Index Futures Market Research Articles

The impact of stock index futures margin levels on market quality

We examine the impact of margin levels on market quality in the China Shanghai–Shenzhen 300 (CSI 300) Stock Index Futures market. Utilizing microstructure theory and the OPOK model, we specifically focus on volatility, liquidity, and effectiveness. Our findings reveal that lowering the margin level for stock index futures reduces capital constraints for both informational and non-informational traders. Furthermore, we show that a reduction in margin levels enhances market liquidity and effectiveness. Improvements in liquidity and effectiveness subsequently reduce market volatility, indicating that a decrease in margin levels does not necessarily increase market risk. Based on these results, we recommend setting margins for stock index futures with comprehensive consideration of their combined effects on volatility, liquidity, and effectiveness.

Left‐digit biases: Individual and institutional investors

AbstractThis study examines the left‐digit bias of individual and institutional investors using the microstructural data set from a highly liquid index futures market. Both investor groups exhibit excess buying after the ask falls with a tens‐digit decrement, whereas excess selling (buying) is observed only for institutions (individuals) after the bid rises with a tens‐digit increment. Such excess buying is generally pronounced when price uncertainty is high. Institutional excess selling is evident when uncertainty is low and immediately after the market opens. While both investor groups focus on cognitive reference points, our findings imply that investors heterogeneously respond to the bias and that individuals experience investment losses as they trade on the bias.

Optimal and Non-Optimal MACD Parameter Values and Their Ranges for Stock-Index Futures: A Comparative Study of Nikkei, Dow Jones, and Nasdaq

This study investigates the optimal and non-optimal parameter values of the MACD (Moving Average Convergence Divergence) technical analysis indicator for three major stock market index futures: the Nikkei 225, the Dow Jones, and the Nasdaq. Using a recently developed methodology, it reveals the existence of specific ranges of optimal and non-optimal values for each of the three parameters of the MACD indicator in these indices. Sample models employing the optimal parameter values in the three index futures generated significantly higher returns, outperforming both a non-technical buy-and-hold strategy and a random strategy that did not incorporate any market information. This discovery suggests that the three market indices may not be weak-form efficient. Therefore, this study contributes to the research on market efficiency by verifying inefficiency using a new approach. The highlight of this study is identifying that the ranges of optimal parameter values for the three indices are different from each other, but the optimal parameter value combinations for each of the three indices share a unique characteristic form. This issue and its finding have not been explored in the existing literature. Several interesting findings and valuable insights for market participants and researchers arise from this study. The new methodology is unique in finding optimal and non-optimal parameter values through the analysis of parameter sets used in well-performing and poorly performing sample models. Its validity and reliability have been confirmed by this study, making a useful contribution to the field of technical analysis research, particularly in parameter optimization insight.

Investor sentiment and futures market mispricing

We examine the effects of sentiment on mispricing in a highly liquid index futures market. Investor sentiment significantly affects futures mispricing, supporting its role in explaining price dynamics. Overly optimistic sentiment induces futures market overvaluation whereas pessimistic sentiment loses its explanatory power in undervaluation after controlling for trading activities and macroeconomic factors. The sentiment effect is more pronounced when noisy individual trading prevails.

Modeling Symmetric and Asymmetric Volatility in Nifty 50 Index Futures Market

Volatility in stock markets is a matter of concern for investors and policymakers across the world. Derivatives enable traders to manage risk arising out of volatility through hedging and arbitrage (Singh & Kansal, 2010). During times of high volatility, regulatory authorities step in to curb the frenzied activity in the stock market. Time series data of financial nature shows non-normality traits. Thus, it is essential to check whether distributions other than normal distribution can perfectly analyze the time series data. Therefore, it becomes important to use the appropriate methods to model volatility. This study aims to analyse both symmetric and asymmetric volatility in Nifty 50 futures markets. Different variants of GARCH models were used in the study under three probability distributions such as normal, Student’s-t, and generalized error distribution (GED). EGARCH (1,1) model with Student’s- t distribution proved to be the best model for capturing volatility as it had the lowest AIC value. The results detected the presence of a leverage effect and thereby confirmed that negative news created more volatility than positive news.

Unspanned macro risks in VIX futures

AbstractThis study investigates hidden factors in the volatility index (VIX) futures market. Risk factors spanned by the futures curve have a limited ability to capture variations in the expected excess returns. The market's hidden factors provide additional predictive power for future returns in addition to that provided by the factors spanned by the futures curve. The use of a dynamic term structure model with these hidden factors indicates that the hidden factors as a proxy for macro risks materially impact the VIX futures returns and their yield term structure and are significantly helpful in depicting the dynamics of the risk premia.

Do IOC Orders Improve the Market Quality? Evidence from the KOSPI 200 Futures Market

This study investigates the effect of IOC (immediate-or-cancel) orders on market quality, such as time to execution, volatility, quote spread, and market depth, in the KOSPI 200 index futures market. Analysis of the order flow imbalance indicates that IOC orders, accounting for 50% of trades in the futures market, leads more price impact than non-IOC,. Additionally, the IOC orders, mostly submitted by foreign investors, and simultaneously by multiple traders in the form of herding, incur negative impact on the market quality in the aspect of market volatility, quote spread, and market depth. However, IOC orders have the positive effect of reducing the time to execution.

International linkages of emerging market index futures, under the closure of underlying spot market – evidence from Indian Nifty futures

PurposeThis study examines the dynamic linkages between the Indian Nifty index futures traded on the offshore Singapore Exchange (SGX) and US stock indices (DJIA, NASDAQ and S&P 500) under the closure of the spot market for Nifty futures.Design/methodology/approachWith high-frequency 5-min overlapping price data, the authors employ the Johansen cointegration test to investigate long-run relationships, the Granger causality test to assess short-run dynamics and the BEKK-GARCH model for volatility spillover investigation.FindingsThe empirical findings reveal that the SGX Nifty futures market is cointegrated with the US DJIA market. The US DJIA stock index strongly influences the price discovery of SGX Nifty futures and past innovations in the US markets strongly impact the current volatility of SGX Nifty futures.Practical implicationsFindings from this study have significant implications for market participants, particularly foreign investors and portfolio managers. These findings might be helpful for market participants to improve the prediction power of expected SGX Nifty futures price and volatility, especially under the closure of the spot market. Also, SGX market participants can take the significant role of the US market into account when formulating hedging and trading strategies with Indian Nifty futures. Besides, our findings have significant implications for policymakers in evaluating market stability.Originality/valueThis article adds to the very limited research on offshore or international stock index futures; it is the first study that empirically examines the international linkages of offshore SGX Nifty futures under the closure of its underlying spot market and also the driving force behind the linkages.

Algorithmic trading and market quality: Evidence from the Taiwan index futures market

AbstractThis study examines the effects of different algorithmic traders on market quality and the price discovery process, considering the impact of different trading strategies and market conditions. Algorithmic foreign institutions and proprietary firms act strategically, by monitoring market conditions. During stable market conditions, they supply liquidity, and this strategic activity both improves price efficiency and increases fundamental volatility. In more turbulent market conditions, algorithmic foreign institutions and proprietary firms instead demand liquidity, and their trading activity leads to an increase in price efficiency and a decrease in excessive volatility. Overall, algorithmic trades do not harm market quality.

Real-Trading-Oriented Price Prediction With Explainable Multiobjective Optimization in Quantitative Trading

Price prediction using machine learning is a heated topic and an effective task in quantitative trading. However, the objectives that existing researches focus on are typically naive and can hardly express the diverse properties in real trading, by using which the results of price prediction cannot precisely reflect the returns in real trading. To alleviate this problem, we first formulate the characteristics of transactions and then propose a multi-objective method under a real-trading-oriented perspective, where a tree model inducing explainable trading characteristics is proposed. With lots of considerations of real trading characteristics, the results of price prediction can better obtain the properties in trading, and especially perform quite well in real trading. Multiple experiments on the Chinese Index Future Market display the effectiveness of the proposed model, where the performance of real trading has reached the industry-leading level. In particular, the difference between model prediction and returns in real trading can be diminished.

The Behavior and Impact of Heterogeneous Investors in China’s Stock Index Futures Market: An Agent‐Based Model on Cross‐Market Trades

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.

The Informational Response of Different Investor Types on Futures Return Fluctuations: Evidence from Taiwan’s Index Futures Market

This article examines the price impact of different types of investors' trading activities in the Taiwan index futures market on the market, and explores the information roles of different types of investors. We find the trading volumes of different investors in the index futures market affect futures returns through information. The impact on index futures returns in the current period is small, showing the ability of foreign institutional investors to quickly respond to negative news and obtain information advantages. Further, from the MSE and QLIKE loss functions, individual investors use EGARCH(1,1), domestic institutional investors TGARCH(1,1), and foreign institutional investors GARCH(1,1). Further, the imbalance of buy and sell orders is suitable for the fluctuation of futures returns using EGARCH(1,1).

The Relationship between Crude Oil Futures Market and Chinese/US Stock Index Futures Market Based on Breakpoint Test.

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.

The Price Discovery Processes in China, India, and Russia’s Stock Index Futures Markets

In this paper, we examine the price discovery patterns in the three BRICS countries’ stock index futures markets which were launched after 2000 – China, India, and Russia. We find the futures market dominates the price discovery process in China and India, but less so in Russia. A closer examination reveals the dynamic nature of the price discovery process, and the significant impacts on futures’ price discovery functions from China’s regulatory changes in September 2015 and Russia’s economic sanctions in March 2014. The results also show a more balanced and bidirectional volatility spillover between futures and spots in China and India than in Russia.

Information Transmission between China’s IH and SGX FTSE A50 Stock Index Futures Markets: The Role of Trading Restrictions

ABSTRACT After China’s stock market crash in 2015, the Chinese government imposed a series of trading restrictions on the stock index futures market. This paper examines how the relative informational role of China’s IH stock index futures and the SGX FTSE China A50 index futures varies when market trading mechanisms are subject to these major changes. We find that imposing the trading restrictions on IH futures substantially undermines their role in price discovery and volatility spillover, and renders them more susceptible to the fluctuations of A50 futures. Importantly, even after the trading restrictions are greatly eased at a later date, the importance of IH futures in price discovery and volatility spillover relative to that of A50 futures remains at a level much lower than before. Changes in liquidity and trading volumes imply that imposing the trading restrictions on IH futures drives investors to flee the IH futures market, but relaxing these restrictions is not able to attract investors back, making it difficult for IH futures to resume its important role in information transmission.

Currency and Index Futures Markets Dynamics: Asymmetric Volatility, Leverage Effects and Long-memory Characteristics

This research examines the performance of return and volatility models on the long-memory, asymmetric volatility, and leverage effects by comparing the two most active futures markets globally, Currency and Index Futures. The study uses daily data from the database Quandl.com website, from January 2000 to March 2018. This study utilizes two short-memory models, the autoregressive moving average – exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH); and autoregressive moving average – asymmetric power autoregressive conditional heteroskedasticity (ARMA-APARCH); and two long-memory models, autoregressive fractionally-integrated moving average – fractionally-integrated exponential generalized autoregressive conditional heteroskedasticity (ARFIMA-FIEGARCH); and autoregressive fractionally-integrated moving average – fractionally-integrated asymmetric power autoregressive conditional heteroskedasticity (ARFIMA-FIAPARCH). The paper shows that portfolio managers and traders can benefit in holding Index futures, because of their steady returns, but with a relatively higher risk for the whole sample period. The study also finds that Currency futures has better safe-haven properties during crisis period, but Index futures performs better after crisis period. Findings suggest that both long-memory models are capable of accurate forecast, especially on the volatility of Currency and Index futures. The proper modelling of Currency and Index futures time-series data can provide traders, fund managers and investors in creating well-defined trading strategies, especially in high volatility regimes.

How does news flow affect cross-market volatility spillovers? Evidence from China’s stock index futures and spot markets

This paper examines how news flow affects cross-market volatility spillovers and price discovery process in China’s stock market and index futures market. We find robust evidence confirming dominant predicting power of the stock market in the price discovery process, and presence of asymmetric and persistent volatility effects. The results show that volatility spillovers are bidirectional between stock index futures and spot prices, and news release has significant and positive association with the dynamic conditional correlation between the index spot and the index futures markets. These have important implications for effective hedging and portfolio management decision in emerging markets.

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

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.

Research on the Relative Trading Volume by Remaining period and Investor Types in the KOSPI200 Index Futures market.

Research on the Relative Trading Volume by Remaining period and Investor Types in the KOSPI200 Index Futures market.

High-Frequency Trading and Its Impact on Exogenous Liquidity Risk of China’s Stock Index Futures Market before and after Trading Restrictions

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.