The Temporal Price Relationship between S&P 500 Futures and the S&P 500 Index

This paper empirically examines the intraday price relationship between S&P 500 futures and the S&P 500 index using minute-to-minute data. Three-stage least-squares regression is used to estimate lead and lag relationships with estimates for expiration days of the S&P 500 futures compared with estimates for days prior to expiration. The results suggest that futures price movements consistently lead index movements by twenty to forty-five minutes while movements in the index rarely affect futures beyond one minute.     

Using Daily High/Low Time to Test for Intraday Random Walk in Two Index Futures Markets

This paper investigates the time of the daily high/low price in the Hang Seng and S&P 500 index futures and uses it to test for deviation from the predictive behavior of an intraday random walk model. Theoretical distributions of the daily high/low time under the random walk model are derived assuming either uniform or time-varying intraday trading speed. We show that under a random walk model, daily high/low time is more likely to occur near market open/close than in the middle of the trading day. Empirical distributions of the daily high/low time are compared with its theoretical distributions to test for the random walk model. It is found that for the intraday movement of the S&P 500 futures, the random walk hypothesis cannot be rejected. However, it is discovered that in the Hong Kong market, daily high/low time tends to appear significantly more often than is predicted by the random walk model in the first 15-minute time interval when the market opens in the morning or in the afternoon. The results remain valid even after we have taken the time-varying trading speed into account. By comparing the price behavior across markets, we can better understand the microstructure of the futures market.     

INTRADAY MARKET BEHAVIOR AND THE EXTENT OF FEEDBACK BETWEEN S&P 500 FUTURES PRICES AND THE S&P 500 INDEX

In this study we empirically examine the intraday lead/lag relation between S&P 500 futures prices and the S&P 500 index, and whether daily market characteristics are associated with changes in the relation. We estimate daily Geweke measures of feedback and regress time series of these measures on daily price volatility and volume characteristics. Results indicate that the contemporaneous price relation is substantive and that measures of contemporaneous feedback are positively associated with the daily range of the futures price. The primary implication is that the relation between cash and futures prices becomes stronger as futures price volatility increases. As volatility increases, information is being impounded at a faster rate so that futures and equity markets operate more closely as one market. Large futures price moves, by themselves, are not responsible for breakdowns in the stock-futures price relation.     

Overreaction of country ETFs to US market returns: Intraday vs. daily horizons and the role of synchronized trading

In this paper we study the intraday price formation process of country Exchange Traded Funds (ETFs). We identify specific parts of the US trading day during which Net Asset Values (NAVs), currency rates, premiums and discounts, and the S&P 500 index have special effects on ETF prices, and characterize a special intraday and overnight updating structure between these variables and country ETF prices. Our findings suggest a structural difference between synchronized and non-synchronized trading hours. While during synchronized trading hours ETF prices are mostly driven by their NAV returns, during non-synchronized trading hours the S&P 500 index has a dominant effect. This effect also exceeds the one that the S&P 500 index has on the underlying foreign indices and suggests an overreaction to US market returns when foreign markets are closed.     

Futures and futures options with basis risk: theoretical and empirical perspectives

Under a no-arbitrage assumption, the futures price converges to the spot price at the maturity of the futures contract, where the basis equals zero. Assuming that the basis process follows a modified Brownian bridge process with a zero basis at maturity, we derive the closed-form solutions of futures and futures options with the basis risk under the stochastic interest rate. We make a comparison of the Black model under a stochastic interest rate and our model in an empirical test using the daily data of S&P 500 futures call options. The overall mean errors in terms of index points and percentage are ?4.771 and ?27.83%, respectively, for the Black model and 0.757 and 1.30%, respectively, for our model. This evidence supports the occurrence of basis risk in S&P 500 futures call options.     

Pinning in the S&P 500 futures

We show that Standard & Poor's (S&P) 500 futures are pulled toward the at-the-money strike price on days when serial options on the S&P 500 futures expire (pinning) and are pushed away from the cost-of-carry adjusted at-the-money strike price right before the expiration of options on the S&P 500 index (anti-cross-pinning). These effects are driven by the interplay of market makers' rebalancing of delta hedges due to the time decay of those hedges as well as in response to reselling (and early exercise) of in-the-money options by individual investors. The associated shift in notional futures value is at least $115 million per expiration day.     

A further analysis of the lead-lag relationship between the cash market and stock index futures market

The intraday lead-lag relation between returns of the MajorMarket cash index and returns of the Major Market Index futuresand S&P 500 futures is investigated. Empirical results showstrong evidence that the futures leads the cash index and weakevidence that the cash index leads the futures. The asymmetriclead-lag relation holds between the futures and all componentstocks, including. those that trade in almost every five-minuteinterval. Evidence indicates that when more stocks move together(market-wide information) the futures leads the cash index toa greater degree. This suggests that the futures market is themain source of market-wide information.     

S&P 500 trading strategies and stock betas

This paper shows that S&P 500 stock betas are overstatedand the non-S&P 500 stock betas are understated becauseof liquidity price effects caused by the S&P 500 tradingstrategies. The daily and weekly betas of stocks added to theS&P 500 index during 1985-1989 increase, on average, by0.211 and 0.130. The difference between monthly betas of otherwisesimilar S&P 500 and non-S&P 500 stocks also equals 0.125during this period. Some of these increases can be explainedby the reduced nonsynchroneity of S&P 500 stock prices,but the remaining increases are explained by the price pressureor excess volatility caused by the S&P 500 trading strategies.I estimate that the price pressures account for 8.5 percentof the total variance of daily returns of a value-weighted portfolioof NYSE/AMEX stocks. The negative own autocorrelations in S&P500 index returns and the negative cross autocorrelations betweenS&P 500 stock returns provide further evidence consistentwith the price pressure hypothesis.     

Analysis of DJIA,S&P 500, S&P 400, NASDAQ 100 and Russell 2000 ETFs and their influence on price discovery

This study examines the temporal behavior of price discovery in the spot, ETF and futures markets of the DJIA, S&P 500, S&P 400, NASDAQ 100 and Russell 2000. We document an increasing trend in the price discovery metrics of exchange traded funds for all indexes but the DJIA. Contrary to past studies, our findings show that the spot market rather than the futures market leads the price discovery. The arbitrage process that links exchange traded funds to spot prices, and not the futures prices might explain the results. This daily arbitrage that ensures exchange traded funds prices equal net asset values appear to promote spot market price discovery especially with the popularity of exchange traded funds in more recent years. We additionally document that the temporal behavior of the exchange traded funds price discovery metric affects differently price discovery in the spot and futures markets across indexes.     

An alternative approach to evaluating the agreement between financial markets

This research investigates that the price relationship between a stock index and its associated nearby futures markets can be explained by the cost-of-carry model using the concordance correlation (CC) coefficient in the US financial markets. The main purpose of this research is to confirm that the CC coefficient is an appropriate methodology to determine ex post arbitrage opportunities and to maximize ex ante arbitrage profits through the analysis of the price relationship derived from the cost-of-carry model. To increase the robustness of the results and to enable us to generalize our conclusions, this analysis is carried out in consideration of external uncertainty, including the marking-to-market procedure of futures contracts and the transaction cost on the stock index and its futures markets, under several assumptions related to the conditions of transactions. Examining transaction price data on the S&P 500 stock index and its futures markets shows that the CC coefficient gives a good result for ex ante arbitrage profits and is appropriate for analyzing the relationship between the observed stock index futures market price and its theoretical price derived from the cost-of-carry model.     

The innovations of e-mini contracts and futures price volatility components: The empirical investigation of S&P 500 stock index futures

The effect of the initiation of e-mini stock index futures (ESIFs) on the volatility components of S&P 500 stock index futures is herein investigated. The study decomposes S&P 500 stock index-related observed volatilities into unobserved fundamental volatility and transitory noise and utilizes the decomposition to test two hypotheses: the “clientele factor hypothesis” and the “information adjustment hypothesis”. The first hypothesis proposes that the ESIFs attract more noisy traders who prefer trading the friendly-size futures contracts. The second one proposes that the innovations of ESIFs improve the information flow of the futures markets. Using a stochastic volatility model, the empirical results are consistent with both of our proposed hypotheses.     

The Flash Crash: High‐Frequency Trading in an Electronic Market

We study intraday market intermediation in an electronic market before and during a period of large and temporary selling pressure. On May 6, 2010, U.S. financial markets experienced a systemic intraday event—the Flash Crash—where a large automated selling program was rapidly executed in the E‐mini S&P 500 stock index futures market. Using audit trail transaction‐level data for the E‐mini on May 6 and the previous three days, we find that the trading pattern of the most active nondesignated intraday intermediaries (classified as High‐Frequency Traders) did not change when prices fell during the Flash Crash.     

A Tale of Two Index Futures: The Intraday Price Discovery and Volatility Transmission Processes Between the China Financial Futures Exchange and the Singapore Exchange

This is the first study to examine the intraday price discovery and volatility transmission processes between the Singapore Exchange and the China Financial Futures Exchange. Using one- and five-minute high-frequency data from May to November 2011, the authors find that the Chinese Securities Index 300 index futures dominate Singapore's A50 index futures in both intraday price discovery and intraday volatility transmission. However, A50 futures contracts also make a substantial contribution (26-37 percent) to the price discovery process. These results have important implications for both traders and policymakers.     

Do economic statistics contain information to predict stock indexes futures prices and returns? Evidence from Asian equity futures markets

This research examines the impact of local and international market factors on the pricing of stock indexes futures in East Asian countries. The purpose of this paper is to present a study of the significant factors that determine the major stock indexes futures’ prices of Hong Kong, Malaysia, Singapore, South Korea and Taiwan. This study first investigates the relationships between Hang Seng Index Futures, KLCI Futures, SiMSCI Futures, KOSPI Futures, Taiwan Exchange Index Futures and local interest rates, dividend yields, local exchange rates, overnight S&P500 index and a newly constructed index, Asian Tigers Malaysia Index (ATMI). 11 years historical data of stock indexes futures and the economic statistics are studied; 10 years in-sample data are used for testing and developing the pricing models, and 1 year out-of-sample data is used for the purpose of verifying the predicted values of the stock indexes futures. Using simple linear regressions, local interest rates, dividend yields, exchange rates, overnight S&P500 and ATMI are found to have significant impact on these futures contracts. In this research, the next period close is predicted using simple linear regression and non-linear artificial neural network (ANN). An examination of the prediction results using nonlinear autoregressive ANN with exogenous inputs (NARX) shows significant abnormal returns above the passive threshold buy and hold market returns and also above the profits of simple linear regression (SLR). The empirical evidence of this research suggests that economic statistics contain information which can be extracted using a hybrid SLR and NARX trading model to predict futures prices with some degree of confidence for a year forward. This justifies further research and development of pricing models using fundamentally significant economic determinants to predict futures prices.

     

What do we know about the price spillover between green bonds and Islamic stocks and stock market indices?

This paper investigates the risk transmission, linkages, and directional predictability between green bonds, Islamic stocks, and other asset classes. Using daily data from November 2008 to August 2020, we use the Standard & Poor's (S&P) Green Bond Index to represent the green bond market and the Dow Jones Islamic World Index and the S&P Global Shariah Indices to represent Islamic stocks. The other asset classes considered include the S&P 500 Stock Composite, S&P 500 Bond, and S&P 500 Energy indices. This paper uses the novel quantile cross-spectral (coherency), the windowed scalogram difference (WSD), and the cross-quantilogram (CQ) correlation approaches. The results from the quantile coherency analysis reveal a negative spillover effect from green bond price returns to Islamic stocks in the long run, which indicates that the green bond market poses a long-run systemic risk to Islamic stocks. From the WSD analysis, the results show that the integration between green bonds and Islamic stocks, the S&P 500 Stock Composite, and the S&P 500 Bond index is weaker during volatile market conditions. The CQ correlation suggests that the dependency between green bonds and other asset returns is concentrated in the lower quantiles and that this dependency is weaker at longer lags. Our results underscore the significance of green bonds in investor portfolios as a new investment asset class.     

Index arbitrage and nonlinear dynamics between the S&P 500 futures and cash

We use a cost of carry model with nonzero transaction coststo motivate estimation of a nonlinear dynamic relationship betweenthe S&P 500 futures and cash indexes. Discontinuous arbitragesuggests that a threshold error correction mechanism may characterizemany aspects of the relationship between the futures and cashindexes. We use minute-by-minute data on the S&P 500 futuresand cash indexes. The results indicate that nonlinear dynamicsare important and related to arbitrage, and suggest that arbitrageis associated with more rapid convergence of the basis to thecost of carry than would be indicated by a linear model.     

Order flow,dealer profitability,and price formation

We analyze the dynamics of the S&P 500 futures price, finding both short- and long-run effects of order flow on price. While price moves strongly with the order flow in the short-run, the long-run impact is slightly negative, attributable to costly slippage from a hedging propensity in futures markets. We find strong evidence of a state dependence in the relation between price and order flow, using both volume and floor trader income measures as states. We also find that both the long- and short-run impacts of order flow are greater when dealer income is higher.     

Does Index Speculation Impact Commodity Prices? An Intraday Analysis

Using intraday data, we find unidirectional causality from commodity index‐linked futures to nonindex‐linked commodity futures for up to one hour which disappears when using daily data. Also, the economic significance of index‐linked to nonindex commodity transmission declines to zero within about an hour. Finally, we find that the magnitude of index‐linked to nonindex return transmission is positively related to the amount of speculation, both long and short, in S&P GSCI commodity index futures. We conclude that speculative pressures exerted by commodity index futures can impact nonindex commodities, mainly through the activity of uninformed, positive feedback traders.     

Intraday Price Discovery in the DJIA Index Markets

Abstract:  This paper explores the dynamics of price discovery between the Dow Jones Industrial Average (DJIA) index and its three derivative products: the DIAMOND exchange-traded fund (ETF), the floor-traded regular futures, and the electronically traded mini futures. Even though the American Stock Exchange is the primary listing exchange for the ETF, the analysis indicates that the electronically traded ETF on the Archipelago (ArcaEx) electronic communications network dominates the price discovery process for DIAMOND shares. The E-mini futures contribute the most to price discovery, followed by the ArcaEx DIAMOND. The DJIA index and regular futures contribute least to price discovery. The analysis is repeated using the derivatives of the S&P 500 index as a robustness check. The results indicate that multi-market trading ensures greater pricing efficiency. Informed traders favor electronic trading because of immediate and anonymous trade execution.     

Do call prices and the underlying stock always move in the same direction?

This article empirically analyzes some properties shared byall one-dimensional diffusion option models. Using S&P 500options, we find that sampled intraday (or interday) call (put)prices often go down (up) even as the underlying price goesup, and call and put prices often increase, or decrease, together.Our results are valid after controlling for time decay and marketmicrostructure effects. Therefore one-dimensional diffusionoption models cannot be completely consistent with observedoption price dynamics; options are not redundant securities,nor ideal hedging instruments - puts and the underlying assetprices may go down together.