scholarly journals The Liquidity Spillover Effects Between the Stock Index Futures and Spot Under the Fractal Market Hypothesis

2021 ◽  
Author(s):  
Jingyang Zhang ◽  
Xu Wu ◽  
Ruzhen Yan ◽  
Zhengjie Chun
Keyword(s):  
Spillover Effect ◽  
Spillover Effects ◽  
Efficient Market Hypothesis ◽  
Stock Index ◽  
Stock Index Futures ◽  
Market Theory ◽  
Index Futures ◽  
Futures Contract ◽  
Extreme Risk ◽  
Maturity Period

Abstract In recent years, the extreme risk events occurred frequently in the financial market have not only brought huge losses to investors and inflicted heavy losses on the market, but also posed a severe challenge for the traditional effective market hypothesis. These extreme risk events are often accompanied by sudden plummeting of liquidity. Different from the efficient market hypothesis(EMT), firstly, this paper studies the nonlinear fluctuation characteristics and causes of contracts with different maturity periods in China stock index futures market under the framework of fractal market theory and using the multifractal detrended fluctuation model Secondly, under the framework of the fractal market theory, the existence of the liquidity spillover effect between the stock index futures and spot is tested, the direction, intensity, and contribution of spillover between stock index futures and spot are analyzed. Finally, there is a robustness test. The study finds that both stock index futures and stock index spot in China have obvious nonlinear fractal fluctuation characteristics, and stock index futures have higher degree of multifractal, the characteristics are related to correlated multifractal and distributed multifractal; the longer the maturity period of the stock index futures contract, the lower the multifractal degree; there are significant asymmetric liquidity spillover effects between the stock index futures and spot; the multifractal degree has an important influence on the intensity and contribution of the liquidity spillover effect, and the multifractal degree is inversely proportional to the intensity of liquidity spillover and the contribution of spot to futures fluctuations.

scholarly journals Shock Transfer in Futures and Spot Markets: An Agent-Based Simulation Modelling Method

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xuan Zhou ◽  
Menggang Li
Keyword(s):  
Simulation Modelling ◽  
Futures Market ◽  
Stock Index ◽  
Market Model ◽  
Stock Index Futures ◽  
Risky Assets ◽  
Index Futures ◽  
Market Interaction ◽  
Futures Contract ◽  
Arbitrage Trading

There have been heated debates about the role of stock index futures in the financial market, especially during the crash periods. In this paper, a multiagent spot-futures market model is developed to analyze the micromechanism of shock transfer across spot and futures markets. We assume that there are two stocks and one stock index futures contract in the spot-futures market. Agents are heterogeneous, including fundamentalists, chartists, noise traders, and arbitragers. The spot market and the futures market are linked by arbitragers. The simulation results show that our spot-futures market model can reproduce various important stylized facts, including the price co-movement between stock index prices and index futures prices and the fat-tailed distribution of the returns of risky assets and the basis. Further analysis shows that when we introduce an exogenous fundamental shock to one of the stocks, the backwardation phenomenon appears in the futures market and the shock is widespread across the whole market by means of index futures. Moreover, the backwardation gradually disappears when the number of arbitragers increases. Besides, when there are few arbitragers or when there are sufficient arbitragers, shocks cannot be transferred to other stocks via the futures market, while an intermediate level of arbitrage will amplify the shock transfer and hurt market stability. These findings underscore that arbitragers play an important role in spot-futures market interaction and shock transfer, and adequate arbitrage trading during crises may help eliminate the positive basis and halt the further spread of the crises.

Price Clustering in the Nikkei 225 Stock Index Futures Contract on the SIMEX: An Intraday Empirical Analysis

2000 ◽  
Vol 03 (04) ◽  
pp. 519-533 ◽  
Author(s):  
Horace Chueh
Keyword(s):  
Financial Markets ◽  
Empirical Analysis ◽  
Futures Market ◽  
Stock Index ◽  
Stock Index Futures ◽  
Index Futures ◽  
Futures Contract ◽  
High Volatility ◽  
Price Clustering ◽  
Bid Ask Spreads

Price clustering in financial markets has been identified by previous studies. However, few studies have examined the phenomenon in the futures market. This paper presents price clustering for the Nikkei 225 stock index futures contract on the SIMEX. An extremely low percentage of odd-tick trades appears at the opening for the first trading session, while moderately low percentage occurs at the opening and the closing for the second trading session. GARCH estimation results document that the degree of price clustering increases in the periods with high volatility, bid-ask spreads, and transaction frequency. Price clustering tends to occur on the last trading day which the futures contract is to be presented. Generally, the results support the negotiation hypothesis of price clustering proposed by Harris (1991).

scholarly journals Does contract size matter for price discovery and risk management in stock index futures?

2016 ◽  
Vol 13 (3) ◽  
pp. 62-74
Author(s):  
Sangram Keshari Jena ◽  
Ashutosh Dash
Keyword(s):  
Risk Management ◽  
Price Discovery ◽  
Stock Index ◽  
Stock Index Futures ◽  
Lot Size ◽  
Open Interest ◽  
Index Futures ◽  
Futures Contract ◽  
Size Matter ◽  
The Impact

In an effort to increase the liquidity and accessibility to the investors, National Stock Exchange of India (NSE) had reduced contract size of its Nifty index futures two times from 200 to 100 and, subsequently, to 50 units. How does this change in contract size of index futures impact the informed and hedge based trading, thereby contributing to the twin objectives of price discovery and risk management, respectively? VAR model is applied to daily return volatility, volume and open interest to study the impact. Significant feedback relationship between volume and volatility following the reduction in contract size establishes the informational trading and price discovery. However, no causality from volatility to open interest implies contract size is not a determinant of hedging. But significant causality from open interest to volatility is establishing the non-informational and liquidity trading. So stock exchanges should consider the appropriate lot size before going for introducing new futures contract

scholarly journals Responses of Economic News on Asset Prices: A Study of Indian Stock Index Futures

2020 ◽  
Vol 9 (SI) ◽  
pp. 3-14
Author(s):  
Ameet Kumar Banerjee
Keyword(s):  
Stock Index ◽  
Stock Index Futures ◽  
Trading Activity ◽  
Index Futures ◽  
Economic News ◽  
Futures Contract ◽  
News Releases ◽  
The Relationship ◽  
Activity Variables

The study examines the role of economic news surprises on the volatility of the returns of the Indian Index futures market. Theoretical literature posits that news arrivals influence price discovery. In similar lines, we investigated the relationship between economic news releases, trading activity variables, and returns volatility. We find that economic news surprises and trading activity variables significantly affect returns volatility. However, among volume and news surprises, economic news surprises are much stronger informational signals, and the news surprises effects are found seemingly asymmetric in the index futures contract.

Forecasting Stock Index Futures Intraday Returns: Functional Time Series Model

2020 ◽  
Vol 24 (3) ◽  
pp. 265-271
Author(s):  
Yizheng Fu ◽  
◽  
Zhifang Su ◽  
Boyu Xu ◽  
Yu Zhou
Keyword(s):  
Time Series ◽  
Principal Component ◽  
Functional Principal Component Analysis ◽  
Stock Index ◽  
Stock Index Futures ◽  
Index Futures ◽  
Futures Contract ◽  
Functional Time Series ◽  
Functional Principal Component ◽  
Dynamic Forecasting

It is of great significance to forecast the intraday returns of stock index futures. As the data sampling frequency increases, the functional characteristics of data become more obvious. Based on the functional principal component analysis, the functional principal component score was predicted by BM, OLS, RR, PLS, and other methods, and the dynamic forecasting curve was reconstructed by the predicted value. The traditional forecasting methods mainly focus on “point” prediction, while the functional time series forecasting method can avoid the point forecasting limitation, and realize “line” prediction and dynamic forecasting, which is superior to the traditional analysis method. In this paper, the empirical analysis uses the 5-minute closing price data of the stock index futures contract (IF1812). The results show that the BM prediction method performed the best. In this paper, data are considered as a functional time series analysis object, and the interference caused by overnight information is removed so that it can better explore the intraday volatility law, which is conducive to further understanding of market microstructure.

Sign in / Sign up

Export Citation Format

Share Document