Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.

AI matches daily forecasts like never before, but when it comes to heat, cold, and wind records, HRES physics rules.

ESG indices in emerging markets often lack long, transparent historical records, making them difficult to analyze with ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. It's easy to forget that beneath the surface of every smart ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

The landscape of demand forecasting, data science and machine learning is rapidly evolving, as companies seek innovative approaches to handle the intricate intersection between technology and consumer ...

Supply chain forecasting is becoming an increasingly critical component of operational success. Accurate forecasting enables companies to optimize inventory levels, reduce waste, enhance customer ...

My print column examines the proliferation of statistical forecasting models for the Academy Awards, which will be handed out on Sunday night. After quantitative predictions did well in forecasting ...