Turbulence is one of the most expensive problems in computing. Simulating the chaotic swirl of air over a wing or the churn ...

Numbers are the language of science—yet in research articles, they are often buried within the text and difficult to analyze.

A Berkeley-trained quantitative researcher who developed quantitative approaches to align internal credit assessments with ...

TradeSmith, a brand under MarketWise, has introduced Predictive Alpha, an artificial intelligence system developed to ...

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.

Flash floods are among the deadliest weather events in the world, killing more than 5,000 people each year. They’re also among the most difficult to predict. But Google thinks it has cracked that ...

A team of scientists from around the world has created the first system that can predict when and where extremely powerful solar storms, called superflares, are most likely to happen. These storms can ...

ABSTRACT: Forecasting future expected returns out-of-sample is challenging due to some statistical characteristics, such as the stochastic and dynamic nature in the time series. Conventional machine ...

The vast majority of asset management companies today use model portfolios. One question we’ve been asked many times is whether ValuEngine stock ratings can be used for portfolio management or merely ...

Abstract: Intelligent financial forecasting models play a crucial role in warnings of market crashes, market recovery, portfolio optimization, and risk control. Among deep learning methods, graph ...

Every three months, participants in the Metaculus forecasting cup try to predict the future for a prize pot of about $5,000. Metaculus, a forecasting platform, poses questions of geopolitical ...