We propose a belief-generating model from which we build a statistical measure of investor disagreement. We simulate differences in beliefs across investors by endowing them with different machine learning models for forecasting returns from the same set of inputs. We measure disagreement as the...

We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...

We propose and implement a procedure to optimally hedge climate change risk. First, we construct climate risk indices through textual analysis of newspapers. Second, we present a new approach to compute factor mimicking portfolios to build climate risk hedge portfolios. The new mimicking...

Stock momentum, long-term reversal, and other past return characteristics that predict future returns also predict future realized betas, suggesting these characteristics capture time-varying risk compensation. We formalize this argument with a conditional factor pricing model. Using...

We propose and implement a procedure to dynamically hedge climate change risk. To create our hedge target, we extract innovations from climate news series that we construct through textual analysis of high-dimensional data on newspaper coverage of climate change. We then use a mimicking...

We propose and implement a procedure to dynamically hedge climate change risk. To create our hedge target, we extract innovations in climate news series that we construct through textual analysis of high-dimensional data on newspaper coverage of climate change. We then use a mimicking-portfolio...

In this article, the authors document robust momentum behavior in a large collection of 65 widely studied characteristic-based equity factors around the globe. They show that, in general, individual factors can be reliably timed based on their own recent performance. A time series “factor...

We study the pricing of shocks to uncertainty and volatility using a novel and wide-ranging set of options contracts. If uncertainty shocks are viewed as bad by investors, portfolios that hedge them should earn negative premia. Empirically, however, such portfolios have historically earned...

We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news series that we construct through textual analysis of newspapers. We then use a mimicking portfolio approach to build climate change hedge portfolios. We discipline the exercise...