This paper explores stock return predictability by exploiting the cross-section of oil futures prices. Motivated by the principal component analysis, we find the curvature factor of the oil futures curve predicts monthly stock returns: a 1% per month increase in the curvature factor predicts...

I extract three oil risk factors using oil futures prices and returns of oil related firms. The first factor accounts for news that uniformly affects expected oil prices at all horizons, the second factor accounts for news that affects near term expected oil prices, and the third factor accounts...

We propose that general purpose technologies (GPTs) — a class of technologies that have pervasive impacts on the economy and spill over across countries — are a source of non-diversifiable technology risk in international stock markets. We construct an empirical GPT factor from patent data...

We propose that innovative originality (InnOrig) is a valuable organizational resource, and that owing to limited investor attention and skepticism of complexity, firms with greater InnOrig are undervalued. We find that firms' InnOrig strongly predicts higher, more persistent, and less volatile...

These are the presentation slides for the paper "Innovative Efficiency and Stock Returns". The abstract of the paper is the following: We find that innovative efficiency (IE), patents or citations scaled by research and development expenditures, is a strong positive predictor of future returns...