Speed of information adjustment in Indian stock indices
TLDR
In this article, the authors tried to analyse the speed at which information gets incorporated into the various stock indices in India and found that the Sensex and Nifty indices, the constituents of which are large capitalization stocks, led the smaller indices till 2009.Citations
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Measuring Productive Efficiency of Stock Exchanges Using Price Adjustment Coefficients
TL;DR: In this paper, the authors measured the speed of stock price adjustment to its intrinsic value with the arrival of new information, and found that information adjustment in the Indian market is very slow.
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Modeling S&P Bombay Stock Exchange BANKEX Index Volatility Patterns Using GARCH Model☆
TL;DR: In this paper, the authors have modeled the volatility patterns of the S&P Bombay Stock Exchange (BSE) BANKEX index which is the indian banking sector index.
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Volatility–volume causality across single stock spot–futures markets in India
TL;DR: In this article, the causal relationships between volatility and volume across spot and futures market for the 50 constituent stocks of the CNX NIFTY Index were examined and the results highlight the importance of volume in absorbing information and its behaviour as the conduit of information.
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Accounting for unadjusted news sentiment for asset pricing
TL;DR: It is demonstrated that it is possible to identify unincorporated information and extract the sentiment polarity to predict future market direction, and top-down/ bottom-up models using quantitative proxy sentiment indicators and natural language processing/machine learning approaches to compute the sentiment from qualitative information to explain variance in market returns.
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Speed of Price Adjustment towards Market Efficiency: Evidence from Emerging Countries:
Parthajit Kayal,S. Maheswaran +1 more
TL;DR: In this paper, the speed with which stock markets adjust to information and news flow into asset prices is of importance to investors, regulators and policymakers, and the authors provide a simple and uniform...
References
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Journal ArticleDOI
Estimating the Dimension of a Model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Estimating the dimension of a model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
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Trading Volume and Cross-Autocorrelations in Stock Returns
TL;DR: In this article, the authors find that trading volume is a significant determinant of the lead-lag patterns observed in stock returns, and that returns on low volume portfolios respond more slowly to information in market returns.
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Trading Volume and Cross-Autocorrelations in Stock Returns
TL;DR: This article found that trading volume is a significant determinant of the lead-lag patterns observed in stock returns, and the speed of adjustment of individual stocks confirms these findings, indicating that differential speed of adjusting to information was a significant source of the cross-autocorrelation patterns in short-horizon stock returns.
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A Simple Measure of Price Adjustment Coefficients
TL;DR: In this paper, the authors developed a simple approach to estimate the price adjustment coefficients by using the information in return processes, and found evidence of a lagged adjustment in shorter return intervals for firms in all market value classes.