5-10 percent, reflecting impact uncertainty. Using hurricane forecasts, we show that landfall uncertainty and potential … forecasts than those from NOAA. Improvements to hurricane forecasts could have economically significant effects in financial …

prices do not promptly incorporate such climate change information, and firms with high climate change exposures are subject …

We document strong abnormal effects due to U.S. landfall hurricanes over the period 1990 to 2017 on stock returns and …-on-equity (ROE), and investment-to-assets (I/A). ROE- and I/A-related long/short factors are insensitive to hurricanes, while size …

In this paper, we estimate, model and forecast Realized Range Volatility, a new realized measure and estimator of the … distribution for the innovations. The analysis of the forecast performance during the different periods suggests that including the …

We propose two simple evaluation methods for time varying density forecasts of continuous higher dimensional random … variables. Both methods are based on the probability integral transformation for unidimensional forecasts. The first method … only its applicability to any continuous distribution but also the evaluation of the forecast accuracy in specific regions …

one month. We extend the methodology developed in Maheu and McCurdy (2011) to exploit the information content of intraday …, we show that models considering jumps apart from the continuous component consistently deliver better density forecasts …

indicate that the employment of PH information allows nonlinear and neural network models to better forecast RV during a … (RV) models to improve their forecast performance during turbulent periods. The results of the empirical experimentation …

effectively incorporate persistent homology (PH) into neural network models to increase their forecast accuracy in predicting … yields statistically significanlty more accurate forecasts than other forecasting models. The proposed model coined as …), NBEATSx-VP demonstrates a minimum 9% improvement in forecast precision compared to benchmark models. Considering Quasi …