Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Asymmetric effect of market liquidity demand shocks on price shocks Empirical studies based on the CSI 300 Index and the Futures

Asymmetric effect of market liquidity demand shocks on price shocks Empirical studies based on... Purpose – With the launch of CSI 300 Index Futures trading on April 16, 2010, China's stock market presents a more diversified trend, such as arbitrage, trends strategy entering the market rapidly. Therefore, the liquidity demand also presents a higher frequency, and the change is more complex than the original situation. In recent years, many literatures are engaged in high‐frequency trading (HFT) related research, and an important concern is the impact of HFT on market volatility and liquidity. Is it playing the role of stabilizing the market, or bringing more noise and turmoil? Based on this, the purpose of this study is trying to study what kind of impact the HFT have on market liquidity before and after the launch of the CSI 300 Index Futures. Design/methodology/approach – The paper uses the simultaneous equations model of price and net order flow proposed by Deuskar and Johnson and for the first time introduces an asymmetric identification through heteroskedasticity (ITH) method. The paper applies the method to the high‐frequency data of CSI 300 Index and the Futures and classifies the buying and selling orders through volume clock. The price risks are decomposed into a component driven by the impact of liquidity demand shocks (flow‐driven risks (FDRs)) and a component driven by external information (information‐driven risks (IDRs)). Findings – The empirical results show that the flow‐driven risk of CSI 300 Index Futures is about 20 percent. In addition, before the introduction of the Index Futures, there is no asymmetric effect between liquidity demand shocks and price shocks existing in either CSI 300 Index or CSI 300 Index Futures. While after the introduction of stock Index Futures, the asymmetric effect in the both two markets emerges. The impact of the buying net order flows on the price is less than the impact of the selling net order flows on CSI 300 Index, whereas the impact of the buying net order flows on the price is larger than the impact of the selling net order flows on CSI 300 Index Futures. The paper further analyzes the relationship between liquidity and FDR and gets the conclusion that the reasons for the deterioration of the liquidity level are caused by the impact of the external information shocks, rather than the liquidity demand shocks. And entries of HFTs like arbitrage traders and hedge traders play a positive role in improving the liquidity level in the market. Originality/value – The paper introduces an asymmetric ITH method for the first time and finds asymmetric effect of the net order flow on the return in both CSI 300 Index market and the corresponding Index Futures market. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png China Finance Review International Emerald Publishing

Asymmetric effect of market liquidity demand shocks on price shocks Empirical studies based on the CSI 300 Index and the Futures

Download PDF
20 pages

Loading next page...
 
/lp/emerald-publishing/asymmetric-effect-of-market-liquidity-demand-shocks-on-price-shocks-cPPF3wG7Lv
Publisher
Emerald Publishing
Copyright
Copyright © 2013 Emerald Group Publishing Limited. All rights reserved.
ISSN
2044-1398
DOI
10.1108/CFRI-04-2012-0040
Publisher site
See Article on Publisher Site

Abstract

Purpose – With the launch of CSI 300 Index Futures trading on April 16, 2010, China's stock market presents a more diversified trend, such as arbitrage, trends strategy entering the market rapidly. Therefore, the liquidity demand also presents a higher frequency, and the change is more complex than the original situation. In recent years, many literatures are engaged in high‐frequency trading (HFT) related research, and an important concern is the impact of HFT on market volatility and liquidity. Is it playing the role of stabilizing the market, or bringing more noise and turmoil? Based on this, the purpose of this study is trying to study what kind of impact the HFT have on market liquidity before and after the launch of the CSI 300 Index Futures. Design/methodology/approach – The paper uses the simultaneous equations model of price and net order flow proposed by Deuskar and Johnson and for the first time introduces an asymmetric identification through heteroskedasticity (ITH) method. The paper applies the method to the high‐frequency data of CSI 300 Index and the Futures and classifies the buying and selling orders through volume clock. The price risks are decomposed into a component driven by the impact of liquidity demand shocks (flow‐driven risks (FDRs)) and a component driven by external information (information‐driven risks (IDRs)). Findings – The empirical results show that the flow‐driven risk of CSI 300 Index Futures is about 20 percent. In addition, before the introduction of the Index Futures, there is no asymmetric effect between liquidity demand shocks and price shocks existing in either CSI 300 Index or CSI 300 Index Futures. While after the introduction of stock Index Futures, the asymmetric effect in the both two markets emerges. The impact of the buying net order flows on the price is less than the impact of the selling net order flows on CSI 300 Index, whereas the impact of the buying net order flows on the price is larger than the impact of the selling net order flows on CSI 300 Index Futures. The paper further analyzes the relationship between liquidity and FDR and gets the conclusion that the reasons for the deterioration of the liquidity level are caused by the impact of the external information shocks, rather than the liquidity demand shocks. And entries of HFTs like arbitrage traders and hedge traders play a positive role in improving the liquidity level in the market. Originality/value – The paper introduces an asymmetric ITH method for the first time and finds asymmetric effect of the net order flow on the return in both CSI 300 Index market and the corresponding Index Futures market.

Journal

China Finance Review International – Emerald Publishing

Published: Oct 25, 2013

Keywords: HFTs; Liquidity demand shocks; Price shocks

References

  • Illiquidity and stock returns: cross‐section and time‐series effects
    Amihud, Y.
  • Asymmetric ACD Models: Introducing Price Information in ACD Models with a Two State Transition Model
    Bauwens, L.; Giot, P.
  • High frequency trading and its impact on market quality
    Brogaard, J.
  • The interaction between order imbalance and stock price
    Brown, P.; Walsh, D.; Yuen, A.
  • A Variance Decomposition for Stock Returns
    Campbell, J.Y.
  • The flash crash: trading aggressiveness, liquidity supply, and the impact of intermarket sweep orders
    Chakravarty, S.; Upson, J.
  • Order imbalance and individual stock returns: theory and evidence
    Chordia, T.; Subrahmanyam, A.
  • Order imbalance, liquidity, and market returns
    Chordia, T.; Roll, R.; Subrahmanyam, A.; Subrahmanyam, C.R.
  • Market liquidity and flow‐driven risk
    Deuskar, P.; Johnson, T.C.
  • The microstructure of the ‘flash crash’: flow toxicity, liquidity crashes and the probability of informed trading
    Easley, D.; López de Prado, M.; O'Hara, M.
  • The exchange of flow toxicity
    Easley, D.; López de Prado, M.; O'Hara, M.
  • Bulk classification of trading activity
    Easley, D.; López de Prado, M.; O'Hara, M.
  • Flow toxicity and liquidity in a high‐frequency world
    Easley, D.; López de Prado, M.; O'Hara, M.
  • Liquidity, information, and infrequently traded stocks
    Easley, D.; Kiefer, N.M.; O'Hara, M.; Paperman, J.B.
  • Predicting VNET: a model of the dynamics of market depth
    Engle, R.F.; Lange, J.
  • Autoregressive conditional duration: a new model for irregularly spaced transaction data
    Engle, R.F.; Russell, J.R.
  • Order imbalance and the dynamics of index and futures prices
    Fung, J.K.W.; Yu, P.L.H.
  • Low‐Latency Trading
    Hasbrouck, J.; Saar, G.
  • High‐Frequency Trading and Price Discovery
    Hendershott, T.J.; Riordan, R.
  • The flash crash: the impact of high frequency trading on an electronic market
    Kirilenko, A.; Kyle, A.; Samadi, M.; Tuzun, T.
  • Asymmetric information, firm investment and stock prices
    Kong, D.; Xiao, T.; Liu, S.
  • Inferring trade direction from intraday data
    Lee, C.M.C.; Ready, M.J.
  • Momentum and asymmetric information
    Liang, T.
  • Identification through heteroskedasticity
    Rigobon, R.
  • Order imbalance and stock returns: evidence from China
    Shenoy, C.; Zhang, Y.J.