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Do order imbalances predict Chinese stock returns? New evidence from intraday data · Study

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ArticleDo order imbalances predict Chinese stock returns? New evidence from intraday data

Paresh Kumar Narayan2015

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Do order imbalances predict Chinese stock returns? New evidence from intraday data

Paresh Kumar Narayan · Seema Narayan · Joakim Westerlund

43 citations·0/0 files stored·Pacific-Basin Finance Journal

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Financial Markets and Investment Strategies Financial Risk and Volatility Modeling Stock Market Forecasting Methods

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References

1993Common risk factors in the returns on stocks and bonds 2003Testing for unit roots in heterogeneous panels 1994Comparing Predictive Accuracy 1995Comparing Predictive Accuracy 2007A Comprehensive Look at The Empirical Performance of Equity Premium Prediction 1991Inferring Trade Direction from Intraday Data 2007Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?2008A bias-adjusted LM test of error cross-section independence

Cited by

2019Economic policy uncertainty and the Chinese stock market volatility: new evidence 2015Emerging trends in Asia-Pacific finance research: A review of recent influential publications and a research agenda 2016Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models 2019Is Indonesia's stock market different when it comes to predictability?2017The intraday directional predictability of large Australian stocks: A cross-quantilogram analysis

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Year2015

Typearticle

Published2015-07-29

VenuePacific-Basin Finance Journal

ISSN-L0927-538X

Languageen

Citations43

Files0 public / 0

ShelfFinancial Markets and Investment Strategies

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doi10.1016/j.pacfin.2015.07.003

openalex_workW2157746809

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2018

Information asymmetry, cluster trading, and market efficiency: Evidence from the Chinese stock market

2018A new GARCH model with higher moments for stock return predictability

2016Intraday return predictability, portfolio maximisation, and hedging