This paper investigates the impact of manager-investor interaction quality on stock returns by utilizing an online IPO roadshow dataset and leveraging a word-embedding model. We find that such interactions are positively valued, as reflected in initial returns. The effect is particularly pronounced for firms characterized by higher levels of information asymmetry, greater investor attention, increased question uncertainty, or discussions on topics not covered in prospectus. Additionally, our research reveals that effective management communication leads to increased first-day turnover rates and thus higher returns. These heightened returns persist up to 180 days following the IPO, without displaying a significant long-term reversal associated with interaction quality. These findings underscore the meaningful impact of the quality of manager-investor interactions on firm valuation.

The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that allows for flexible predictive distributions of oil prices that can depart from normality. This model, based on Bayesian additive regression trees, remains agnostic on the functional form of the conditional mean relations and assumes that the shocks are driven by a stochastic volatility model. We show that our nonparametric approach improves in terms of tail forecasts upon three competing models: quantile regressions commonly used for studying tail events, the Bayesian VAR with stochastic volatility, and the simple random walk. We illustrate the practical relevance of our new approach by tracking the evolution of predictive densities during three recent economic and geopolitical crisis episodes, by developing consumer and producer distress indices that signal the build-up of upside and downside price risk, and by conducting a risk scenario analysis for 2024.