Will Order Imbalances Predict Stock Returns in Extreme Market Situations? Evidence from China

Lao, Lan-Jun; Tian, Shu; Zhao, Qidan

doi:10.1080/1540496x.2016.1278364

Cited by 7 publications

(4 citation statements)

References 35 publications

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“…While many studies report significant predictive power of order imbalance for stock returns, others do not. For example, Shenoy and Zhang (2007) and Lao et al (2018) suggest, unlike the findings of Chordia and Subrahmanyam (2004) in U.S. markets, that order imbalance do not show predictive power in China. Understanding this difference is important because it provides insights in the nature of the predictability of order imbalance to stock returns.…”

Section: Introductionmentioning

confidence: 95%

“…As a result, order imbalance is predictive of stock returns. Many studies have examined the relationship between stock returns and order imbalance since then (e.g., Bailey, Cai, Cheung, & Wang, 2009; Chordia & Subrahmanyam, 2004; Lao, Tian, & Zhao, 2018; Narayan, Narayan, & Westerlund, 2015; Shenoy & Zhang, 2007). Contributing to this growing literature in this paper we use the first half‐hour order imbalance ( FOIB ) as a predictor of stock returns.…”

Section: Introductionmentioning

confidence: 99%

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Forecasting stock returns using first half an hour order imbalance

Chu

Qiu

2020

Int. J Fin Econ

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We explore the predictive power of the first half‐hour order imbalance (FOIB) to stock returns in Chinese stock market. Our results show that FOIB predicts returns better than daily order imbalance both in‐sample and out‐of‐sample. The predictive power of FOIB is both statistically and economically significant. Moreover, we provide evidence that the predictive power of FOIB appears stemming from large trade size.

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Forecasting stock returns using first half an hour order imbalance

Chu

Qiu

2020

Int. J Fin Econ

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“…There are relatively few prior order flow studies of Chinese markets, with Shenoy and Zhang (2007), He, Yang, Xie, and Han (2014), Narayan, Narayan, and Westerlund (2015), Wang, Ye, and Zhao (2016) and Lao, Tian, and Zhao (2017), being notable exceptions. While Shenoy and Zhang (2007), Narayan et al (2015) and Lao et al (2017) find a positive contemporaneous relation between daily trade imbalance and price change in Chinese stock markets, the agricultural futures focus of He et al (2014) and Wang et al (2016) is more closely aligned to our study. He et al (2014) study Chinese agricultural futures markets, discovering a strong and positive contemporaneous relation between price and volume for six agricultural futures contracts including soybean meal.…”

Section: Introductionmentioning

confidence: 99%

Order book price impact in the Chinese soybean futures market

Jin

Kearney

et al. 2021

Int. J Fin Econ

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We study the price impact of order flow in the world's largest soybean meal futures markets. Our intraday results indicate that incoming orders can be used to explain and predict future price changes. Our results are shown to be robust to various order flow measures, price aggregation approaches and data frequencies. We find that order flow imbalance (OFI) is a more allencompassing measure carrying greater information about price change relative to both trade imbalance (TI) and volume. Moreover, while both OFI and TI are shown to predict future price changes, this predictability diminishes over longer measure and price change frequency horizons.

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“…There are relatively few prior order flow studies of Chinese markets, with Shenoy and Zhang (2007), He et al (2014), Narayan et al (2015), Wang et al (2016) and Lao et al (2017), being notable exceptions. While Shenoy and Zhang (2007), Narayan et al (2015) and Lao et al (2017) find a positive contemporaneous relation between daily trade imbalance and price change in Chinese stock markets, the agricultural futures focus of He et al (2014) and Wang et al (2016) is more closely aligned to our study. He et al (2014) study Chinese agricultural futures markets, discovering a strong and positive contemporaneous relation between price and volume for six agricultural futures contracts including soybean meal.…”

Section: Introductionmentioning

confidence: 99%