Index-futures arbitrage and the behavior of stock index futures prices

This article examines intraday transaction data for S&P500 stock index futures prices and the intraday quotes for theunderlying index. The data indicate that the futures price changesare uncorrelated and that the variability of these price changesexceeds the variability of price changes in the S&P 500index. This excess variability of the futures over the indexremains even after controlling for the nonsynchronous pricesin the index quotes, which induces auto-correlation in the indexchanges. We advance and examine empirically two hypotheses regardingthe difference between the futures price and its theoreticalvalue: that this 'mispricing' increases on average with maturity,and that it is path-dependent. Evidence supporting these hypothesesis presented.     

Price discovery on the S&P 500 index markets: An analysis of spot index,index futures,and SPDRs

This paper investigates the price discovery function in three S&P 500 index markets: the spot index, index futures, and S&P Depositary Receipts markets. Four hypotheses regarding market structure and security design are proposed to differentiate the price discovery function performed by the three index instruments. Using matched synchronous intraday trading data, Johansen's maximum likelihood estimator is employed to disclose the cointegration relationships among the three markets. Results indicate that the three price series are a cointegrated system with one long-run stochastic trend. Estimated coefficients of the vector error correction model suggest that price adjustment takes place in the spot index market and for SPDRs, but not in the futures market. When the common stochastic trend is decomposed, it is found that the futures market serves the dominant price discovery function. The leverage hypothesis and the uptick rule hypothesis explain its superior price discovery function.     

Testing Greeks and price changes in the S&P 500 options and futures contract: A regression analysis

We use a regression model to test observed price changes with Greeks as regressors. Greeks are computed using implied volatility, price-change implied volatility and historical volatility. We find sufficient evidence to reject model Greeks as unbiased responses to underlying price as well as sufficient evidence that the American version of binomial model results in biased estimates of price changes. We use options on the S&P 500 futures contracts and their underlying. We also evaluate the frequency of “wrong signs.” Call prices and their underlying move in the opposite direction almost 10 percent of the time.     

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.

     

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.     

Market uncertainty,expected volatility and the mispricing of S&P 500 index futures

An association between increased index futures mispricing and concurrent index volatility has been reported within several prior studies; in the present study, we argue that expected volatility over an arbitrage horizon also has an adverse effect on the ability and willingness of traders to engage in arbitrage, leading to greater and more persistent futures mispricing. Using the CBOE VIX and its innovation on the concurrent spot volatility as proxies for expected volatility, we present evidence of an increase in S&P 500 index futures mispricing with expected volatility. The impact of the VIX grows exponentially across the distribution of conditional mispricing levels, which suggests that the expectations of heightened future volatility become increasingly detrimental to arbitrage activities when the futures price deviations are enlarged; however, the influence of expected volatility is found to have been reduced during the global financial crisis period, a period during which concurrent volatility overwhelmingly dominated the magnitude of mispricing.     

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.     

Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities

This study examines the joint evolution of risk-neutral stock index and bond yield volatilities by using the Chicago Board Option Exchange S&P500 volatility index (VIX) and the Bank of America Merrill Lynch Treasury Option Volatility Estimate Index (MOVE). I use bivariate regime-switching models to investigate the alternation of “high-risk” and “low-risk” markets, where the high-risk regime is characterized by higher and more volatilities with weaker cross-market linkages. Common information about economic and financial conditions appears to drive VIX and MOVE fluctuations between the two risk regimes. Two-regime specifications also distinguish between information spillover and common information effects. Ignoring regime shifts leads to spurious extreme persistence and incomplete inferences about asymmetric volatility. The findings carry important implications for asset allocation.     

Simultaneous volatility transmissions and spillover effects: U.S. and Hong Kong stock and futures markets

Contemporaneous transmission effects across volatilities of the Hong Kong Stock and Index futures markets and futures volume of trade are tested by employing a structural systems approach. Competing measures of volatility spillover, constructed from the overnight U.S. S&P500 index futures, are tested and found to impact on the Hong Kong asset return volatility and volume of trade patterns. The examples utilize intra-day 15-min sampled data from this medium-sized Asia Pacific equity and derivative exchange. Both the intra- and inter-day patterns in the Hong Kong market are allowed for in the estimation process.     

Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests

We examine whether the dynamics of the implied volatility surface of individual equity options contains exploitable predictability patterns. Predictability in implied volatilities is expected due to the learning behavior of agents in option markets. In particular, we explore the possibility that the dynamics of the implied volatility surface of individual stocks may be associated with movements in the volatility surface of S&P 500 index options. We present evidence of strong predictable features in the cross-section of equity options and of dynamic linkages between the volatility surfaces of equity and S&P 500 index options. Moreover, time-variation in stock option volatility surfaces is best predicted by incorporating information from the dynamics in the surface of S&P 500 options. We analyze the economic value of such dynamic patterns using strategies that trade straddle and delta-hedged portfolios, and find that before transaction costs such strategies produce abnormal risk-adjusted returns.     

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.     

Nonlinear tail dependence in cryptocurrency-stock market returns: The role of Bitcoin futures

We investigate the median and tail dependence between cryptocurrency and stock market returns of BRICS and Developed countries using a newly developed nonparametric cumulative measure of dependence over the period January 4, 2016 – December 31, 2019 as well as before and after the introduction of Bitcoin futures on December 17, 2017. The new measure is model-free and permits measuring tail risk. The results highlight the leading role of S&P500, Nasdaq and DAX 30 in predicting BRICS and developed countries’ stock market returns. Among BRICS countries, BVSP shows a starring role in predicting stock market returns. BSE 30 is the most predictor of cryptocurrencies, which have a little predictability on stock market returns. Ethereum has the leading role in predicting cryptocurrencies and stock market returns followed by Bitcoin. Tail dependence shows substantial role of S&P500, Nasdaq and BVSP in predicting stock market returns. Subsample analysis show the role of Bitcoin futures in reshaping the mean and tail dependence between cryptocurrency and stock market returns. Our results have important policy implications for portfolio managers, hedge funds and investors.     

Transmission of Stock Returns and Volatility between the U.S. and Japan: Evidence from the Stock Index Futures Markets

In this paper, we examine the nature of transmission of stock returns and volatility between the U.S. and Japanese stock markets using futures prices on the S&P 500 and Nikkei 225 stock indexes. We use stock index futures prices to mitigate the stale quote problem found in the spot index prices and to obtain more robust results. By employing a two-step GARCH approach, we find that there are unidirectional contemporaneous return and volatility spillovers from the U.S. to Japan. Furthermore, the U.S.'s influence on Japan in returns is approximately four times as large as the other way around. Finally, our results show no significant lagged spillover effects in both returns and volatility from the Osaka market to the Chicago market, while a significant lagged volatility spillover is observed from the U.S. to Japan. This revised version was published online in August 2006 with corrections to the Cover Date.     

Stock price synchronicity and liquidity

We argue and provide evidence that stock price synchronicity affects stock liquidity. Under the relative synchronicity hypothesis, higher return co-movement (i.e., higher systematic volatility relative to total volatility) improves liquidity. Under the absolute synchronicity hypothesis, stocks with higher systematic volatility or beta are more liquid. Our results support both hypotheses. We find all three illiquidity measures (effective proportional bid-ask spread, price impact measure, and Amihud's illiquidity measure) are negatively related to stock return co-movement and systematic volatility. Our analysis also shows that larger industry-wide component in returns improves liquidity. We find that improvement in liquidity following additions to the S&P 500 Index is related to the stock's increase in return co-movement.     

Price discovery and changes in regimes for stock index futures

In this paper, we propose a cointegration system that considers regime shifts in the stock index futures markets. Meanwhile, three such markets—the S&P, the CAC 40, and the Nikkei 225 index futures—are examined using the proposed model. The empirical evidence shows that the cointegration system with consideration of regime shifts performs better than the usual cointegration system without considering regime shifts. Moreover, the three futures markets exhibit different patterns for distinct regimes.     

General equilibrium pricing of options with habit formation and event risks

This paper proposes a general equilibrium model that explains the pricing of the S&P 500 index options. The central ingredients are a peso component in the consumption growth rate and the time-varying risk aversion induced by habit formation which amplifies consumption shocks. The amplifying effect generates the excess volatility and a large jump-risk premium which combine to produce a pronounced volatility smirk for index options. The time-varying volatility and jump-risk premiums explain the observed state-dependent smirk patterns. Besides volatility smirks, the model has a variety of other implications which are broadly consistent with the aggregate stock and option market data.     

S&P 500 Cash Stock Price Volatilities

S&P 500 stock return volatilities are compared to the volatilities of a matched set of stocks, after controlling for cross-sectional differences in firm attributes known to affect volatility. No significant difference in volatility is observed between 1975 and 1983—before the start of trade in index futures and index options. Since then, S&P 500 stocks have been relatively more volatile. The difference is statistically, but not economically, significant. The relative increase occurs primarily in daily returns and only to a lesser extent in longer interval returns. Other factors besides the start of derivative trade could be responsible for the small increase in volatility.     

Forecasting time-varying covariance with a range-based dynamic conditional correlation model

This paper proposes a range-based dynamic conditional correlation (DCC) model combined by the return-based DCC model and the conditional autoregressive range (CARR) model. The substantial gain in efficiency of volatility estimation can boost the accuracy for estimating time-varying covariances. As to the empirical study, we use the S&P 500 stock index and the 10-year treasury bond futures to examine both in-sample and out-of-sample results for six models, including MA100, EWMA_, CCC_, BEKK, return-based DCC, and range-based DCC. Of all the models considered, the range-based DCC model is largely supported in estimating and forecasting the covariance matrices.     

A Likelihood Ratio Test of Price Volatilities: Comparing Stock Index Spot and Futures

This paper uses three methods to estimate the price volatility of two stock market indexes and their corresponding futures contracts. The classic variance measure of volatility is supplemented with two newer measures, derived from the Garman-Klass and Ball-Torous estimators. A likelihood ratio test is used to compare the classic variance measure of price volatilities of two stock market indexes and their corresponding futures contracts during the bull market of the 1980s. The stock market volatilities of the Standard & Poor's 500 (S&P 500) and New York Stock Exchange (NYSE) indexes were found to be significantly lower than their respective futures price volatilities. Since information may flow faster in the futures markets than in the corresponding stock market, our results support Ross's information-volatility hypothesis. It was also noted that the NYSE spot volatility was lower than the S&P 500 spot volatility. If the rate of information flow and firm size are positively related, then the lower NYSE spot volatility is explained by the size effect. The futures price volatilities for the two indexes were insignificantly different from each other. With stock index spot-futures price correlations approaching unity, one implication of our results for index futures activity is that smaller positions in futures contracts may suffice to achieve hedging or arbitrage goals.     

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.