A new study shows why traditional valuation ratios like price/dividend and CAPE fail to predict stock returns—and how ...

The traditional spreadsheet model of financial planning is officially broken. It did not break quietly, and it was not broken ...

Background: Ensuring the consistent availability of operating theatre supplies is critical for safe surgical care. However, supply chain disruptions remain common in low ...

Online prediction markets are taking bets on everything from climate change to quantum computing. But researchers question their accuracy ...

Abstract: Accurate load forecasting is critical for efficient and reliable grid operations, particularly given increasing volatility caused by atypical events such as extreme weather, policy changes, ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

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 ...

Accurate medium-to-long-term electricity price forecasting constitutes a critical prerequisite for electricity market participants to formulate optimal bidding strategies and mitigate energy ...

With increasing uncertainties on both the generation and load sides in power systems, ultra-short-term load forecasting (USTLF) and risk assessment have become crucial for ensuring the secure and ...

Startups should utilize both top-down and bottom-up forecasting methods to combine market insights with company-specific data for accurate projections. Employ quantitative techniques like the Percent ...

Utilize quantitative methods like Simple Linear Regression and Percent of Sales to analyze historical data for accurate financial predictions. Incorporate qualitative approaches such as expert ...

A new AI tool to predict the spread of infectious disease outperforms existing state-of-the-art forecasting methods. The tool, created with federal support by researchers at Johns Hopkins and Duke ...