Using the FPE/multivariate Granger-causality modeling technique, this paper tests whether changes in Canadian stock returns are caused by a number of economic variables, including base money and fiscal deficits. The empirical results from monthly data show that lagged changes in fiscal deficits, in particular, Granger-cause stock returns. If expected returns to equity are not time-varying, such a finding appears inconsistent with market efficiency.

Utilizing a Granger causality approach, the authors test whether there has been a causal rela tion between public sector growth and real economic growth rates for the OECD countries. Special emphasis is laid on feedback effects from economic growth to government growth that result from macroeconomic policy. The authors find that government growth has had mixed effects on economic growth rates, positive for some countries and negative f or others. However, for the majority of the OECD countries, there was no discernable impact of government growth on the rate of real econo mic growth.

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 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.

We examine the performance of several types of the consumption-based CAPM (C-CAPM) models to explore if consumption factors matter for determining excess returns across 17 MSCI country indexes. While the classic world C-CAPM does exhibit some power in explaining cross-sectional variations of expected excess returns, the model seems to require an implausibly large coefficient of risk aversion. The more sophisticated models including the heterogeneous C-CAPM, the world surplus consumption and the habit-formation models provide more reasonable estimates and add substantial explanatory power for the variation in the cross section of excess stock returns. Our results suggest that country-specific consumption risk is not fully diversified thus implying that stock returns are related to idiosyncratic consumption risk.