scholarly journals Investigation of Causal Relationship between Stock Prices and Trading Volume using Toda and Yamamoto Procedure

2014 ◽  
Vol 7 (14) ◽  
pp. 155-181 ◽  
Author(s):  
Sushil BAJAJ ◽  
◽  
Vibha DUA ◽  
2018 ◽  
Vol 43 (1) ◽  
pp. 47-57 ◽  
Author(s):  
C. P. Gupta ◽  
Sanjay Sehgal ◽  
Sahaj Wadhwa

Executive Summary The future trading has been held responsible by certain political and interest groups of enhancing speculative trading activities and causing volatility in the spot market, thereby further spiralling up inflation. This study examines the effect of future of trading activity on spot market volatility. The study first determined the Granger causal relationship between unexpected future trading volume and spot market volatility. It then examined the Granger causal relationship between unexpected open interest and spot market volatility. The spot volatility and liquidity was modelled using EGARCH and unexpected trading volume. The expected trading volume and open interest was calculated by using the 21-day moving average, and the difference between actual and expected component was treated as the unexpected trading volume and unexpected open interest. Empirical results confirm that for chickpeas ( channa), cluster bean ( guar seed), pepper, refined soy oil, and wheat, the future (unexpected) liquidity leads spot market volatility. The causal relationship implies that trading volume, which is a proxy for speculators and day traders, is dominant in the future market and leads volatility in the spot market. The results are in conformity with earlier empirical findings — Yang, Balyeat and Leathan (2005) and Nath and Lingareddy (2008) —that future trading destabilizes the spot market for agricultural commodities. Results show that there is no causal relationship between future open interest and spot volatility for all commodities except refined soy oil and wheat. The findings imply that open interest, which is a proxy of hedging activity, is leading to volatility in spot market for refined soy oil and wheat. The results are in conformity to earlier empirical studies that there is a weak causal feedback between future unexpected open interest and volatility in spot market ( Yang et al., 2005 ). For chickpeas (channa), the increase in volatility in the spot market increases trading activity in the future market. The findings are contrary to earlier empirical evidence ( Chatrath, Ramchander, & Song, 1996 ; Yang et al., 2005 ) that increase in spot volatility reduces future trading activity. However, they are in conformity to Chen, Cuny and Haugen (1995) that increase in spot volatility increases future open interest. The results reveal that the future market has been unable to engage sufficient hedging activity. Thereby, a causal relationship exists only for future trading volume and spot volatility, and not for future open interest and spot volatility. The results have major implications for policymakers, investment managers, and for researchers as well. The study contributes to literature on price discovery, spillovers, and price destabilization for Indian commodity markets.


2016 ◽  
Vol 8 (9) ◽  
pp. 226
Author(s):  
Tsung-Hsun Lu ◽  
Jun-De Lee

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.


2020 ◽  
Vol 1 (1) ◽  
pp. 1-16
Author(s):  
Gama Paksi Baskara ◽  
Suyanto Suyanto ◽  
Sri Retnaning Rahayu

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 .


2020 ◽  
Vol 4 (1) ◽  
pp. 26
Author(s):  
Erni Jayani ◽  
Jumiadi Abdi Winata ◽  
Khairunnisa Harahap

The problem in this research is the need for fast and accurate information in the format of the presentation of financial statements resulting in the distribution of information, and data management can be problematic. Therefore, a format for financial reporting systems, namely Extensible Business Reporting Language (XBRL), was formed. The purpose of this study was to determine the effect of XBRL technology, stock prices, Return on Assets (ROA), and institutional ownership on market efficiency (information asymmetry and stock trading volume). The population and sample of this study are banking companies listed on the Indonesia Stock Exchange from 2015-2016. The sampling method using a purposive sampling method and obtained a sample of 42 companies. Data collection techniques are carried out by taking data from the Indonesia Stock Exchange website (www.idx.co.id) and the site http://finance.yahoo.com. Data were analyzed with multiple regression tests after being declared normal with the normality test and though using SPSS 20. The results of this study simultaneously stated that XBRL technology, stock prices, ROA, and institutional ownership together have an influence on information asymmetry and stock trading volume. From the results of the study, it can be concluded that XBRL technology, stock prices, ROA, and institutional ownership cause a decrease in the level of information asymmetry and trading volume. This result also states that the company is in excellent condition when the value of information asymmetry decreases, but it is not good when the trading volume of its shares also decreases. Keywords: XBRL Technology; Stock Prices; Market Efficiency; Information Asymmetry; Stock Trading Volume. 


Sign in / Sign up

Export Citation Format

Share Document