Intraday Lead-Lag Relationships Between the Futures-, Options and Stock Market

In rational, efficiently functioning and complete markets, returns on derivative and underlying securities should be perfectly contemporaneously correlated. Due to market imperfections, one of these markets may reflect information faster. The use of high-frequency data and the choice for a small unit time interval to measure these lead-lag relations comes at the cost of some or many missing observations, causing traditional estimators to either under- or overestimate covariances and correlations. We use a new estimator to estimate lead-lag relationships between the cash AEX index, options and futures. We find that futures returns lead both options and cash index returns by approximately 10 minutes. The relationship between options and the cash market is not completely unidirectional.     

The Lead-Lag Relation Between Spot and Futures Markets Under Different Short-Selling Regimes

We examine the lead‐lag relation between index futures and the underlying index under three types of short‐selling restrictions on stocks in Hong Kong. Our results indicate that lifting short‐selling restrictions can enhance the informational efficiency of the stock market relative to the index futures. We also investigate the impact of two market characteristics, market conditions and the magnitude of mispricing on the lead‐lag relations under different short‐selling regimes. Our findings suggest that if we remove restrictions, the contemporaneous price relation between the futures and cash markets becomes stronger particularly in the falling market and when the cash market is relatively overpriced.     

The effects of newly listed derivatives in a thin stock market

This study examines the informational feedback effects associated to the listing and trading of derivatives in Switzerland. The observed changes in the price and higher moments of stock returns are representative of a thin stock market. The listing of stock options and index futures generated positive abnormal returns for large stocks and for the index while small stocks essentially benefited from the launching of index options. While reducing the variance of blue chips and of the index, their variance's stochasticity increased (decreased) at index options' (futures) listings. Finally, we detect significant stock and index derivatives' price leads which do not however generate arbitrage opportunities.     

The lead–lag relationship between the spot and futures markets in China

Based on daily and one-minute high-frequency returns, this paper examines the lead–lag dependence between the CSI 300 index spot and futures markets from 2010 to 2014. A nonparametric and non-linear method based on the thermal optimal path method is adopted. Empirical results of the daily data indicate that the lead–lag relationship between the two markets is within one day but this relationship is volatile since neither of the two possible situations (the futures leads or lags behind the spot market) takes a dominant place. Our results using the high-frequency data demonstrate that there is a price discovery in the Chinese futures market: the intraday one-minute futures return leads the cash return by 0–5 min regardless of the price trend of the market.     

The Lead‐Lag Relationship Between Cash and Stock Index Futures in a New Market

This paper investigates the lead‐lag relationship in daily returns and volatilities between price movements of the FTSE/ATHEX‐20 and FTSE/ATHEX Mid‐40 stock index futures and the underlying cash indices in the relatively new futures market of Greece. Empirical results show that there is a bi‐directional relationship between cash and futures prices. However, futures lead the cash index returns, by responding more rapidly to economic events than stock prices. This speed is much higher in the more liquid FTSE/ATHEX‐20 market. Moreover, results indicate that futures volatilities spill information over to the corresponding cash market volatilities in both investigated futures markets, but volatilities in the cash markets have no effect on the volatilities of futures markets. Overall, it seems that new market information is disseminated faster in the futures market compared to the stock market. This implies that the futures markets can be used as price discovery vehicles, providing further evidence that derivatives markets contribute to completing and stabilising capital markets in Greece. A further finding of this study is that futures volume and disequilibrium effects between cash and futures prices are important variables in the explanation of volatilities in cash and futures markets.     

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.     

Trading activity in the equity market and its contingent claims: An empirical investigation

Little is known about the joint dynamics of volume across the various contingent claims on the equity market. We study the time-series of trading activity in the cash S&P 500 index and its derivatives (options, the legacy and E-mini futures contracts, and the ETF), and consider their dynamic relation with the macroeconomy, over more than 3000 trading days during 1997–2009. Legacy futures volume has trended downward while other series have trended upward. Total futures volume has increased, suggesting that the trading in the legacy contract has been at least partially supplanted by trading in the E-mini contract. All series are highly cross-correlated and jointly dependent. Signed and absolute trading activity in contingent claims (most prominently, options) predicts shifts in aggregate state variables such as the short interest rate, and the term and credit spreads, as well as signed and absolute returns around major macroeconomic announcements. Overall, consistent with the informational role of options, their volume innovations have the strongest forecasting ability for fluctuations in the macroeconomic environment.     

Intraday Lead-Lag Relationships Between the Futures-, Options and Stock Market

In rational, efficiently functioning and complete markets, returnson derivative and underlying securities should be perfectlycontemporaneously correlated. Due to market imperfections, oneof these markets may reflect information faster. The use ofhigh-frequency data and the choice for a small unit time intervalto measure these lead-lag relations comes at the cost of someor many missing observations, causing traditional estimatorsto either under- or overestimate covariances and correlations.We use a new estimator to estimate lead-lag relationships betweenthe cash AEX index, options and futures. We find that futuresreturns lead both options and cash index returns by approximately10 minutes. The relationship between options and the cash marketis not completely unidirectional. JEL Classification: G13, G14     

An Examination of Stock Market Return Volatility During Overnight and Intraday Periods, 1964–1989

This paper examines the variance of hourly market returns during 1964–1989. Results indicate that return volatility falls from the opening hour until early afternoon and rises thereafter and is significantly greater for intraday versus overnight periods. Market variance is also shown to change significantly over time, rising after NASDAQ began in 1971, rising after trading in stock options began in 1973, falling after fixed commissions were eliminated in 1975, rising after trading in stock index futures was introduced in 1982, and falling after margin requirements for stock index futures became larger in 1988.     

Futures trading volume as a determinant of prices in different momentum phases

Recent studies contend that trading volume has predictive power for ex ante stock prices, particularly small stocks that do not react quickly to macroeconomic information. This study postulates that a significant amount of macro-information that flows on to stock markets is derived from derivative markets. We examine the impact of short-term futures trading volume and prices on cash stock prices using a case study of 15-min data from the Australian stock index futures market which reports actual trading volume. After applying vector error correction modelling (VECM), variance decomposition and impulse functions, we conclude that futures prices provide a short-term information lead to stock prices that dominates trading volume effects. We also observe asymmetric changes in the impact of trading volume between bull and bear price momentum phases and after large trading volume shocks. These results suggest that, in future, studies on trading volume should control for the cross-correlation impact from derivative prices and the differential impact of trading phases.     

Informed Futures Trading and Price Discovery: Evidence from Taiwan Futures and Stock Markets

This article focuses on the information effects between the futures market and its spot market. Intraday data are used to investigate the lead-lag relationships between the returns and trading activity of Taiwan stock index futures and the spot returns. We focus on the transmission direction and the sources of information. Consistent with most previous studies, our results show that other than the contemporaneous relationship predicted by carry-cost theory and efficient market theory, futures returns significantly lead spot returns, which implies that informed trades may occur in the futures market. Using private transaction information, net open buy, as a proxy for futures trading activity and distinguishing different types of futures traders, we find that foreign institutional traders are the major source of informed trades because their trading has predictive power for future movements in both spot and futures prices. Traders in other categories are information laggards.     

Does futures trading increase stock market volatility? The case of the Nikkei stock index futures markets

We propose new tests to examine whether stock index futures affect stock market volatility. These tests decompose spot portfolio volatility into the cross-sectional dispersion and the average volatility of returns on the portfolio's constituent securities. Our tests show that for Nikkei stocks spot portfolio volatility increased and cross-sectional dispersion decreased compared with average volatility when Nikkei futures began trading on the Osaka Securities Exchange, but not on the Singapore International Monetary Exchange. For non-Nikkei stocks, no shift occurred when futures trading began on either exchange. These findings are consistent with the hypotheses that futures trading increases spot portfolio volatility but that there is no volatility “spillover” to stocks against which futures are not traded. However, the increase in volatility attributable to futures trading is small compared with volatility shifts induced by changes in broad economic factors.     

Expiration day effects and market manipulation: evidence from Taiwan

In this study, we analyze the expiration day effects of index futures on the cash market in Taiwan, and find that both volatility and trading volume are higher on the final settlement days than on other trading days. We also calculate the volume of open interest for the final settlement of index futures contracts relating to different classes of traders, as well as the profits they earn from their open interest positions. We find that proprietary traders exhibit superior performance whereas foreign investors achieve the worst returns. Our empirical results support the view that the expiration day effects in the Taiwan futures market are at least partially attributable to attempts at ‘marking the close’.     

Does vega-neutral options trading contain information?

This study suggests a novel approach for decomposing net options demands into the options order imbalances with and without volatility risk. By analyzing a high-frequency index futures and options dataset, we examine the information content of (i) the direction-motivated order imbalance induced by a single option type, which is exposed to volatility risk, and (ii) that constructed by both calls and puts, which is vega-neutral. The aggregate options order imbalance does not convey information after controlling for futures market trading. However, the intraday options order imbalance by trading without volatility risk significantly predicts spot index returns, though its longer-horizon forecasting ability is relatively weak because of a possible cross-market hedging effect. The predictive abilities of informed foreigners’ trades and out-of-the-money options trading are prominent. Our empirical results suggest that the vega-neutral options trading conveys additional information distinct from the futures order imbalance.     

Using implied volatility on options to measure the relation between asset returns and variability

Prior research has documented that volatility in financial asset markets is most directly related to trading rather than calendar days, and that there is an inverse asymmetric relation between volatility and returns in both stocks and long-term bonds. We examine these relations in 37 futures options markets representing a wide variety of asset types. Using futures prices and implied volatilities from this extensive array of markets, we confirm that in all of them, save one, market volatility is more directly related to trading days. However, the nature of the association between implied volatility and underlying asset returns varies greatly across asset categories and across exchanges. Thus, we show that findings from equity markets apparently are not generalizable to other asset classes.     

An empirical investigation of large trader market manipulation in derivatives markets

Using account-level transaction data in options and futures markets, we investigate the existence of market manipulation, which is the ability of large traders to trade strategically, impacting prices and making abnormal profits. First, large trader’s option positions have a quantity impact on the underlying asset’s price. Second, large traders generate significantly positive alphas from trading options and futures. Among the different investor types, proprietary dealers generate the largest positive alphas. Third, these abnormal returns are consistent with strategic trading and cross-market manipulation. The evidence supports market manipulation across the options and futures markets, but not within the futures market itself.     

Option trading after the opening bell and intraday stock return predictability

Prior literature finds that information is reflected in option markets before stock markets, but no study has explored whether option volume soon after market open has predictive power for intraday stock returns. Using novel intraday signed option-to-stock volume data, we find that a composite option trading score (OTS) in the first 30 min of market open predicts stock returns during the rest of the trading day. Such return predictability is greater for smaller stocks, stocks with higher idiosyncratic volatility, and stocks with higher bid–ask spreads relative to their options’ bid–ask spreads. Moreover, OTS is a significantly stronger predictor of intraday stock returns after overnight earnings announcements. The evidence suggests that option trading in the 30 min after the opening bell has predictive power for intraday stock returns.     

Empirical Analyses of Three Explanations for the Positive Autocorrelation of Short-Horizon Stock Index Returns

This paper provides empirical analyses of three explanations for the observed positive autocorrelation of short-horizon stock index returns, using NYSE/AMEX and NASDAQ data. Results indicate that index autocorrelation cannot be substantially explained by either autocorrelated, time-varying expected returns, or nonsynchronous trading. The third explanation for index autocorrelation, the nonsynchronous information transfer hypothesis, states that stocks incorporate market-wide information on a nonsynchronous basis due to information and transaction costs. Evidence from analyses of mean returns on various portfolios following large returns on the S 500 futures contract, as well as regressions of portfolio returns on current and lagged futures returns, support this explanation. Small (large) firms collectively require approximately 7 (1-2) weeks to fully incorporate new market information on average, and this delayed impoundment accounts for the bulk of the observed autocorrelation.     

The Weekly Pattern in Stock Returns: Cash versus Futures: A Note

This paper presents tests designed to determine whether the weekly pattern in stock returns continues after the introduction of futures trading on stock indexes and whether the pattern carries over to the futures market. Using data for the SP500, I find that the “Monday effect” does persist in the cash market, but there is no evidence of a similar pattern in the futures market.     

Index arbitrage with heterogeneous investors: A smooth transition error correction analysis

The traditional index arbitrage model assumes a constant threshold mispricing between the futures and cash prices for all investors. Allowing for heterogeneity in investors' transaction costs, objectives, and capital constraints, we model the intraday mispricing of DJIA futures as a smooth transition autoregressive (STAR) process with the speed of adjustment toward equilibrium varying directly with the mispricing. We show that the observed mean reversion in mispricing changes is induced by heterogeneous arbitrageurs, instead of a statistical illusion-infrequent trading of index portfolio stocks. We further use a STAR error correction model to describe the nonlinear dynamics between the DJIA futures and index. This model describes not only which market is more informationally efficient than the other, but also the legging process – the nonsimultaneous establishing of cash and futures positions.