The Journal of Finance

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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Search results: 5.

Information Asymmetry and Asset Prices: Evidence from the China Foreign Share Discount

Published: 01/10/2008   |   DOI: 10.1111/j.1540-6261.2008.01313.x


We examine the effect of information asymmetry on equity prices in the local A‐ and foreign B‐share market in China. We construct measures of information asymmetry based on market microstructure models, and find that they explain a significant portion of cross‐sectional variation in B‐share discounts, even after controlling for other factors. On a univariate basis, the price impact measure and the adverse selection component of the bid‐ask spread in the A‐ and B‐share markets explains 44% and 46% of the variation in B‐share discounts. On a multivariate basis, both measures are far more statistically significant than any of the control variables.

Does Algorithmic Trading Improve Liquidity?

Published: 01/06/2011   |   DOI: 10.1111/j.1540-6261.2010.01624.x


Algorithmic trading (AT) has increased sharply over the past decade. Does it improve market quality, and should it be encouraged? We provide the first analysis of this question. The New York Stock Exchange automated quote dissemination in 2003, and we use this change in market structure that increases AT as an exogenous instrument to measure the causal effect of AT on liquidity. For large stocks in particular, AT narrows spreads, reduces adverse selection, and reduces trade‐related price discovery. The findings indicate that AT improves liquidity and enhances the informativeness of quotes.

High‐Frequency Trading around Large Institutional Orders

Published: 02/14/2019   |   DOI: 10.1111/jofi.12759


Liquidity suppliers lean against the wind. We analyze whether high‐frequency traders (HFTs) lean against large institutional orders that execute through a series of child orders. The alternative is HFTs trading with the wind, that is, in the same direction. We find that HFTs initially lean against these orders but eventually change direction and take positions in the same direction for the most informed institutional orders. Our empirical findings are consistent with investors trading strategically on their information. When deciding trade intensity, they seem to trade off higher speculative profits against higher risk of being detected and preyed on by HFTs.

Information Revelation in Decentralized Markets

Published: 08/09/2019   |   DOI: 10.1111/jofi.12838


How does information get revealed in decentralized markets? We test several hypotheses inspired by recent dealer‐network theory. To do so, we construct an empirical map of information revelation where two dealers are connected based on the synchronicity of their quote changes. The tests, based on the euro to Swiss franc spot rate (EUR/CHF) quote data including the 2015 crash, largely support theory: strongly connected (i.e., central) dealers are more informed. Connections are weaker when there is less to be learned. The crash serves to identify how a network forms when dealers are transitioned from no‐learning to learning, that is, from a fixed to a floating rate.

Competition for Order Flow and Smart Order Routing Systems

Published: 01/10/2008   |   DOI: 10.1111/j.1540-6261.2008.01312.x


We study the rivalry between Euronext and the London Stock Exchange (LSE) in the Dutch stock market to test hypotheses about the effect of market fragmentation. As predicted by our theory, the consolidated limit order book is deeper after entry of the LSE. Moreover, cross‐sectionally, we find that a higher trade‐through rate in the entrant market coincides with less liquidity supply in this market. These findings imply that (i) fragmentation of order flow can enhance liquidity supply and (ii) protecting limit orders against trade‐throughs is important.