Recent empirical studies suggest that demand and supply factors have important effects on bond yields. Both market segmentation and preferred habitat hypothesis are used to explain these demand and supply effects. In this paper, we use an affine preferred-habitat term structure model and the...

While economic variables have been used extensively to forecast bond risk premia, little attention has been paid to technical indicators which are widely used by practitioners. In this paper, we study the predictive ability of a variety of technical indicators vis-a-vis the economic variables....

We use machine learning to estimate sparse principal components (PCs) for 120 monthly macro variables spanning 1960:02 to 2018:06 from the FRED-MD database. For comparison, we also extract the first ten conventional PCs from the macro variables. Each of the conventional PCs is a linear...

This paper constructs an investor sentiment measure at both individual bond and aggregate levels, uncovering the first evidence that investor sentiment has strong cross- sectional predictive power for corporate bond returns. High bond investor sentiment leads to low future returns. A portfolio...

We construct an information factor (INFO) using the informed stock buying of corporate insiders and the informed selling of short sellers and option traders. INFO strongly predicts future stock returns -- a long-short portfolio formed on INFO earns monthly alphas of 1.24%, substantially...

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...

We study whether the similarity of firm disclosures on the Compensation Discussion and Analysis (CD&A) has predictability for future stock returns. We find that changes to the language and construction of the CD&As predict firms' future stock returns. A portfolio that longs the CD&A...

We analyze the daily predictability of investor sentiment across four major asset classes and compare sentiment measures based on news and social media with those based on trade information. For the majority of assets, trade-based sentiment measures outperform their text-based equivalents for...

In this replication paper, we extend Kelly, Malamud, and Pedersen (2021)'s new asset pricing framework to allow incorporating multiple predictive signals into optimal principal portfolios. Empirically, we find that the multi-signal theory is valuable for combining signals, improving a naive...

To understand theoretically why the 1/N rule is very difficult to beat, we show that the usual estimated investment strategies are biased even asymptotically when the dimensionality is high relative to sample size, and the 1/N rule is optimal in a one-factor model with diversifiable risks as...