I study the effects of short sale constraints in a rational framework with asymmetric information. I consider the cases of Bernoulli-distributed (à la Glosten and Milgrom) and continuously distributed (à la Kyle) liquidation values, and focus on the latter case.In this case my model is able to...

This paper investigates the pricing of single-asset autocallable barrier reverse convertibles in the Heston local-stochastic volatility (LSV) model. Despite their complexity, autocallable structured notes are the most traded equity-linked exotic derivatives. The autocallable payoff embeds an...

Using administrative data on deposits and loans of every Norwegian with every Norwegian bank, we show that an existing deposit account makes a household more likely to hold deposits at the same bank later despite better alternatives and more likely to borrow there. Consistent with this, banks...

We document the existence of a premium in the green bond market based on the greenness of green bonds. Using BERT, a natural language processing method for textual analysis, we develop a novel measure for bonds’ greenness and document that a 10 percent increase in the bond’s greenness...

We propose that investment strategies should be evaluated based on their net-of-trading-cost return for each level of risk, which we term the "implementable efficient frontier." While numerous studies use machine learning return forecasts to generate portfolios, their agnosticism toward trading...

Empirical studies investigate various causes and effects of sustainable investments. While some attempts have been made to describe the results found by theoretical models, these are relatively complex and idiosyncratic. We relate to existing studies and use a parsimonious CAPM in which we model...

Tweet-level data from a social media platform reveals low average accuracy and high dispersion in the quality of advice by financial influencers, or “finfluencers”: 28% of finfluencers are skilled, generating 2.6% monthly abnormal returns, 16% are unskilled, and 56% have negative skill...

We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and...

We estimate the transmission of the pandemic shock in 2020 to prices in the residential and commercial real estate market by causal machine learning, using new granular data at the municipal level for Germany. We exploit differences in the incidence of Covid infections or short-time work at the...

“Buy Now, Pay Later” (BNPL) and other forms of consumer credit create a wedge between consumption and payments. We introduce this wedge into a standard consumption-based asset pricing model (CCAPM). In equilibrium, the pricing kernel equals the marginal utility of consumption divided by the...