The intraday lead–lag relation between returns of the Major Market cash index and returns of the Major Market Index futures and S&P 500 futures is investigated. Empirical results show strong evidence that the futures leads the cash index and weak evidence that the cash index leads the futures. The asymmetric lead–lag relation holds between the futures and all component stocks, including those that trade in almost every five-minute interval. Evidence indicates that when more stocks move together (market-wide information) the futures leads the cash index to a greater degree. This suggests that the futures market is the main source of market-wide information.

This paper examines the roles of the number of trades, size of trades, and order imbalance (buyer- versus seller-initiated trades) in explaining the volatility–volume relation for a sample of NYSE and Nasdaq stocks. Our results reconfirm the significance of the size of trades, beyond that of the number of trades, in the volatility–volume relation on both markets. After controlling for the return impact of order imbalance, the volatility–volume relation becomes much weaker. For NYSE stocks, the order imbalance in large trade size categories affects the return more than in smaller size categories. For Nasdaq stocks, the largest return impact comes from the order imbalance in maximum-sized Small Order Execution System (SOES) trades.

I develop a model to explain why stock returns are positively cross‐autocorrelated. When market makers observe noisy signals about the value of their stocks but cannot instantaneously condition prices on the signals of other stocks, which contain marketwide information, the pricing error of one stock is correlated with the other signals. As market makers adjust prices after observing true values or previous price changes of other stocks, stock returns become positively cross‐autocorrelated. If the signal quality differs among stocks, the cross‐autocorrelation pattern is asymmetric. I show that both own‐ and cross‐autocorrelations are higher when market movements are larger.

This paper examines the relation between the stock price synchronicity and analyst activity in emerging markets. Contrary to the conventional wisdom that security analysts specialize in the production of firm-specific information, we find that securities which are covered by more analysts incorporate greater (lesser) market-wide (firm-specific) information. Using the R2 statistics of the market model as a measure of synchronicity of stock price movement, we find that greater analyst coverage increases stock price synchronicity. Furthermore, after controlling for the influence of firm size on the lead–lag relation, we find that the returns of high analyst-following portfolio lead returns of low analyst-following portfolio more than vice versa. We also find that the aggregate change in the earnings forecasts in a high analyst-following portfolio affects the aggregate returns of the portfolio itself as well as those of the low analyst-following portfolio, whereas the aggregate change in the earnings forecasts of the low analyst-following portfolio have no predictive ability. Finally, when the forecast dispersion is high, the effect of analyst coverage on stock price synchronicity is reduced.

We document that instrumental variables known to possess forecast power in equity and bond markets (Treasury bill yields, equity dividend yields, and the ‘junk’ bond premium) also possess forecast power for prices in agricultural, metals, and currency futures markets. The pattern of forecastability in futures is consistent with economic equilibrium as embodied by a two-‘latent-variable’ model. We test whether the latent variables that explain these futures returns coincide with latent variables that explain returns on size-ranked equity portfolios. This hypothesis is rejected, suggesting that futures are subject to different sources of priced risk than are equities.

We investigate what stock return synchronicity reflects in terms of price informativeness by examining its effect on the pricing of seasoned equity offerings (SEOs). Based on 5,087 SEOs from 1984 to 2007, we find a significantly negative relation between stock return synchronicity (estimated as the logit transformation of the R-squared statistic from a two-factor regression) and SEO discounts (the percentage differences between pre-offer day closing prices and offer prices). The negative relation is strongest when there is no analyst coverage, and it declines as analyst coverage increases. This shows that stock price is more informative when stock return synchronicity is higher and also that information asymmetry can be mitigated by analyst coverage. We further decompose stock return synchronicity into the market comovement and industry comovement components and find that both components are equally important in affecting SEO discounts.