The Journal of Finance publishes leading research across all the major fields of finance. It is one of the most widely cited journals in academic finance, and in all of economics. Each of the six issues per year reaches over 8,000 academics, finance professionals, libraries, and government and financial institutions around the world. The journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics.
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The Market Reaction to Stock Splits
Published: 12/01/1987 | DOI: 10.1111/j.1540-6261.1987.tb04370.x
CHRISTOPHER G. LAMOUREUX, PERCY POON
In this paper, a model of market reaction to stock splits is presented and tested. We argue that the announcement of a split sets off the following chain of events. The market recognizes that, subsequent to the (reverse) split ex‐day, the daily number of transactions along with the raw volume of shares traded will increase (decrease). This increase in volume results in an increase in the noisiness of the security's return process. The increase in noise raises the tax‐option value of the stock, and it is this value that generates the announcement effect of stock splits. Empirical evidence using security returns, daily trading volume, and shareholder data strongly supports this theory. The evidence, in conjunction with this theory, also agrees with extant literature that splits result in decreased liquidity, but there is no evidence that this reduction in liquidity is priced.
Firm Size and Turn‐of‐the‐Year Effects in the OTC/NASDAQ Market
Published: 12/01/1989 | DOI: 10.1111/j.1540-6261.1989.tb02651.x
CHRISTOPHER G. LAMOUREUX, GARY C. SANGER
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.
Empirical Analysis of the Yield Curve: The Information in the Data Viewed through the Window of Cox, Ingersoll, and Ross
Published: 12/17/2002 | DOI: 10.1111/1540-6261.00467
Christopher G. Lamoureux, H. Douglas Witte
This paper uses recent advances in Bayesian estimation methods to exploit fully and efficiently the time‐series and cross‐sectional empirical restrictions of the Cox, Ingersoll, and Ross model of the term structure. We examine the extent to which the cross‐sectional data (five different instruments) provide information about the model. We find that the time‐series restrictions of the two‐factor model are generally consistent with the data. However, the model's cross‐sectional restrictions are not. We show that adding a third factor produces a significant statistical improvement, but causes the average time‐series fit to the yields themselves to deteriorate.
When It's Not The Only Game in Town: The Effect of Bilateral Search on the Quality of a Dealer Market
Published: 04/18/2012 | DOI: 10.1111/j.1540-6261.1997.tb04818.x
CHRISTOPHER G. LAMOUREUX, CHARLES R. SCHNITZLEIN
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.
Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects
Published: 03/01/1990 | DOI: 10.1111/j.1540-6261.1990.tb05088.x
CHRISTOPHER G. LAMOUREUX, WILLIAM D. LASTRAPES
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.