We report results from experimental asset markets with liquidity traders and an insider where we allow bilateral trade to take place, in addition to public trade with dealers. In the absence of the search alternative, dealer profits are large—unlike in models with risk‐neutral, competitive dealers. However, when we allow traders to participate in the search market, dealer profits are close to zero. Dealers compete more aggressively with the alternative trading avenue than with each other. There is no evidence that price discovery is less efficient when the specialists are not the only game in town.

We report results from experimental asset markets with liquidity traders and an insider where we allow bilateral trade to take place, in addition to public trade with dealers. In the absence of the search alternative, dealer profits are large—unlike in models with risk-neutral, competitive dealers. However, when we allow traders to participate in the search market, dealer profits are close to zero. Dealers compete more aggressively with the alternative trading avenue than with each other. There is no evidence that price discovery is less efficient when the specialists are not the only game in town.

This paper provides empirical support for the notion that Autoregressive Conditional Heteroskedasticity (ARCH) in daily stock return data reflects time dependence in the process generating information flow to the market. Daily trading volume, used as a proxy for information arrival time, is shown to have significant explanatory power regarding the variance of daily returns, which is an implication of the assumption that daily returns are subordinated to intraday equilibrium returns. Furthermore, ARCH effects tend to disappear when volume is included in the variance equation.

This paper provides empirical support for the notion that autoregressive conditional heteroskedasticity in daily stock return data reflects time dependence in the process generating information flow to the market. Daily trading volume, used as a proxy for information arrival time, is shown to have significant explanatory power regarding the variance of daily returns, which is an implication of the assumption that daily returns are subordinated to intraday equilibrium returns. Furthermore, autoregressive conditional heteroskedasticity effects tend to disappear when volume is included in the variance equation.

This paper provides empirical support for the notion that Autoregressive Conditional Heteroskedasticity (ARCH) in daily stock return data reflects time dependence in the process generating information flow to the market. Daily trading volume, used as a proxy for information arrival time, is shown to have significant explanatory power regarding the variance of daily returns, which is an implication of the assumption that daily returns are subordinated to intraday equilibrium returns. Furthermore, ARCH effects tend to disappear when volume is included in the variance equation.

This paper examines the turn‐of‐the‐year effect, the firm size effect, and the relation between these two effects for a sample of OTC stocks traded via the NASDAQ reporting system over the period 1973–1985. We find results similar to those based solely on listed stocks. The importance of these findings stems from the existence of nontrivial differences between the characteristics of the OTC/NASDAQ sample and the samples of listed firms examined previously in the literature. We also find that NASDAQ quoted bid‐ask spreads are highly negatively correlated with firm size, are not highly seasonal, and are large enough to preclude trading profits based upon a knowledge of the seasonality of small firms' returns.

This paper examines the turn-of-the-year effect, the firm size effect, and the relation between these two effects for a sample of OTC stocks traded via the NASDAQ reporting system over the period 1973–1985. We find results similar to those based solely on listed stocks. The importance of these findings stems from the existence of nontrivial differences between the characteristics of the OTC/NASDAQ sample and the samples of listed firms examined previously in the literature. We also find that NASDAQ quoted bid-ask spreads are highly negatively correlated with firm size, are not highly seasonal, and are large enough to preclude trading profits based upon a knowledge of the seasonality of small firms' returns.

Within the past few years several articles have suggested that returns on large equity portfolios may contain a significant predictable component at horizons 3 to 6 years. Subsequently, the tests used in these analyses have been criticized (appropriately) for having widely misunderstood size and power, rendering the conclusions inappropriate. This criticism however has not focused on the data, it addressed the properties of the tests. In this article we adopt a subjectivist analysis – treating the data as fixed – to ascertain whether the data have anything to say about the permanent/temporary decomposition. The data speak clearly and they tell us that for all intents and purposes, stock prices follow a random walk.

The choices of firms raising external capital conform to standard static choice theory in that the higher the (relative) cost of an alternative—both at the overall market level and at the firm level—the less attractive is that alternative. Price elasticities of demand are smaller for more profitable and tangible firms, and larger for larger and more liquid firms. Firm fixed effects account for one-third of the explained choice variation of multiple issuers. Short-term debt is more attractive when the yield curve is steeply sloped, but the demand for equity is inelastic with respect to the market price-earnings multiple.