[In Japan, almost identical government bonds can trade at large price differentials. Motivated by this phenomenon, we examine the issue of the value of liquidity in markets for riskless securities. We develop a model of an issuer of bonds, a market maker, and heterogeneous investors trading in an incomplete market. We show not only that divergent prices for similar securities can be sustained in a rational expectations equilibrium, but also that this divergence may be optimal from the perspective of the issuer. Price segmentation is possible because agents have a desire to trade, but short-sale restrictions limit their trading strategies and prevent them from forcing bond prices to be equal. Restricting the form of market making to exclude price competition and unregulated profit maximization is also necessary to sustain price segmentation. The optimality of segmentation from the issuer's standpoint arises because of the issuer's ability to charge for the liquidity services provided to the investors.]

In Japan, almost identical government bonds can trade at large price differentials. Motivated by this phenomenon, we examine the issue of the value of liquidity in markets for riskless securities. We develop a model of an issuer of bonds, a market maker, and heterogeneous investors trading in an incomplete market. We show not only that divergent prices for similar securities can be sustained in a rational expectations equilibrium, but also that this divergence may be optimal from the perspective of the issuer. Price segmentation is possible because agents have a desire to trade, but short-sale restrictions limit their trading strategies and prevent them from forcing bond prices to be equal. Restricting the form of market making to exclude price competition and unregulated profit maximization is also necessary to sustain price segmentation. The optimality of segmentation from the issuer's standpoint arises because of the issuer's ability to charge for the liquidity services provided to the investors.

[The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For the persistence levels of dividend yields, the analytical correlation is 99% between the 1- and 2-year horizon estimators and 94% between the 1- and 5-year horizons. Common sampling error across equations leads to ordinary least squares coefficient estimates and R²s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. We perform joint tests across horizons for a variety of explanatory variables and provide an alternative view of the existing evidence.]

[This article reexamines the autocorrelation patterns of short-horizon stock returns. We document empirical results which imply that these autocorrelations have been overstated in the existing literature. Based on several new insights, we provide support for a market efficiency-based explanation of the evidence. Our analysis suggests that institutional factors are the most likely source of the autocorrelation patterns.]

Multivariate density estimation (MDE) suggests that mortgage-backed security (MBS) prices can be well described as a function of the level and slope of the term structure. We analyze how this function varies across MBSs with different coupons. An important finding is that the interest rate level proxies for the moneyness of the option, the expected level of prepayments, and the average life of the cash flows, while the term structure slope controls for the average rate at which these cash flows should be discounted. Though the origination and prepayment behavior of mortgages differ substantially across coupons, there remains an unexplained common factor in MBS prices. This factor does not seem to be related to the usual suspects and therefore presents a puzzle to financial economists.

We investigate the relation between returns on stock indices and their corresponding futures contracts to evaluate potential explanations for the pervasive yet anomalous evidence of positive, short-horizon portfolio autocorrelations. Using a simple theoretical framework, we generate empirical implications for both microstructure and partial adjustment models. The major findings are (i) return autocorrelations of indices are generally positive even though futures contracts have autocorrelations close to zero, and (ii) these autocorrelation differences are maintained under conditions favorable for spot-futures arbitrage and are most prevalent during low-volume periods. These results point toward microstructure-based explanations and away from explanations based on behavioral models.

The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For example, for the persistence levels of dividend yields, the analytical correlation is 99% between the 1-and 2-year horizon estimators and 94% between the 1-and 5-year horizons, due to the combined effects of overlapping returns and the persistence of the predictive variable. Common sampling error across equations leads to ordinary least squares coefficient estimates and R2s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. The asymptotic theory is corroborated, and the analysis extended by extensive simulation evidence. We perform joint tests across horizons for a variety of explanatory variables, and provide an alternative view of the existing evidence.

This article reexamines the autocorrelation patterns of short-horizon stock returns. We document empirical results which imply that these autocorrelations have been overstated in the existing literature. Based on several new insights, we provide support for a market efficiency-based explanation of the evidence. Our analysis suggests that institutional factors are the most likely source of the autocorrelation patterns.

What moves stock prices? Prior literature concludes that the revelation of private information through trading, and not public news, is the primary driver. We revisit the question by using textual analysis to identify fundamental information in news. We find that this information accounts for 49.6% of overnight idiosyncratic volatility (vs. 12.4% during trading hours), with a considerable fraction due to days with multiple news types. We use our measure of public information arrival to reinvestigate two important contributions in the literature related to individual R^2s of stock returns on aggregate factors.Received February 24, 2016; editorial decision May 19, 2018 by Editor Andrew Karolyi.

Multivariate density estimation (MDE) suggests that mortgage-backed security (MBS) prices can be well described as a function of the level and slope of the term structure. We analyze how this function varies across MBSs with different coupons. An important finding is that the interest rate level proxies for the moneyness of the option, the expected level of prepayments, and the average life of the cash flows, while the term structure slope controls for the average rate at which these cash flows should be discounted. Though the origination and prepayment behavior of mortgages differ substantially across coupons, there remains an unexplained common factor in MBS prices. This factor does not seem to be related to the usual suspects and therefore presents a puzzle to financial economists.