returns will be negatively related to trading volume given that market makers will need to be rewarded with higher returns for accommodating noise traders. For our full sample we find remarkably consistent support for the CGW hypothesis and results — return autocorrelations are negatively but non-linearly related to lagged trading volume and less strongly to volatility. These results are quite robust with respect to different messures of volume and volatility. We argue that this is a striking result in view of the substantial differences between the US market in the 1960s, 1970s and 1980s and the Chinese market of the 1990s. The relationship proves to be unstable over short sub-periods although whether this is due to the relatively short sample we use or to the inherent instability of the Chinese market in its first decade of operation will not be clear until much longer data sets are available for Chinese stock prices.

An Empirical Research on the Relationship between Real Estate Prices and Inflation

2011 ◽  
Vol 55-57 ◽  
pp. 1992-1996
Author(s):  
Tie Qun Li
Keyword(s):  
Real Estate ◽  
Stock Prices ◽  
Test Analysis ◽  
Social Demand ◽  
The Real Estate ◽  
Key Factor ◽  
Negative Effect ◽  
Labor Service ◽  
Real Estate Prices ◽  
The Relationship

The former researches referring to inflation and real estate prices concentrated mainly on the stock prices rather than the real estate prices. Owing to the enlarging ratio of real estate industry in national economy with each passing day, as well as the overheating real estate prices in recent years, the relationship between real estate prices and inflation is particularly vital to the monetary policy making for the monetary authorities. According to the test analysis of data from 2001 to 2009, it is found that real estate prices is Granger Cause of inflation while inflation is not the Granger Cause of real estate prices in this paper. Through the Effects of Wealth, Credit and Tobin, real estate prices drive the growth of social consumption and investments and expand the total social demand which possess an positive effect on inflation; nevertheless the rising of real estate prices causes the rising of currency for real estate purchasing, which, under the circumstance of that currency supply remains, will inevitably bring about the reduction of currency for other consumption and investments and restrain the total social demand which would mean a suppression of continuous rising of prices of other commodity and labor service. All these show that real estate also has a negative effect on inflation. The cancellations between the two effects make the long-term influence real estate bearing on inflation is not obvious. The experimental results indicate that when the price of real estate rises 1%, inflation only rises 0.058%. Consequently, a strict controlling of the amount of money issued is the key factor for keeping the over rapid rising of real estate prices from leading to inflation.

scholarly journals Is Abnormally Large Volume a Clue?

2016 ◽  
Vol 8 (9) ◽  
pp. 226
Author(s):  
Tsung-Hsun Lu ◽  
Jun-De Lee
Keyword(s):  
Stock Market ◽  
Large Volume ◽  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Sensitive Analysis ◽  
Support Level ◽  
Out Of Sample ◽  
Sample Test ◽  
Abnormal Trading Volume

This paper investigates whether abnormal trading volume provides information about future movements in stock prices. Utilizing data from the Taiwan 50 Index from October 29, 2002 to December 31, 2013, the researchers employ trading volume rather than stock price to test the principles of resistance and support level employed by technical analysis. The empirical results suggest that abnormal trading volume provides profitable information for investors in the Taiwan stock market. An out-of-sample test and a sensitive analysis are conducted for the robustness of the results.

scholarly journals PENGARUH VOLUME PERDAGANGAN DAN SIMPLE MOVING AVERAGE TERHADAP HARGA SAHAM

2020 ◽  
Vol 1 (1) ◽  
pp. 1-16
Author(s):  
Gama Paksi Baskara ◽  
Suyanto Suyanto ◽  
Sri Retnaning Rahayu
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Qualitative Data ◽  
Moving Average ◽  
Analytical Tool ◽  
T Test ◽  
Quantitative Approach ◽  
F Test ◽  
Regression Tests

Trading volume is a sheet of company shares traded on a particular transaction and has beenagreed between the seller and the buyer, Simple Moving Average is a method that studies themovement of the previous stock price based on the number of certain days in order to predict thestock price that will occur to the next.The objective of the study is to find out how much influenceTrade Volume and Simple Moving Average on Stock Prices is and what are the most dominantaspects in influencing Stock Prices. The type of the research uses a quantitative approach, namely anapproach in which the data are in the form of numbers or qualitative data that have been used asnumbers. The technique of collecting data uses documentation. The analytical tool used is multiplelinear regression tests including T Test, F Test and Coefisein R² Determination processed usingEviews. The results of the study show that partially the trading volume variable does not have asignificant effect on Stock Prices and the Simple Moving Average variable shows a positive andsignificant effect on stock prices while the results of the research simultaneously show that theTrading Volume and Simple Moving Average variables simultaneously affect the Stock Price .

scholarly journals Hubungan Perilaku Perdagangan Investor Dengan Volume Perdagangan Di Bursa Efek Indonesia

2009 ◽  
Vol 2 (1) ◽  
Author(s):  
Ghazali Syamni
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Time Interval ◽  
Time Intervals ◽  
Using Data ◽  
Changes Over Time ◽  
Relationship Of ◽  
The Relationship ◽  
Order Pattern ◽  
Over Time

This paper examines the relationship of behavior trading investor using data detailed transaction history-corporate edition demand and order history in Indonesia Stock Exchange during period of March, April and May 2005. Peculiarly, behavior placing of investor order at trading volume. The result of this paper indicates that trading volume order pattern to have pattern U shape. The pattern happened that investors have strong desires to places order at the opening and close of compared to in trading periods. While the largest orders are of market at the opening indicates that investor is more conservatively when opening, where many orders when opening has not happened transaction to match. In placing order both of investor does similar strategy. By definition, informed investors’ orders more large than uninformed investors. If comparison of order examined hence both investors behavior relatively changes over time. But, statistically shows there is not ratio significant. This implies behavior trading of informed investors and uninformed investors stable relative over time. The result from regression analysis indicates that informed investors to correlate at trading volume in all time intervals, but not all uninformed investors correlates in every time interval. This imply investor order inform is more can explain trading volume pattern compared to uninformed investor order in Indonesia Stock Exchange. Finally, result of regression also finds that order status match has greater role determines trading volume pattern intraday especially informed buy match and informed sale match. While amend, open and withdraw unable to have role to determine intraday trading volume pattern.

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