We investigate the effect of ETF ownership on stock market anomalies and market efficiency. We find that low ETF ownership stocks exhibit higher returns, greater Sharpe ratios, and highly significant alphas in comparison to high ETF ownership stocks. We show that high ETF ownership stocks...

We provide the first comprehensive analysis of option information for pricing the cross-section of stock returns by jointly examining extensive sets of firm and option characteristics. Using portfolio sorts and high-dimensional methods, we show that certain option measures have significant...

Using a comprehensive data set and an array of 27 macroeconomic, stock and bond predictors, we find that corporate bond returns are highly predictable based on an iterated combination model. The large set of predictors outperforms traditional predictors substantially, and predictability...

This paper shows that investors do not fully incorporate cost behavior information into valuation. Firms with higher growth in operating costs generate substantially lower future stock returns and operating performance. An equal-weighted long-short spread portfolio earns an average return of 82...

Using a large number of predictors and based on an extended iterated combination approach of Lin, Wu, and Zhou (2017), we document both statistical and economic significance of Treasury bond return predictability. Macroeconomic and aggregate liquidity variables contain predictive information for...

This paper conducts a comprehensive study on predicting the cross section of Chinese stock market returns with a large panel of 75 individual firm characteristics. We use not only the traditional Fama-MacBeth regression, but also “big-data” econometric methods: principal component analysis...

In this paper, we study investor sentiment in five major asset markets: stocks, bonds, commodities, currencies, and housing. Based on Thomson Reuter's sentiment measures extracted from 235 news and social media sources, we find that each market is predicted by its own sentiment. Cross-markets,...

Using time-series trends of a set of firms' major fundamentals, we find that there is a fundamentalmomentum in the stock market. Buying stocks in the top quintile of fundamental trends and selling stocks in the bottom quintile earns a monthly average return of 0.88%, whose magnitude is...

Using a large hand-collected dataset, we provide novel evidence on the additional information embedded in the designs and graphs of financial reports. We find that firms that add graphic financial reports experience a positive 2.7% abnormal returns in the following 3 to 6 months. The finding...

While common machine learning algorithms focus on minimizing the mean-square errors of model fit, we show that genetic programming, GP, is well-suited to maximize an economic objective, the Sharpe ratio of the usual spread portfolio in the cross-section of expected stock returns. In contrast to...