Abstract: Time series forecasting is widely used in finance, meteorology, and industrial systems. Although existing methods have made progress in modeling trends and periodicity, they still face ...
As global economic and political volatility intensifies with the ongoing Iran conflict and other geopolitical tensions, the ...
Existing forecasting methods often force a trade-off: either train a highly specialized model for each site (which is costly and doesn't scale) or adapt a large, general-purpose model (which can be ...
With the increasing integration of renewable energy into power systems, accurate photovoltaic (PV) power forecasting has become crucial for maintaining grid stability, optimizing energy storage, and ...
Rising gasoline prices — and their impact on inflation as they flow through global economies — are the subject of a new study from Federal Reserve Bank of Dallas researchers. Authored by Dallas Fed ...
Uncertainties surrounding the Iran war briefly dropped the Dow Jones Industrial Average and Nasdaq Composite into correction territory. The Federal Reserve Bank of Cleveland's proprietary Inflation ...
ABSTRACT: We propose a hybrid approach that combines the time-series forecasting model and the ensemble learning algorithm to generate investor views in the Black-Litterman model. Specifically, we ...
Abstract: Forecasting inflation in Thailand is challenging because limited time series and strong external exposures create an imbalance between few observations and many potential predictors. We ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results