Asymmetric theories predict that information will flow from large stock prices to small stock prices. This paper examines whether the multivariate lead-Iag intraday relationship between large, medium and small stocks in Australia changes according to market trading conditions. The analysis applies recent time series techniques of unit root testing, multivariate Johansen-Juselius tests of cointegration, vector error-correction modelling (VECM), and forecast error variance decomposition (VDC). We find that the information environment faced by stock market participants is fluid and related to whether prices are generally rising or falling. During abearprice phase,large stocks provided the dominant price lead in the stock market. In a bull phase, however, the role of small stocks became more powerful, in both the short and long term, and their prices relatively more exogenous. We conclude that the increased independence of small and medium stocks during the bull price phase is related to an increase in information search, by analysts and market traders, induced by more favourable cost-benefit incentives.

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.

The dynamic nature of the price information transfer when stock and futures markets switch between different price trading phases is examined. This is undertaken by decomposing Australian stock indexes and share price index futures contract data into bear- and bull-market phases and analyzing the change in the power of the bidirectional information feedback between the futures market and small, medium, and large stocks. Results support the hypothesis that the nature of the price-discovery process varies with the trading phase. In particular, during the bull phase small stocks show a marked increase in price exogeneity and futures prices contain relatively less price-sensitive fundamental information. We argue that in bull phases, futures trading becomes increasingly associated with noninformation trading such as realizing paper profits, portfolio rebalancing, and increased noise trading.