scholarly journals Multivariate Fractional Integration Tests allowing for Conditional Heteroskedasticity with an Application to Return Volatility and Trading Volume

2021 ◽  
Author(s):  
Marina Balboa ◽  
Paulo M. M. Rodrigues ◽  
Antonio Rubia ◽  
A. M. Robert Taylor
Keyword(s):  
Trading Volume ◽  
Fractional Integration ◽  
Conditional Heteroskedasticity ◽  
Return Volatility

Assessment of Asymmetric Information Cost in Indian Stock Market: A Sectoral Approach

2020 ◽  
pp. 097215091986508
Author(s):  
Aritra Pan ◽  
Arun Kumar Misra
Keyword(s):  
Asymmetric Information ◽  
Stock Prices ◽  
Trading Volume ◽  
Share Price ◽  
Return Volatility ◽  
Information Cost ◽  
Market Conditions ◽  
Price Variation ◽  
Bid Ask Spread ◽  
The Impact

Bid-ask spread, along with profit, also encompass the impact of asymmetric information cost and order processing cost. Asymmetric information influences stock prices with varying degree of investors’ perception. Estimation of asymmetric information cost and its determinants have been explored significantly under low-frequency trading. The literature hardly attempts to study asymmetric information cost under high-frequency trading (HFT). Asymmetric information cost significantly influences bid-ask spread, and hence the nature of its impact under different market conditions needs to be analyzed under HFT. The study attempts to estimate asymmetric information cost in HFT and analyze its determinants under different industry sectors and market conditions. The study followed Affleck-Graves et al. (1994 , The Journal of Finance, 49(4), 1471–1488) model to estimate the asymmetric information cost using 5 minutes interval data for a period of 82 trading days. Information gets reflected in equity through the movement in price, variation in trading volume, and return volatility. The study has found share price, traded volume, return volatility and trading frequency as the major determinants of asymmetric information cost in different market conditions. The findings of the study have significant implications for market microstructure for trading, lowering information asymmetry in market and enhancing market quality.

A THRESHOLD MODEL FOR STOCK RETURN VOLATILITY AND TRADING VOLUME

2000 ◽  
Vol 03 (03) ◽  
pp. 467-472 ◽  
Author(s):  
GIULIA IORI
Keyword(s):  
Transaction Costs ◽  
Trading Volume ◽  
Stock Return ◽  
Cross Correlation ◽  
Threshold Model ◽  
Feedback Mechanism ◽  
Return Volatility ◽  
Volatility Clustering ◽  
Stock Return Volatility ◽  
Future Trading

We propose a model with heterogeneous interacting traders which can explain the observed cross-correlation between stock return volatility and trading volume. Transaction costs are introduced which, by responding to price movements, create a feedback mechanism on future trading and generates volatility clustering.

New evidence on the relation between return volatility and trading volume

2009 ◽  
pp. n/a-n/a ◽  
Author(s):  
Thomas C. Chiang ◽  
Zhuo Qiao ◽  
Wing-Keung Wong
Keyword(s):  
Trading Volume ◽  
Return Volatility ◽  
New Evidence

scholarly journals Foreign Ownership, Return Volatility, Trading Volume, and Risk of Stocks in Indonesia

2018 ◽  
Author(s):  
Ahmad Maulin Naufa ◽  
I Wayan Nuka Lantara
Keyword(s):  
Panel Data ◽  
Trading Volume ◽  
Stock Return ◽  
Stock Exchange ◽  
Foreign Ownership ◽  
Return Volatility ◽  
Stock Return Volatility ◽  
Indonesian Government ◽  
The Relationship

This study examines the relationship between foreign ownership and return volatility, trading volume, and risk of stocks at the Indonesia Stock Exchange (IDX). Panel data of selected companies listed on the LQ45 index of the IDX was employed for the period between 2011 and 2017. Foreign ownership was found to positively affect stock return volatility, trading volume, and risk. Hence, more substantial foreign ownership of stocks meant more drawbacks to Indonesian stocks. Therefore, there is a need for the Indonesian government to limit and regulate foreign shareholders in Indonesia.  

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