The incorporation of diverse information into asset prices is empirically examined in an actual securities market with multiple rounds of trade. Using prices of Israeli index and nominal bonds of equal maturity, we calculate implied expectations of inflation that has already occurred but for which the official statistic has not yet been announced. Learning is defined as the convergence of these expectations to the actual level of inflation in the period after the end of the month but before the announcement of the official statistic. We find that the variance of the inflation expectation errors decreases with trading days in this period. The decline in the variance suggests that investors learn, by repeatedly observing prices, about the distribution of other investors' information. We also find a positive relation between the dispersion of relative price changes and the size of the inflation‐expectation errors on the first round of trade. The correlation diminishes as investors learn about the distribution of inflation information in the economy.

[The incorporation of diverse information into asset prices is empirically examined in an actual securities market with multiple rounds of trade. Using prices of Israeli index and nominal bonds of equal maturity, we calculate implied expectations of inflation that has already occurred but for which the official statistic has not yet been announced. Learning is defined as the convergence of these expectations to the actual level of inflation in the period after the end of the month but before the announcement of the official statistic. We find that the variance of the inflation expectation errors decreases with trading days in this period. The decline in the variance suggests that investors learn, by repeatedly observing prices, about the distribution of other investors' information. We also find a positive relation between the dispersion of relative price changes and the size of the inflation-expectation errors on the first round of trade. The correlation diminishes as investors learn about the distribution of inflation information in the economy.]

The incorporation of diverse information into asset prices is empirically examined in an actual securities market with multiple rounds of trade. Using prices of Israeli index and nominal bonds of equal maturity, we calculate implied expectations of inflation that has already occurred but for which the official statistic has not yet been announced. Learning is defined as the convergence of these expectations to the actual level of inflation in the period after the end of the month but before the announcement of the official statistic. We find that the variance of the inflation expectation errors decreases with trading days in this period. The decline in the variance suggests that investors learn, by repeatedly observing prices, about the distribution of other investors' information. We also find a positive relation between the dispersion of relative price changes and the size of the inflation‐expectation errors on the first round of trade. The correlation diminishes as investors learn about the distribution of inflation information in the economy.

This article uses a unique dataset to study how firms managed liquidity during the 2008–2009 financial crisis. Our analysis provides new insights on interactions between internal liquidity, external funds, and real corporate decisions, such as investment and employment. We first describe how companies used credit lines during the crisis (access, size of facilities, and drawdown activity), the characteristics of these facilities (fees, markups, maturity, and collateral), and whether managers had difficulties in renewing or initiating lines. We also describe the dynamics of credit line violations and the outcome of subsequent renegotiations. We show how companies substitute between credit lines and internal liquidity (cash and profits) when facing a severe credit shortage. Looking at real-side decisions, we find that credit lines are associated with greater spending when companies are not cash-strapped. Firms with limited access to credit lines, in contrast, appear to choose between saving and investing during the crisis. Our evidence indicates that credit lines eased the impact of the financial crisis on corporate spending.

We assess the finite sample performance of simulation estimators that are used to estimate the parameters of dynamic corporate finance models. We formulate an external validity specification test and propose a new set of statistical benchmarks that can be used to estimate and evaluate these models. These benchmarks are based on model policy functions. Our Monte Carlo simulations show that the estimators are largely unbiased with low root mean squared errors. When computed with an optimal weight matrix, the specification tests associated with the estimators are close to correctly sized. These tests have excellent power to detect misspecification.

We develop a three-factor no-arbitrage model for valuing mortgage-backed securities in which we solve for the implied prepayment function from the cross-section of market prices. This model closely fits the cross-section of mortgage-backed security prices without needing to specify an econometric prepayment model. We find that implied prepayments are generally higher than actual prepayments, providing direct evidence of significant macroeconomic-driven prepayment risk premiums in mortgage-backed security prices. We also find evidence that mortgage-backed security prices were significantly affected by Fannie Mae credit risk and the Federal Reserve’s quantitative easing programs.

[We examine the performance of liquidity proxies in commodities. The Amihud measure has the largest correlation with liquidity benchmarks. Amivest and Effective Tick measures also perform well. These proxies are useful for studies of commodity liquidity over a long time period and those that lack access to high-frequency data. We use various aspects of transaction costs, such as spread, depth, immediacy, and resiliency, to give insight into the costs of different execution approaches. Transaction costs increase with volatility and exhibit mean reversion. Splitting trades over one hour can reduce trading costs by two-thirds compared to an immediate execution.]

[Many investors purchase mutual funds through intermediated channels, paying brokers or financial advisors for fund selection and advice. This article attempts to quantify the benefits that investors enjoy in exchange for the costs of these services. We study broker-sold and direct-sold funds from 1996 to 2004, and fail to find that brokers deliver substantial tangible benefits. Relative to direct-sold funds, broker-sold funds deliver lower risk-adjusted returns, even before subtracting distribution costs. These results hold across fund objectives, with the exception of foreign equity funds. Further, broker-sold funds exhibit no more skill at aggregate-level asset allocation than do funds sold through the direct channel. Our results are consistent with two hypotheses: that brokers deliver substantial intangible benefits that we do not observe and that there are material conflicts of interest between brokers and their clients.]

This article studies the pricing of options in an extended Black Scholes economy in which the underlying asset is not perfectly liquid. The resulting liquidity risk is modeled as a stochastic supply curve, with the transaction price being a function of the trade size. Consistent with the market microstructure literature, the supply curve is upward sloping with purchases executed at higher prices and sales at lower prices. Optimal discrete time hedging strategies are then derived. Empirical evidence reveals a significant liquidity cost intrinsic to every option.

This article shows how to evaluate the performance of managed portfolios using stochastic discount factors (SDFs) from continuous-time term structure models. These models imply empirical factors that include time averages of the underlying state variables. The approach addresses a performance measurement bias, described by Goetzmann, Ingersoll, and Ivkovic (2000) and Ferson and Khang (2002), arising because fund managers may trade within the return measurement interval or hold positions in replicable options. The empirical factors contribute explanatory power in factor model regressions and reduce model pricing errors. We illustrate the approach on US government bond funds during 1986-2000.