Previous studies use cross-sectional forecast dispersion in examining the relation between forecast dispersion and future stock returns and report an anomalous negative dispersion-return relation. This paper examines how time-series forecast dispersion is distinct in the relation to stock...

As some recent studies have shown empirically, future gold price fluctuations are especially difficult to forecast. Against this background, this study evaluates the forecasting power of three methods that have been applied successfully in a stock market prediction context: 1) technical...

This paper investigates the relationships among cross-sectional stock returns and analysts' forecast revisions, forecast dispersion and momentum. Market rewards the strategy in pursuit of revision up and away from revision down by 22.7% per annum over the 1983-2015 periods. I find that the...

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...

The paper finds that firms' exposure to temperature changes predicts stock returns. We use the sensitivity of stock returns to abnormal temperature changes to measure firm-level climate sensitivity. Stocks with higher climate sensitivity forecast lower stock returns. A trading strategy that...

We study the effect of a mandatory improvement in public disclosure due to the adoption of International Financial Reporting Standards (IFRS) on the stock return predictability of shorting activity. To assess the impact of the disclosure shock, we measure monthly changes in the demand for and...

A growing body of literature in accounting and finance relies on implied cost of equity (COE) measures. Such measures are sensitive to assumptions about terminal earnings growth rates. In this paper we develop a new COE measure that is more accurate than existing measures because it incorporates...

We review the literature on return and cash flow growth predictability form the perspective of the present-value identity. We focus predominantly on recent work. Our emphasis is on U.S. aggregate stock return predictability, but we also discuss evidence from other asset classes and countries

We use machine learning tools to analyze industry return predictability based on theinformation in lagged industry returns from across the entire economy. Controlling forpost-selection inference and multiple testing, we nd significant in-sample evidence ofindustry return predictability. Lagged...

Exploiting financial news stories data, we construct news-implied linkages and document a strong lead-lag effect of firms with shared news coverage in China’s stock market. The news-link momentum strategy generates a monthly return of 1.33% and a four-factor alpha (Liu et al., 2019) of 1.43%....