scholarly journals How Investor Structure Influences the Yield, Information Dissemination Efficiency, and Liquidity

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hongli Che ◽  
Xiong Xiong ◽  
Juntian Yang ◽  
Wei Zhang ◽  
Yongjie Zhang
Keyword(s):  
Information Dissemination ◽  
Futures Market ◽  
Stock Index ◽  
Stock Index Futures ◽  
Agent Based ◽  
Index Futures ◽  
Yield Information ◽  
Informed Traders ◽  
Probability Of Informed Trading ◽  
Dissemination Efficiency

This essay focuses on the investor structure of the stock index futures market and uses agent-based computational finance method to discuss how the volume-synchronized probability of informed trading (VPIN) affects market absolute yield, information dissemination efficiency, and liquidity with different ratios of informed traders in the market. The result shows that the higher the proportion of informed traders is, the more the volatility of the market is. Furthermore, the result indicates that when the proportion of informed traders in the stock index futures market accounts for 1/3-1/2, the transparency and liquidity of the market will be better.

scholarly journals Study on Informational Transaction and Its Effect on China's Stock Index Futures Market

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Hongli Che ◽  
Xiong Xiong ◽  
Jiatong Han ◽  
Wei Zhang ◽  
Yongjie Zhang
Keyword(s):  
Futures Market ◽  
Informed Trading ◽  
Stock Index ◽  
Stock Index Futures ◽  
Risky Assets ◽  
Index Futures ◽  
The Future ◽  
Probability Of Informed Trading

Information is one of the important factors that influence the behavior of investors and then have an effect on the price of the risky assets in the market. Firstly, the new procedure developed by Easley et al. (2011) is used to estimate the Volume-Synchronized Probability of Informed Trading (VPIN) of the Chinese stock index futures market. Then VPIN for special scenarios is depicted. As a result, we find that the future contracts generally have a larger number of information transactions. We also find that, for particular scenarios, the probability of informed trading in the market has obvious exceptions. The larger proportion of informed trader is, the higher the volatility of the price is.

scholarly journals VPIN and the China’s Circuit-Breaker

2017 ◽  
Vol 9 (12) ◽  
pp. 126 ◽  
Author(s):  
Yameng Zheng
Keyword(s):  
High Frequency ◽  
Circuit Breaker ◽  
Futures Market ◽  
Informed Trading ◽  
Stock Index ◽  
Stock Index Futures ◽  
Index Futures ◽  
Trading Market ◽  
Probability Of Informed Trading

The market microstructure theory and high-frequency trading analyze as quantitative investment’s frontier and hot issue is popular in China in recent years, but China’s stock index futures introduced later, so there are not much academic attention. This paper measures the probability of informed trading in China’s stock index futures market by VPIN method. The empirical results show that the VPIN can not only monitor the probability of the informed trading market of IF 300, IH 50 and IC 500, but also play an early warning role before the “circuit-breaker”. Tracking VPIN values allows the liquidity providers to control their position risk, and regulators can monitor the liquidity quality of the market, limit transactions in advance or tighten market controls.

scholarly journals Impact of the Adjustment of Maximum Order Volume on Pricing Efficiency of Stock Index Futures in China

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Liang Wang ◽  
Tingjia Xu ◽  
Longhao Qin ◽  
Xianyan Xiong
Keyword(s):  
Futures Market ◽  
Informed Trading ◽  
Stock Index ◽  
Stock Index Futures ◽  
Order Book ◽  
Maximum Order ◽  
Index Futures ◽  
Pricing Efficiency ◽  
Probability Of Informed Trading ◽  
The Impact

In April 2017, China Financial Futures Exchange adjusted the maximum order volume of single trading in stock index futures, and this paper conducts research on this event. Firstly, it analyzes the influence of the adjustment of maximum order volume on the characteristics of the limit order book with high-frequency data and the impact of ordering situation on the trading depth and volatility of each contract with panel data. Secondly, it takes high-frequency tick-by-tick data to explore the causal relationship between the ordering situation and the probability of informed trading and analyzes the impact of the event on the probability of informed trading. Finally, the dynamic factor analysis method is used to quantify the pricing efficiency based on the probability of informed trading and the characteristics of limit order book, and the influence of the event on the pricing efficiency of stock index futures market is discussed. The results show that the reduction of maximum order volume has different effects on dominant contracts and nondominant contracts of stock index futures. After the event, the overall trading volume of the market increased, where the trading volume of dominant contracts decreased and that of nondominant contracts increased. For dominant contracts, the depth, slope, and liquidity decrease, the spread increases, and the probability of informed trading decreases so that the pricing efficiency becomes worse, while the results of nondominant contracts are the opposite. For Chinese stock index futures market, the pricing efficiency is greatly reduced and the resource allocation capacity is weakened under the influence of the event. Therefore, the adjustment of maximum order volume is not conducive to the healthy development of the stock index futures market. It is suggested that the reduction of the maximum order volume is only implemented for nondominant contracts.

scholarly journals The Impact of Underlying Market Closure on Futures Market Liquidity: Evidence from China

2012 ◽  
Author(s):  
Wang Chun Wei ◽  
Alex Frino
Keyword(s):  
Futures Market ◽  
Market Liquidity ◽  
Stock Index ◽  
Stock Index Futures ◽  
Contagion Effect ◽  
Index Futures ◽  
Empirical Results ◽  
Open Session ◽  
The Impact ◽  
Closure Theory

This study investigates the trading activity of Chinese stock index futures, recently introduced at the open and close of the underlying trading. We document the impact of the underlying spot on the futures market liquidity as well as volatility as discussed in earlier works on market closure theory. Our empirical results support previous literature on the impact of the underlying, particularly during the open session, as a contagion effect, which is clearly at play. We find significant U-shaped patterns in liquidity factors and intraday volatility during open and close trades in the morning.  

The nonlinear characteristics of Chinese stock index futures yield volatility

2019 ◽  
Vol 10 (2) ◽  
pp. 175-196 ◽  
Author(s):  
Xuebiao Wang ◽  
Xi Wang ◽  
Bo Li ◽  
Zhiqi Bai
Keyword(s):  
High Frequency ◽  
Futures Market ◽  
Stock Index ◽  
High Frequency Data ◽  
Stock Index Futures ◽  
Frequency Data ◽  
Short Term ◽  
Content Type ◽  
Index Futures ◽  
Basic Characteristics

Purpose The purpose of this paper is to consider that the model of volatility characteristics is more reasonable and the description of volatility is more explanatory. Design/methodology/approach This paper analyzes the basic characteristics of market yield volatility based on the five-minute trading data of the Chinese CSI300 stock index futures from 2012 to 2017 by Hurst index and GPH test, A-J and J-O Jumping test and Realized-EGARCH model, respectively. The results show that the yield fluctuation rate of CSI300 stock index futures market has obvious non-linear characteristics including long memory, jumpy and asymmetry. Findings This paper finds that the LHAR-RV-CJ model has a better prediction effect on the volatility of CSI300 stock index futures. The research shows that CSI300 stock index futures market is heterogeneous, means that long-term investors are focused on long-term market fluctuations rather than short-term fluctuations; the influence of the short-term jumping component on the market volatility is limited, and the long jump has a greater negative influence on market fluctuation; the negative impact of long-period yield is limited to short-term market fluctuation, while, with the period extending, the negative influence of long-period impact is gradually increased. Research limitations/implications This paper has research limitations in variable measurement and data selection. Practical implications This study is based on the high-frequency data or the application number of financial modeling analysis, especially in the study of asset price volatility. It makes full use of all kinds of information contained in high-frequency data, compared to low-frequency data such as day, weekly or monthly data. High-frequency data can be more accurate, better guide financial asset pricing and risk management, and result in effective configuration. Originality/value The existing research on the futures market volatility of high frequency data, mainly focus on single feature analysis, and the comprehensive comparative analysis on the volatility characteristics of study is less, at the same time in setting up the model for the forecast of volatility, based on the model research on the basic characteristics is less, so the construction of a model is relatively subjective, in this paper, considering the fluctuation characteristics of the model is more reasonable, characterization of volatility will also be more explanatory power. The difference between this paper and the existing literature lies in that this paper establishes a prediction model based on the basic characteristics of market return volatility, and conducts a description and prediction study on volatility.

Does VPIN provide predictive information for realized volatility forecasting: evidence from Chinese stock index futures market

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Conghua Wen ◽  
Fei Jia ◽  
Jianli Hao
Keyword(s):  
High Frequency ◽  
Realized Volatility ◽  
Futures Market ◽  
Stock Index ◽  
Stock Index Futures ◽  
Trading Behavior ◽  
Volatility Forecasting ◽  
Content Type ◽  
Index Futures ◽  
Intraday Data

PurposeUsing intraday data, the authors explore the forecast ability of one high frequency order flow imbalance measure (OI) based on the volume-synchronized probability of informed trading metric (VPIN) for predicting the realized volatility of the index futures on the China Securities Index 300 (CSI 300).Design/methodology/approachThe authors employ the heterogeneous autoregressive model for realized volatility (HAR-RV) and compare the forecast ability of models with and without the predictive variable, OI.FindingsThe empirical results demonstrate that the augmented HAR model incorporating OI (HARX-RV) can generate more precise forecasts, which implies that the order imbalance measure contains substantial information for describing the volatility dynamics.Originality/valueThe study sheds light on the relation between high frequency trading behavior and volatility forecasting in China's index futures market and reveals the underlying market mechanisms of liquidity-induced volatility.

scholarly journals An Agent-Based Computational Model for China’s Stock Market and Stock Index Futures Market

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Hai-Chuan Xu ◽  
Wei Zhang ◽  
Xiong Xiong ◽  
Wei-Xing Zhou
Keyword(s):  
Market Mechanism ◽  
Stock Index ◽  
Market Model ◽  
Stock Index Futures ◽  
Volatility Clustering ◽  
Agent Based ◽  
Index Futures ◽  
Bid Ask Spread ◽  
Trading Mechanism ◽  
Index Future

This study presents an agent-based computational cross market model for Chinese equity market structure, which includes both stocks and CSI 300 index futures. In this model, we design several stocks and one index future to simulate this structure. This model allows heterogeneous investors to make investment decisions with restrictions including wealth, market trading mechanism, and risk management. Investors’ demands and order submissions are endogenously determined. Our model successfully reproduces several key features of the Chinese financial markets including spot-futures basis distribution, bid-ask spread distribution, volatility clustering, and long memory in absolute returns. Our model can be applied in cross market risk control, market mechanism design, and arbitrage strategies analysis.

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