Showing 1 - 10 of 191
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...
Persistent link: https://www.econbiz.de/10014544801
achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian …
Persistent link: https://www.econbiz.de/10015145107
Many observers have forecast large partisan shifts in the US electorate based on demographic trends. Such forecasts are …
Persistent link: https://www.econbiz.de/10015094858
We propose a novel time-series econometric framework to forecast U.S. Presidential election outcomes in real time by …
Persistent link: https://www.econbiz.de/10015194984
consistent with a model of strategic diversification incentives in forecast reporting. Our results caution against the use of …
Persistent link: https://www.econbiz.de/10014337840
This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent,...
Persistent link: https://www.econbiz.de/10013362020
Portfolio optimization focuses on risk and return prediction, yet implementation costs critically matter. Predicting trading costs is challenging because costs depend on trade size and trader identity, thus impeding a generic solution. We focus on a component of trading costs that applies...
Persistent link: https://www.econbiz.de/10015094879
of the multi-step forecasting risk and the impulse response estimation risk to determine hyperparameters in settings …
Persistent link: https://www.econbiz.de/10015326468
This paper shows that shootings are predictable enough to be preventable. Using arrest and victimization records for almost 644,000 people from the Chicago Police Department, we train a machine learning model to predict the risk of being shot in the next 18 months. We address central concerns...
Persistent link: https://www.econbiz.de/10013334389
inserted into these images where the recent data are most similar to the historical data. This amounts to a forecast. The … traditional probit model used to forecast recessions inappropriately treats every observation as a separate experiment. This new …
Persistent link: https://www.econbiz.de/10013334464