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Dynamic relations between order imbalance, volatility and return of top gainers

Dynamic relations between order imbalance, volatility and return of top gainers Investors have been working hard to find the best trading strategy. Previous studies suggest that order imbalance can be a state variable in explaining cross sectional stock return. In this article, we examine dynamic relations between order imbalance, volatility and stock return of top gainers. Then, we develop an order imbalance based trading strategy and explain the causality. We employ a time varying Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model to investigate intraday dynamics among order imbalance, volatility and return. A significantly negative relation between order imbalance and volatility has been documented. The leverage effect proposed by Christie (1982) could explain the above result. Current period order imbalance explains current period volatility and stock return. Contemporaneous order imbalance has a significantly positive and lag-one order imbalance has a significantly negative influence on stock return. Time span of data and responsibility of market maker explain this phenomenon. Finally, we develop a profitable order imbalance based trading strategy. To explore the profitability of our trading strategy, we examine the causal relationship between return and order imbalance. We find that order imbalance is a good indicator for price discovery. Moreover, order imbalance is a better indicator for predicting returns in large firm size quartile. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Economics Taylor & Francis

Dynamic relations between order imbalance, volatility and return of top gainers

Applied Economics , Volume 44 (12): 11 – Apr 1, 2012
11 pages

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References (55)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1466-4283
eISSN
9999-7004
DOI
10.1080/00036846.2010.543080
Publisher site
See Article on Publisher Site

Abstract

Investors have been working hard to find the best trading strategy. Previous studies suggest that order imbalance can be a state variable in explaining cross sectional stock return. In this article, we examine dynamic relations between order imbalance, volatility and stock return of top gainers. Then, we develop an order imbalance based trading strategy and explain the causality. We employ a time varying Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model to investigate intraday dynamics among order imbalance, volatility and return. A significantly negative relation between order imbalance and volatility has been documented. The leverage effect proposed by Christie (1982) could explain the above result. Current period order imbalance explains current period volatility and stock return. Contemporaneous order imbalance has a significantly positive and lag-one order imbalance has a significantly negative influence on stock return. Time span of data and responsibility of market maker explain this phenomenon. Finally, we develop a profitable order imbalance based trading strategy. To explore the profitability of our trading strategy, we examine the causal relationship between return and order imbalance. We find that order imbalance is a good indicator for price discovery. Moreover, order imbalance is a better indicator for predicting returns in large firm size quartile.

Journal

Applied EconomicsTaylor & Francis

Published: Apr 1, 2012

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