For articles eventually published in the top twenty academic finance journals and top-tier academic business journals, I examine the acceptance time (the time from first-round submission to final-round acceptance) and online/print publication times (the time from first-round submission to online/print publication). I find that the median acceptance times of the top five general-interest finance journals are: Journal of Financial Economics (9.9 months), Journal of Financial and Quantitative Analysis (10.6 months), Review of Finance (11.7 months), Review of Financial Studies (15.5 months), and Journal of Finance (19.8 months). The three fastest in finance are Review of Corporate Finance Studies, Review of Asset Pricing Studies, and Financial Management. Journal of Finance is one of the slowest top-tier business journals. Large and significant time differences support the editorial differences hypothesis. Received December 14, 2016; editorial decision December 22, 2016 by Editor Paolo Fulghieri.

We develop an integrated model in which a risk-neutral informed trader optimally chooses any combination of a market buy, a market sell, a limit buy including the limit buy price, and a limit sell including the limit sell price. Limit orders undercut the market maker and generate transactions inside the bid-ask spread. The informed trader exploits limit orders by submitting market orders even when the terminal value is inside the spread. When the terminal value is above the bid, a combined market buy-limit sell is more profitable than a market buy only. We obtain an analytic solution. Journal of Economic Literature Classification Numbers: D40, D82, G12, G14.

We develop a stylized model that generates the following empirical predictions: the less (more) accessible the underlying market is ex ante, the more its liquidity improves (deteriorates) when basket trading becomes available. We empirically test these predictions using corporate bonds before and after the introduction of exchange-traded funds. Consistent with the model’s prediction, liquidity improvement is larger for highly arbitraged, low-volume, and high-yield bonds, and for 144A bonds to which retail investor access is prohibited by law. Our article leads to a more nuanced understanding of the impact of basket security introduction than previous research suggested.

[We analyze a competitive model in which different information signals get reflected in value at different points in time. If investors are sufficiently risk averse, we obtain an equilibrium in which all investors focus exclusively on the short term. In addition, we show that increasing the variance of informationless trading increases market depth but causes a greater proportion of investors to focus on the short-term signal, which decreases the informativeness of prices about the long run. Finally, we also explore parameter spaces under which long-term informed agents wish to voluntarily disclose their information.]

ABSTRACT Do fast, competitive markets yield liquidity measurement problems when using the popular Monthly Trade and Quote (MTAQ) database? Yes. MTAQ yields distorted measures of spreads, trade location, and price impact compared with the expensive Daily Trade and Quote (DTAQ) database. These problems are driven by (1) withdrawn quotes, (2) second (versus millisecond) time stamps, and (3) other causes, including canceled quotes. The expensive solution, using DTAQ, is first‐best. For financially constrained researchers, the cheap solution—using MTAQ with our new Interpolated Time technique, adjusting for withdrawn quotes, and deleting economically nonsensical states—is second‐best. These solutions change research inferences.

The authors develop a multiperiod auction model in which multiple privately informed agents strategically exploit their long-lived information. They show that such traders compete aggressively and cause most of their common private information to be revealed very rapidly. In the limit, as the interval between auctions approaches zero, market depth becomes infinite and all private information is revealed immediately. These results are in contrast to those of Albert S. Kyle (1985) in which the monopolistic informed trader causes his information to be incorporated into prices gradually and, when the interval between auctions is vanishingly small, market depth is constant over time.

Performance share plans are an increasingly important component of executive compensation. They are equity-based, long-term incentive plans where the number of shares to be awarded is a quasi-linear function of a performance result over a fixed time period. We derive closed-form formulas for the value of a performance share plan when the performance measure is: (1) a non-traded measure following an Arithmetic Brownian Motion (e.g., earnings per share), (2) a non-traded measure following a Geometric Brownian Motion (e.g., revenue), or (3) a rank-order tournament of traded asset returns that are following Arithmetic Brownian Motions (e.g., percentile of ranked stock returns). Then we empirically test our valuation formulas. We find that our valuation formulas are more accurate for performance share plans based on earnings per share when forecasting using analyst consensus prior to the grant date. We also find that the efficiency of our valuation model greatly depends on the method used to forecast future firm performance. The policy implication is that FASB should consider requiring that grant date fair value be estimated using valuation formulas such as ours.

We analyze a competitive model in which different information signals get reflected in value at different points in time. If investors are sufficiently risk averse, we obtain an equilibrium in which all investors focus exclusively on the short term. In addition, we show that increasing the variance of informationless trading increases market depth but causes a greater proportion of investors to focus on the short-term signal, which decreases the informativeness of prices about the long run. Finally, we also explore parameter spaces under which long-term informed agents wish to voluntarily disclose their information.