This paper investigates the hypotheses that the recently established Mexican stock index futures market effectively serves the price discovery function, and that the introduction of futures trading has provoked volatility in the underlying spot market. We test both hypotheses simultaneously with daily data from Mexico in the context of a modified EGARCH model that also incorporates possible cointegration between the futures and spot markets. The evidence supports both hypotheses, suggesting that the futures market in Mexico is a useful price discovery vehicle, although futures trading has also been a source of instability for the spot market. Several managerial implications are derived and discussed.

We use the consumption-based asset pricing model with habit formation to study the predictability and cross-section of returns from the international equity markets. We find that the predictability of returns from many developed countries' equity markets is explained in part by changing prices of risks associated with consumption relative to habit at the world as well as local levels. We also provide an exploratory investigation of the cross-sectional implications of the model under the complete world market integration hypothesis and find that the model performs mildly better than the traditional consumption-based model, the unconditional and conditional world CAPMs and a three-factor international asset pricing model.

We propose a new methodology to test Fama’s [J. Finance 46 (1991) 1575] contention that the present value model (PVM) should be augmented by time-varying expected inflation to more adequately account for actual stock price behavior. Unlike other methods, our testing approach can distinguish between the excess-price movement hypothesis of Shiller [Am. Econ. Rev. 71 (1981) 421] and the dividend-smoothing hypothesis of Marsh and Merton [Am. Econ. Rev. 76 (1986) 483]. We decompose the levels (as opposed to the variances) of stock prices into their fundamental and non-fundamental elements in the context of a multivariate PVM co-integrating framework and utilize the Gonzalo and Granger [J. Bus. Econ. Stat. 13 (1995) 27] procedure to formally test for the statistical significance of the non-fundamental component. Our results from monthly data for the post-WWII period do not support the inflation-augmented PVM since the non-fundamental component continues to achieve significance. This finding persists under alternative model specifications and data frequencies. The apparent failure of the traditional, rational-expectation, PVM model to adequately account for observed market behavior provides another piece of evidence supportive of Shiller’s [Am. Econ. Rev. 71 (1981) 591] belief in some form of market “irrationality”.

We examine the contemporaneous correlation as well as the lead–lag relation between trading volume and return volatility in all stocks comprising the Dow Jones industrial average (DJIA). We use 5-minute intraday data and measure return volatility by the exponential generalized autoregressive conditional heteroscedasticity method. Contrary to the mixture of distribution hypothesis, the vast majority of the DJIA stock shows no contemporaneous correlation between volume and volatility. However, we find evidence of significant lead–lag relations between the two variables in a large number of the DJIA stocks in accordance with the sequential information arrival hypothesis.

This paper reexamines the dynamic relation between intraday trading volume and return volatility of large and small NYSE stocks in two partitioned samples, with and without identifiable public news. We argue that the sequential information arrival hypothesis (SIAH) can be tested only in periods containing public news. After partitioning the sample into periods with and without public news, we find bi-directional Granger-causality between volume and volatility in the presence of public information as hypothesized by the SIAH. Our analysis further suggests that return volatility is higher in the periods with public news, while trading volume is significantly higher in the no-news period; perhaps owing to the importance of private information for trading stocks. Using the sample without public news, we find evidence that volume Granger-causes volatility without feedback. These results are broadly consistent with behavioral models like the overconfidence and biased self-attribution model of [Daniel, K., Hirshleifer, D., Subrahmanyam, A., 1998. Investor psychology and security market under- and over-reactions. Journal of Finance 53, 1839–1885]. It appears that overconfident investors overrate the precision of their private news signals and therefore trade too aggressively in the absence of public news; when public news arrives, investors’ biased self-attribution triggers excessive return volatility.