Using Compustat data, we reproduce the annual return distribution each year from 1963 to 2020 of the largest 500 and the next-largest 1000 US stocks, which on average represent about 96% of investable US stock capitalization. In the average calendar year about 65% (62%) of the largest (smaller)...

This study examines the determinants of the cross-sectional variation in stock prices by decomposing individual stock price-ratios over a set of 21 variables split between seven categories. I test a firm-specific version of the Campbell and Shiller (1988) model and show that expected returns and...

Over-the-counter (OTC) stocks are far less liquid, disclose less information, and exhibit lower institutional holdings than listed stocks. We exploit these different market conditions to test theories of cross-sectional return premiums. Compared to premiums in listed markets, the OTC illiquidity...

Over-the-counter (OTC) stocks are far less liquid, disclose less information, and exhibit lower institutional holdings than listed stocks. We exploit these different market conditions to test theories of cross-sectional return premiums. Compared to premiums in listed markets, the OTC illiquidity...

This research aim to calculate influence corporate financial performance to stock return. Multiregression model follow Fama and French procedure. Result of first hypothesis confirmed statistically, that the difference of stock of return pursuant to finance performance not automatically own...

This study aims to analyze and test empirically the influence of corporate financial performance against systematic risk on stocks. The analysis technique used is multiple linear regression. The results showed that the financial performance did not significantly affect the systematic risk of the...

When practitioners evaluate the equity market, two important questions recur. What long-run returns should investors expect? And, are there fundamental yardsticks that reliably indicate when the market is overvalued? Researchers have not reached a consensus on either of these questions. Equity...

We extract contextualized representations of news text to predict returns using the state-of-the-art large language models in natural language processing. Unlike the traditional bag-of-words approach, the contextualized representation captures both the syntax and semantics of text, thus...

We provide data and code that successfully reproduces nearly all crosssectional stock return predictors. Our 319 characteristics draw from previous meta-studies, but we differ by comparing our t-stats to the original papers' results. For the 161 characteristics that were clearly significant in...