No abstract

This paper develops a model of speculative trading in a large economy with a continuum of investors. In our model the investors are assumed to have diverse beliefs which are rational in the sense of being compatible with observed data. We demonstrate the existence of price amplification effects and show that the equilibrium prices can be higher or lower than the rational expectation equilibrium price. It is also shown that trading volume is positively related to the directions of price changes. Moreover, we study how asset price volatility and trading volume are influenced by belief structures, short selling constraints and the amount of fund available for investment. Copyright Springer-Verlag Berlin/Heidelberg 2004Price volatility, Trading volume, Speculation, Rational beliefs.,

This article examines the evidence of herd behaviour and stock price co-movement within high-tech stocks in the Taiwan market. We study return dispersion, volatility dispersion and directional co-movement within the industry, finding their relations with high-tech mania and extreme markets. Our empirical results demonstrate more significant evidence of return dispersion, volatility dispersion, and a higher degree of directional co-movement in high-tech industries than in traditional industries. Both return dispersion and volatility dispersion were found to have a consistent association with extreme market movements for high-tech stocks. However, the level of directional co-movement, as a modified measure of herd behaviour, is greater during extreme markets for all industries, with an asymmetric result that has great significance for herding during extreme up markets as related to down markets.

This study proposes a novel spatial model in which an online retailer competes with heterogeneous brick‐and‐mortar retailers. Consumers are assumed to be non‐uniformly distributed along an urban‐rural line, and online transactions provide savings in transportation costs at the expense of distaste costs. Among other results, we show that the surviving brick‐and‐mortar retailers eventually move toward densely populated (urban) areas after the entry of the online retailer. Consumer welfare, the policy of not taxing online business, and the socially optimal number of retailers are also analyzed.

Financial leverage, Diverse beliefs, Stock price volatility, Leverage effect, Pyramiding/depyramiding effect, D84, G12, G18,