A number of recent studies regress a “narratively” identified measure of a macroeconomic shock directly on an outcome variable. In this note, we argue that this approach can be viewed as the reduced-form regression of an instrumental variable approach in which the narrative time series is...

How did the rise of multinational enterprises (MNEs) put pressure on the prevailing international corporate tax framework? MNEs, and firms with market power, are not new phenomena, nor is the corporate income tax, which dates to the early 20th century. This prompts the question, what is...

We directly optimize portfolio weights as a function of firm characteristics via deep neural networks by generalizing the parametric portfolio policy framework. Our results show that network-based portfolio policies result in an increase of investor utility of between 30 and 100 percent over a...

We consider parametric portfolio policies of any complexity using deep neural networks to optimize investor utility. Risk aversion acts as an economic regularization mechanism, with higher risk aversion constraining model complexity. Empirically, Deep Parametric Portfolio Policies (DPPP)...

We provide data and code that successfully reproduces nearly all cross-sectional stock return predictors. Unlike most metastudies, we carefully examine the original papers to determine whether our predictability tests should produce t-stats above 1.96. For the 180 predictors that were clearly...