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Journal articles on the topic 'Stock index futures Australia'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Cummings, James Richard, and Alex Frino. "Tax Effects on the Pricing of Australian Stock Index Futures." Australian Journal of Management 33, no. 2 (December 2008): 391–406. http://dx.doi.org/10.1177/031289620803300209.

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2

Frino, Alex, and Andrew West. "The Lead-Lag Relationship Between Stock Indices and Stock Index Futures Contracts: Further Australian Evidence." Abacus 35, no. 3 (October 1999): 333–41. http://dx.doi.org/10.1111/1467-6281.00049.

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3

Cummings, James Richard, and Alex Frino. "Index arbitrage and the pricing relationship between Australian stock index futures and their underlying shares." Accounting & Finance 51, no. 3 (August 16, 2010): 661–83. http://dx.doi.org/10.1111/j.1467-629x.2010.00365.x.

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4

Sim, Ah-Boon, and Ralf Zurbreugg. "Intertemporal volatility and price interactions between Australian and Japanese spot and futures stock index markets." Journal of Futures Markets 19, no. 5 (August 1999): 523–40. http://dx.doi.org/10.1002/(sici)1096-9934(199908)19:5<523::aid-fut2>3.0.co;2-6.

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5

Galati, Luca, Alex Frino, and Alexander Webb. "LIQUIDITY OF FUTURES MARKETS OVER THE LAST QUARTER OF A CENTURY: TECHNOLOGY & MARKET STRUCTURE VERSUS ECONOMIC INFLUENCES." Applied Finance Letters 11, no. 1 (May 24, 2022): 52–65. http://dx.doi.org/10.24135/afl.v11i1.547.

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This study examines the major technological and market forces that have acted on the liquidity of futures markets over almost the last quarter of a century – equivalent to Professor Robert Webb’s tenor as Editor-in-Chief at the Journal of Futures Markets. We examine the impact of electronic trading replacing open outcry, the impact of high-frequency trading and co-located trading, compare the liquidity impacts of these developments with the impact of major economic events, including the Global Financial Crisis and Covid-19 Pandemic. Using a stock index futures contract traded on Australian futures exchanges as an example, we find that technological advances have had a statistically significant but almost imperceptible influence on measures of liquidity of Australian futures contracts. In contrast, economic crises, and crashes such as the Global Financial Crash and the Covid-19 crash have had a massive and sustained impact on the liquidity of futures markets. Our results suggest that liquidity effects from technological innovations, while important, remain dwarfed by those from extreme outlier events.

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6

Vuong, Ngoc Bao, and Yoshihisa Suzuki. "Does Fear has Stronger Impact than Confidence on Stock Returns? The Case of Asia-Pacific Developed Markets." Scientific Annals of Economics and Business 67, no. 2 (2020): 157–75. http://dx.doi.org/10.47743/saeb-2020-0009.

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Employing data from Australia, Hong Kong, and Japan over the period between January 2004 to December 2017, this study investigates the relationship between investor sentiment and stock returns. We analyze two reversed sentiment indicators, namely Consumer Confidence Index (CCI) and Volatility Index (VIX), in two conversing situations: low and high sentiment. The empirical evidence suggests that sentiment has a significant link with concurrent returns, but its influence seems to wipe out quickly as the little to no return predictability is detected. More importantly, we find that “investor fear gauge” (VIX) generates a more significant contemporaneous effect on market returns than investor confidence. The impact on future returns, on the contrary, is inconclusive since low CCI and VIX dominate the opposite ones most of the time.

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7

Gardner, C., S. D. Frusher, R. B. Kennedy, and A. Cawthorn. "Relationship between settlement of southern rock lobster pueruli, Jasus edwardsii, and recruitment to the fishery in Tasmania, Australia." Marine and Freshwater Research 52, no. 8 (2001): 1271. http://dx.doi.org/10.1071/mf01032.

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Puerulus catches on artificial collectors were measured monthly at four sites around Tasmania from 1991 to April 2000, with the aim of predicting future changes in recruitment to the fishery. Support for the potential of catch-rate prediction in Tasmania was provided at the two sites that have overlap of several years between indices of puerulus settlement and indices of the abundance of recruits to the fishery. At Bicheno, on the northeast coast, correlations between annual puerulus index and commercial catch rates were highly significant, with a lag of 5 years (P< 0.01). Similar interannual trends in puerulus index and estimates from a stock-assessment model of the biomass of recruits to the fishery provided additional support for a link with puerulus index. A 5-fold interannual variation in puerulus index detected at Bicheno, with a peak in 1995, was preceded by 3 years of relatively low puerulus catch. The peak in puerulus index appears to lead to an increase in the abundance of sublegal males in research sampling 3 years later. Correlation between annual measures of puerulus index and catch rate also appeared significant at King Island (P= 0.06) although data at this site had less contrast.

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8

Brennan, Michael J., and Eduardo S. Schwartz. "Arbitrage in Stock Index Futures." Journal of Business 63, S1 (January 1990): S7. http://dx.doi.org/10.1086/296491.

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9

Liu, Yixuan. "Correlation Analysis between Stock Index and Spot Index." Frontiers in Business, Economics and Management 5, no. 1 (September 1, 2022): 94–97. http://dx.doi.org/10.54097/fbem.v5i1.1472.

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Since the reform and opening up, with the continuous strengthening of China's economic strength, the continuous improvement of the financial market, and the increasing appeal of investors to avoid market risks. Since China's first stock index futures contract was listed and traded, the research on the relationship between this financial derivative and the corresponding spot market has been a hot spot in academic circles. It refers to the hot events triggered by the futures market, and it has also been widely concerned by the media, the government and the people. China's financial derivatives market is still in its infancy, the market system is not yet perfect, and the professional quality of institutions and individuals engaged in trading still lags far behind that of investors in western mature markets. How to improve the futures index market mechanism and maintain the stable operation of the market deserves the government's in-depth consideration. China's financial futures market supervision authorities should continue to vigorously promote the improvement and development of China's stock index futures market. Specific measures include: speeding up the introduction of institutional investors to participate in futures trading and cultivating mature market trading subjects; Establish an investor suitability management system to lower the entry threshold of the stock index futures market; Perfecting the risk management system of the futures market will provide the necessary risk barrier for the healthy and stable development of China's financial market.

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10

Lu, Xunfa, Kai Liu, Kin Keung Lai, and Hairong Cui. "The Relationship between Crude Oil Futures Market and Chinese/US Stock Index Futures Market Based on Breakpoint Test." Entropy 23, no. 9 (September 6, 2021): 1172. http://dx.doi.org/10.3390/e23091172.

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Combined with the B-P (breakpoint) test and VAR–DCC–GARCH model, the relationship between WTI crude oil futures and S&P 500 index futures or CSI 300 index futures was investigated and compared. The results show that breakpoints exist in the relationship in the mean between WTI crude oil futures market and Chinese stock index futures market or US stock index futures market. The relationship in mean between WTI crude oil futures prices and S&P 500 stock index futures, or CSI 300 stock index futures is weakening. Meanwhile, there is a decreasing dynamic conditional correlation between the WTI crude oil futures market and Chinese stock index futures market or US stock index futures market after the breakpoint in the price series. The Chinese stock index futures are less affected by short-term fluctuations in crude oil futures returns than US stock index futures.

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11

Wang, Rui Zhong. "Analysis of the Association for Shanghai Composite Index and Stock Index Futures." Applied Mechanics and Materials 644-650 (September 2014): 5672–75. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.5672.

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In this paper, data mining association rules algorithms and techniques for relevance Shanghai CSI 300 Shanghai Financial Futures Exchange and the Shanghai Stock Index Futures Stock Exchange Composite Index were analyzed. The results show that the futures contracts and price movements highly positive correlation exists. The author believes that between the two since it is highly positive relationship, IF way of trading and settlement transactions should be fully consistent with the way the Shanghai Stock Exchange and deliver company's stock. Thus, equal opportunity traders in futures contracts and stock traders, more conducive to the development of China's securities market.

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12

Stoll, Hans R., and Robert E. Whaley. "The Dynamics of Stock Index and Stock Index Futures Returns." Journal of Financial and Quantitative Analysis 25, no. 4 (December 1990): 441. http://dx.doi.org/10.2307/2331010.

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13

MacKinlay, A. Craig, and Krishna Ramaswamy. "Index-Futures Arbitrage and the Behavior of Stock Index Futures Prices." Review of Financial Studies 1, no. 2 (April 1988): 137–58. http://dx.doi.org/10.1093/rfs/1.2.137.

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14

Zainudin, Ahmad Danial, and Azhar Mohamad. "Cross hedging with stock index futures." Quarterly Review of Economics and Finance 82 (November 2021): 128–44. http://dx.doi.org/10.1016/j.qref.2021.08.005.

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15

Laws, Jason, and John Thompson. "Hedging effectiveness of stock index futures." European Journal of Operational Research 163, no. 1 (May 2005): 177–91. http://dx.doi.org/10.1016/j.ejor.2004.01.007.

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16

Carchano, Óscar, and Ángel Pardo. "Rolling over stock index futures contracts." Journal of Futures Markets 29, no. 7 (July 2009): 684–94. http://dx.doi.org/10.1002/fut.20373.

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17

Merrick, John J. "Portfolio insurance with stock index futures." Journal of Futures Markets 8, no. 4 (August 1988): 441–55. http://dx.doi.org/10.1002/fut.3990080405.

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18

Yadav, Pradeep K., and Peter F. Pope. "Stock index futures arbitrage: International evidence." Journal of Futures Markets 10, no. 6 (December 1990): 573–603. http://dx.doi.org/10.1002/fut.3990100603.

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19

Chan, Kalok, K. C. Chan, and G. Andrew Karolyi. "Intraday Volatility in the Stock Index and Stock Index Futures Markets." Review of Financial Studies 4, no. 4 (October 1991): 657–84. http://dx.doi.org/10.1093/rfs/4.4.657.

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20

Fan, Xuejun, and De Du. "The spillover effect between CSI 500 index futures market and the spot market." China Finance Review International 7, no. 2 (May 15, 2017): 249–72. http://dx.doi.org/10.1108/cfri-08-2016-0103.

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Purpose Focusing on the spillover effects between the CSI 500 stock index futures market and its underlying spot market during April to September 2015, the purpose of this paper is to explore whether Chinese stock index futures should be responsible for the 2015 stock market crash. Design/methodology/approach Using both linear and non-linear econometric models, this paper empirically examines the mean spillover and the volatility spillover between the CSI 500 stock index futures market and the underlying spot market. Findings The results showed the following: the CSI 500 stock index futures market has significant one-way mean spillover effect on its spot market. The volatility in CSI 500 stock index futures market also has a significant positive spillover effect on its spot stock market, and the mean value of dynamic correlation coefficient between the two market volatility is 0.4848. The spillover effect of the CSI 500 stock index futures market on the underlying spot market is significantly asymmetric, characterized by relatively moderate and slow during the period of the markets rising, yet violent and rapid during the period of the markets falling. The findings suggest that although the stock index futures itself was not the “culprit” of Chinese stock market crash in 2015, its existence indeed accelerated and exacerbated the stock market’s decline under the imperfect trading system. Originality/value Different from the existing literature mainly focusing on CSI 300 stock index futures, this paper empirically examines the impact of the introduction of CSI 500 stock index futures on 2015 Chinese stock market crash for the first time.

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21

Lee, Cheng-Few, Kehluh Wang, and Yan Long Chen. "Hedging and Optimal Hedge Ratios for International Index Futures Markets." Review of Pacific Basin Financial Markets and Policies 12, no. 04 (December 2009): 593–610. http://dx.doi.org/10.1142/s0219091509001769.

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This empirical study utilizes four static hedging models (OLS Minimum Variance Hedge Ratio, Mean-Variance Hedge Ratio, Sharpe Hedge Ratio, and MEG Hedge Ratio) and one dynamic hedging model (bivariate GARCH Minimum Variance Hedge Ratio) to find the optimal hedge ratios for Taiwan Stock Index Futures, S&P 500 Stock Index Futures, Nikkei 225 Stock Index Futures, Hang Seng Index Futures, Singapore Straits Times Index Futures, and Korean KOSPI 200 Index Futures. The effectiveness of these ratios is also evaluated. The results indicate that the methods of conducting optimal hedging in different markets are not identical. However, the empirical results confirm that stock index futures are effective direct hedging instruments, regardless of hedging schemes or hedging horizons.

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22

Wu, Maoguo, and Daimin Lu. "Volatility Spillover Effect of International Crude Oil Futures and China-Russia Stock Market: A Multivariate BEKK-GARCH Model Based on Wavelet Multiresolution Analysis." Asian Journal of Finance & Accounting 11, no. 1 (May 19, 2019): 183. http://dx.doi.org/10.5296/ajfa.v11i1.14348.

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The increasingly prominent strategic position of crude oil determines its high impact on macro-economy. The value of crude oil is reflected in the price of crude oil futures. Stock market is the barometer of macro economy. To what extent does international crude oil futures price affect stock market? China and Russia are the biggest importer and exporter of crude oil, respectively. Crude oil is of strategic value to both countries. This study empirically investigates the volatility spillover effect of international crude oil futures and China-Russia stock market from April 24th, 2015 to April 20th, 2018, based on the data of international crude oil futures prices, China-Russia stock market composite index, and industry stock index. The empirical results show that there is a short-term relationship between China-Russia stock market composite index and international crude oil futures price. The international crude oil futures price has a greater explanatory power to Russian RTS index, but a smaller explanatory power to Shanghai composite index. All industry stock indices are cointegrated with international crude oil futures prices. Except for China industry and Russia energy, the adjustment coefficient of international crude oil futures price on stock index volatility of other industries is insignificant. This study mainly studies the relationship between international crude oil futures price and the comprehensive stock index and industry stock index of China and Russia, and compares the impact of international crude oil futures price on the stock market of the largest importer and the largest exporter of crude oil to explore the linkage between crude oil futures price and stock market, and puts forward policy implications based on the empirical results.

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23

Thị Nhung, Nguyễn, Trần Thị Vân Anh, Nguyễn Tố Nga, Vương Thùy Linh, and Đinh Xuân Cường. "Price discovery and information transmission across stock index futures: evidence from VN 30 Index Futures on Vietnam’s stock market." Investment Management and Financial Innovations 16, no. 4 (December 19, 2019): 262–76. http://dx.doi.org/10.21511/imfi.16(4).2019.23.

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The introduction of the first tradable stock index futures of VN 30 is a very good signal showing that Vietnam is starting to have a high-level financial market, which brings many expectations about sustainable and safe development of its stock market. However, risk concerns of this type of derivative products have been raising with many claims since then. This article aims to provide empirical evidences to show if futures trading plays important role of price discovery and information transmission for spot market. Using daily data collected about VN 30 Index Futures, VN 30 Index, VN Index from August 10, 2017 to February 28, 2019, which is divided into three sub-periods (increase/decrease/recovery), the research verifies VN 30 Index Futures’ role of price discovery and information transmission by applying Vector Error Correction Model (VECM). Empirical findings show that there is a stable equilibrium relationship between the two series groups (including VN 30 Index Futures, VN 30 Index and VN 30 Index Futures and VN Index) during three sub-periods or spot and futures markets are integrated and synchronized. In particular, VN 30 Index Futures’ price discovery and information transmission are clearly seen when the market falls or does not change a lot.

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24

Lin, Ching-Chung, Shen-Yuan Chen, Dar-Yeh Hwang, and Chien-Fu Lin. "Does Index Futures Dominate Index Spot? Evidence from Taiwan Market." Review of Pacific Basin Financial Markets and Policies 05, no. 02 (June 2002): 255–75. http://dx.doi.org/10.1142/s021909150200078x.

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By utilizing vector error correction model (VECM) and EGARCH model, this article uses 5-minute intraday data to examine the interaction of return and volatility between Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the newly introduced TAIEX futures. VECM model shows that there exists bi-directional Granger causality between index spot and index futures markets, but spot market plays a more important role in price discovery. The results of impulse response function and information share indicate that most of the price discovery happens in index spot market. The evidence of EGRACH shows that the impacts of spot and futures innovations are asymmetrical, and the volatility spillovers between spot and futures markets are bi-directional. However, the information flow from spot to futures is stronger. These results suggest that the TAIEX spot market dominates the TAIEX futures market in terms of return and volatility.

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25

Oh, Se Kyung. "Intraday Volatility in the Korean Stock Ind and Korean Stock Index Futures Markets." Journal of Derivatives and Quantitative Studies 10, no. 1 (May 31, 2002): 55–80. http://dx.doi.org/10.1108/jdqs-01-2002-b0003.

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This paper tries to find the information flow between KOSPI200 Index and KOSPI200 Futures more accurately by considering two models. First, three-stage least-squares regression is used to estimate lead and lag relationships based on the representation of a simultaneous-equations model because futures and cash returns may affect each other contemporaneously. Secondly, a bivariate GARCH model is used because the lead-lag relationships between the two markets should consider not only return itself but also return volatility. The results from the first regression suggest that KOSPI200 futures returns and the index are simultaneously related and that the lead from futures to cash returns extends for about 40 minutes and the lead from cash to futures returns extends for about 30 minutes, which means the lead-lag relationship between the two markets are not unidirectional. I find from the analysis of a bivariate GARCH model that the information flow between the two markets is rather symmetrical when the volatility relationships are also considered, although it seems non-symmetrical when the returns relationships alone are considered. I also find a much stronger dependence in both directions in the volatility of returns between the cash and futures markets than that observed in the returns alone. When I consider intraday volatility as well in the lead-lag relationship between the two markets, KOSPI200 futures markets strongly lead index markets but KOSPI index do not lead futures markets. Evidence also suggests strong intermarket dependences in the conditional volatilities and in the return shocks. So the results have implications for understanding the pattern of information flows between the two markets.

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26

Shi, GuangWei, and Yun Chen. "High-Frequency Trading and Its Impact on Exogenous Liquidity Risk of China’s Stock Index Futures Market before and after Trading Restrictions." Complexity 2020 (August 27, 2020): 1–11. http://dx.doi.org/10.1155/2020/9192841.

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Since China’s first stock index futures, China Securities Index 300 (CSI300) stock index futures were published in 2010, and China’s stock index futures market is now in a period of rapid development and play a key role in price discovery. During 2014 to 2015, China’s stock index futures market fluctuated abnormally, and the overuse of high-frequency trading (HFT) strategies in the stock index futures market was blamed as the main reason of the abnormal volatility. To lower down market fluctuation, the regulatory institute then announced a series of trade restriction policy to prevent the overuse of HFT behaviour. However, until now, the impact of such trade restriction policy for HFT remains uncertain. To tackle this issue, based on minute-level HFT data from the CSI 300 index futures market, this paper aims to investigate the relationship between HFT and the exogenous liquidity risk and how HFT affects China’s stock index futures market on its liquidity using the liquidity-adjusted value at risk (LVaR) model. The findings indicate that HFT improves the return of the liquidity provider and reduces the exogenous liquidity risk significantly.

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27

Chen, Ruoyang, and Bin Pan. "Chinese Stock Index Futures Price Fluctuation Analysis and Prediction Based on Complementary Ensemble Empirical Mode Decomposition." Mathematical Problems in Engineering 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/3791504.

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Since the CSI 300 index futures officially began trading on April 15, 2010, analysis and predictions of the price fluctuations of Chinese stock index futures prices have become a popular area of active research. In this paper, the Complementary Ensemble Empirical Mode Decomposition (CEEMD) method is used to decompose the sequences of Chinese stock index futures prices into residue terms, low-frequency terms, and high-frequency terms to reveal the fluctuation characteristics over different time scales of the sequences. Then, the CEEMD method is combined with the Particle Swarm Optimization (PSO) algorithm-based Support Vector Machine (SVM) model to forecast Chinese stock index futures prices. The empirical results show that the residue term determines the long-term trend of stock index futures prices. The low-frequency term, which represents medium-term price fluctuations, is mainly affected by policy regulations under the analysis of the Iterated Cumulative Sums of Squares (ICSS) algorithm, whereas short-term market disequilibrium, which is represented by the high-frequency term, plays an important local role in stock index futures price fluctuations. In addition, in forecasting the daily or even intraday price data of Chinese stock index futures, the combination prediction model is superior to the single SVM model, which implies that the accuracy of predicting Chinese stock index futures prices will be improved by considering fluctuation characteristics in different time scales.

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28

Zhang, Qian. "Price Discovery on Stock Index Futures markets under Extreme Events: Evidence from China." European Scientific Journal, ESJ 14, no. 25 (September 30, 2018): 190. http://dx.doi.org/10.19044/esj.2018.v14n25p190.

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In this paper, the price discovery function of stock index futures for spot stock index is studied in view of the soaring and plunging periods of Chinese stock market in recent years. We use the VECM model to do empirical research under periods of stationary, boom and slump. The results show that there is a long-term relationship between CSI 300 index and CSI 300 index futures. During the stable period of Chinese stock market, the CSI 300 stock index futures are sensitive to the short-term impact, and its ability of price discovery is obviously. However, during the period of boom and collapse, the price discovery function of CSI 300 index futures is weak.

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29

Halford, Richard. "The Art of Trading Stock Index Futures." Journal of Investing 6, no. 3 (August 31, 1997): 87–93. http://dx.doi.org/10.3905/joi.1997.408430.

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30

Junkus, Joan C., and Charles M. S. Sutcliffe. "Stock Index Futures: Theories and International Evidence." Journal of Finance 49, no. 1 (March 1994): 366. http://dx.doi.org/10.2307/2329153.

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31

Horan, Stephen M. "Asian Stock Index Futures: Enhancing Portfolio Performance." CFA Digest 30, no. 1 (February 2000): 91. http://dx.doi.org/10.2469/dig.v30.n1.636.

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32

Maberly, Edwin D., David S. Allen, and Roy F. Gilbert. "Stock Index Futures and Cash Market Volatility." Financial Analysts Journal 45, no. 6 (November 1989): 75–77. http://dx.doi.org/10.2469/faj.v45.n6.75.

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33

Miwa, Kotaro. "Stock Futures of a Flawed Market Index." Asia-Pacific Financial Markets 26, no. 1 (November 7, 2018): 1–21. http://dx.doi.org/10.1007/s10690-018-9253-6.

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34

Clare, Andrew D., Michalis Ioannides, and Frank S. Skinner. "Hedging Corporate Bonds with Stock Index Futures." Journal of Fixed Income 10, no. 2 (September 30, 2000): 25–34. http://dx.doi.org/10.3905/jfi.2000.319269.

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35

Bhatt, Swati, and Nusret Cakici. "Premiums on stock index futures-some evidence." Journal of Futures Markets 10, no. 4 (August 1990): 367–75. http://dx.doi.org/10.1002/fut.3990100405.

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36

Rougier, Jonathan. "An optimal price index for stock index futures contracts." Journal of Futures Markets 16, no. 2 (April 1996): 189–99. http://dx.doi.org/10.1002/(sici)1096-9934(199604)16:2<189::aid-fut4>3.0.co;2-g.

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37

Tosini, Paula A. "Stock Index Futures and Stock Market Activity in October 1987." Financial Analysts Journal 44, no. 1 (January 1988): 28–37. http://dx.doi.org/10.2469/faj.v44.n1.28.

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38

Hancock, G. D. "Futures option expirations and volatility in the stock index futures market." Journal of Futures Markets 11, no. 3 (June 1991): 319–30. http://dx.doi.org/10.1002/fut.3990110306.

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39

Hui, GAO, and GAO Tian Chen. "Crude Oil Price Shocks and Stock Market Volatility: Evidence From China." Review of European Studies 14, no. 4 (October 30, 2022): 39. http://dx.doi.org/10.5539/res.v14n4p39.

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As the first international futures variety in China, crude oil futures, its price influence and function play has attracted much attention at home and abroad, from the perspective of market performance, crude oil futures have had a greater impact on the capital market since its launch, and what needs to be further studied is the quantitative degree and complexity of the impact of crude oil futures price fluctuations on stock market fluctuations. The daily data from March 26, 2018 to July 5, 2022 were selected to study the influence of domestic crude oil futures prices on domestic Shanghai and Shenzhen stock index by Granger causality, cointegration test and smooth transition regression model. The study shows that the price and yield of domestic crude oil futures have a one-way guiding effect on the domestic Shanghai and Shenzhen stock indexes and yields, but their guiding effect on the Shenzhen component index is greater than that of the Shanghai Composite Index. Domestic crude oil futures prices and Shanghai and Shenzhen stock indexes have a long-term similar negative cointegration relationship. The positive and negative impact of the domestic crude oil futures price yield on Shanghai and Shenzhen stock index yields is non-linear and asymmetrical, but the mechanism of impact on the two stock markets is different, for the Shanghai stock market, the negative impact of the crude oil futures price yield is greater than the positive shock impact, for the Shenzhen stock market, the positive impact of the crude oil futures price yield is greater than the negative shock impact, and the impact on both stock markets was limited .Therefore, for domestic crude oil futures to become the global crude oil price benchmark, they also need to be continuously improved in terms of national policies, industry supervision, exchange rules and market system construction.

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40

Wan, Yinglin. "The Impact of Stock Index Futures on the Information Environment of Listed Firm: Evidence from Chinese Listed Firms." International Journal of Business and Management 13, no. 5 (April 18, 2018): 147. http://dx.doi.org/10.5539/ijbm.v13n5p147.

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We investigate the impact of stock index futures on the information environment of listed firms through the launch of Shanghai-Shenzhen 300 stock index futures (CSI 300 index) as natural experiment on April 16, 2010. We employ difference in difference analysis and apply the PIN indicator (the probability of informed trading) to measure information asymmetry. We found that the CSI 300 index significantly reduce the information asymmetry of CSI 300 companies. For the companies with higher market capitalization, higher turnover rate and higher institutional investor’s rate, the impact of stock index future on the corporate information environment is more significant. The results of this paper provide new evidence for evaluating the impacts of Chinese stock index futures.

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41

Wang, Janchung, and Hsinan Hsu. "Price Expectation and the Pricing of Stock Index Futures: Evidence from Developed and Emerging Markets." Review of Pacific Basin Financial Markets and Policies 09, no. 04 (December 2006): 639–60. http://dx.doi.org/10.1142/s0219091506000884.

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This study examines how well the pricing model of Hsu and Wang (2004) explains the behavior of stock index futures prices for the developed markets (such as the S&P 500 index futures market) and the emerging markets (such as the Taiwan Futures Exchange (TAIFEX) Taiwan stock index futures market). It also compares the pricing performance of three alternative pricing models of stock index futures: the cost of carry model, the Hemler and Longstaff (1991) model, and the Hsu–Wang model. Overall, the Hsu–Wang model provides significantly better pricing performance than that of the cost of carry model in emerging markets with high degrees of imperfection. Moreover, this study also observes that the Hemler and Longstaff (1991) model performs better than the cost of carry model in estimating prices of the TAIFEX futures, suggesting that the incorporation of stochastic market volatility is beneficial to predict the TAIFEX futures prices.

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Chang, Eric C., Joseph W. Cheng, and J. Michael Pinegar. "Does futures trading increase stock market volatility? The case of the Nikkei stock index futures markets." Journal of Banking & Finance 23, no. 5 (May 1999): 727–53. http://dx.doi.org/10.1016/s0378-4266(98)00069-7.

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Ryoo, Hyun-Jung, and Graham Smith. "The impact of stock index futures on the Korean stock market." Applied Financial Economics 14, no. 4 (February 20, 2004): 243–51. http://dx.doi.org/10.1080/0960310042000201183.

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44

Martikainen, Teppo, Jukka Perttunen, and Vesa Puttonen. "ON THE DYNAMICS OF STOCK INDEX FUTURES AND INDIVIDUAL STOCK RETURNS." Journal of Business Finance & Accounting 22, no. 1 (January 1995): 87–100. http://dx.doi.org/10.1111/j.1468-5957.1995.tb00673.x.

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45

Wang, Janchung. "Stock market volatility and the forecasting performance of stock index futures." Journal of Forecasting 28, no. 4 (July 2009): 277–92. http://dx.doi.org/10.1002/for.1101.

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Yang, Zhuoyi, Xiong Xiong, Lijian Wei, Yian Cui, and Li Wan. "The Behavior and Impact of Heterogeneous Investors in China’s Stock Index Futures Market: An Agent-Based Model on Cross-Market Trades." Complexity 2022 (September 27, 2022): 1–12. http://dx.doi.org/10.1155/2022/9439957.

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Since the period of unusual volatility in China’s A-share market in 2015, there has been an ongoing discussion about the role of stock index futures in the A-share market. There is no unified consensus among academics and industry insiders on whether stock index futures affect spot market volatility. Using agent-based modeling, we construct a theoretical model of the order book of the stock index futures market to assess the microbehavior of speculators, arbitrageurs, and hedgers in this market. We then calibrate the link between the futures and spot models to explore the respective influences of heterogeneous investors in the two markets. We find that speculators, arbitrageurs, and hedgers all play different roles and have varying effects on the two markets. While speculators serve as the foundation for other investors to participate in trading activities, both arbitrageurs and hedgers affect the spot market by significantly reducing volatility, enhancing price efficiency, and playing a positive role in the operation of this market. We develop our model from the perspective of investor behavior and explain why the stock index futures market can reduce spot market volatility. In addition, our conclusion may help regulators understand the roles played by different types of investors in the Chinese stock index futures market.

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Wang, Ning, Yibo Chen, and Bo Wang. "Normality of the Stock Index Futures of China." Journal of Mathematical Finance 08, no. 01 (2018): 86–101. http://dx.doi.org/10.4236/jmf.2018.81007.

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Fielitz, Bruce D., and Gerald D. Gay. "Managing cash flow risks in stock index futures." Journal of Portfolio Management 12, no. 2 (January 31, 1986): 74–78. http://dx.doi.org/10.3905/jpm.1986.409048.

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Kawaller, Ira G., and Timothy W. Koch. "Managing cash flow risk in stock index futures." Journal of Portfolio Management 15, no. 1 (October 31, 1988): 41–44. http://dx.doi.org/10.3905/jpm.1988.409183.

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Miller, Merton H., Burton Malkiel, Myon Scholes, and John D. Hawke. "STOCK INDEX FUTURES AND THE CRASH OF '87." Journal of Applied Corporate Finance 1, no. 4 (January 1989): 6–17. http://dx.doi.org/10.1111/j.1745-6622.1989.tb00170.x.

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