We evaluate the influence of measurement error in analysts' forecasts on the accuracy of implied cost of capital estimates from various implementations of the ‘implied cost of capital' approach, and develop corrections for the measurement error. We document predictable error in the implied...

This study examines whether analysts' decisions to issue cash flows forecasts depend endogenously on their decision to use these forecasts to set target prices. An endogenous switching regression model, with analyst report regimes of disclosure and non-disclosure of cash flow forecasts, shows...

This paper reveals that in addition to fundamental factors, the 52-week high price and recent investor sentiment play an important role in analysts' target price formation. Analysts' forecasts of short-term earnings and long-term earnings growth are shown to be important explanatory variables...

We examine whether, and to what extent, investors focus on salient and easy-to-process features in responding to analyst forecasts. We focus on rounding as arguably the most salient forecast feature. We find that while rounding is only marginally associated with forecast accuracy, investors...

In this paper, we employ the earnings model developed in Ashton and Wang (2013) to forecast the one- to three-year ahead earnings of individual companies. We find that the model produces forecasts of future earnings that are less biased and more informative than both the consensus analysts'...

Current evidence on the sophistication of analysts' cash flow forecasts is ambiguous. For example, Call et al. (2009) show that issuing cash flow forecasts has important benefits for analysts' earnings forecasts, while Givoly et al. (2009) question the validity of this result, arguing that...

Current evidence on the sophistication of analysts' cash flow forecasts is ambiguous. For example, Call et al. (2009) show that issuing cash flow forecasts has important benefits for analysts' earnings forecasts, while Givoly et al. (2009) question the validity of this result, arguing that...

In the present paper we propose a new method, the Penalized Adaptive Method (PAM), for a data driven detection of structural changes in sparse linear models. The method is able to allocate the longest homogeneous intervals over the data sample and simultaneously choose the most proper variables...

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...

The answer to this question is yes, but not that much about banks. Every quarter the Federal Reserve System surveys a panel of senior loan officers at major banks across the nation. The results of this survey have been found in previous studies to provide useful information in predicting gross...