New research reveals that "foundation models" trained on vast, general time-series data may be able to forecast river flows accurately, even in regions with little or no local hydrological records.

AI scenario planning doesn’t attempt to be “right” in the traditional forecasting sense. Its real value lies in systematic ...

A new way to solve data scarcity: Turning qualitative reports into quantitative data with an LLM.

Reliable and scalable water level prediction is crucial in hydrology for effective water resources management, especially ...

Driven Financial Analysis, Time-Series Analysis, Financial Market Infrastructure Farzaliyeva, A. (2026) Data Infrastructure and the Evolution of Financial Analytics in the U.S. FinTech Ecosystem.

US Treasury yields could rise toward 6% due to elevated inflation expectations and term premium normalization. Read the full analysis here.

Despite significant mathematical refinements, econometrics has shown the weaknesses of its logical underpinnings, primarily during economic turning points—financial crises, pandemics, and geopolitical ...

Researchers at the Federal Reserve recently published a paper on Kalshi's effectiveness in predicting certain economic ...

In light of recent global shocks and rising external volatility, there is a growing need to effectively monitor short-term economic fluctuations, especially in countries with limited access to ...