Black-Scholes Model: What It Is, How It Works, and the Options Formula

Learn about the Black-Scholes model, how it works, and how its formula helps estimate fair option prices by weighing ...
Seeking Alpha

An S&P 500 Prediction Model Based On Macroeconomic Variables

Seeking Alpha article used statistical approach to estimate S&P 500 P/E market multiple based on macroeconomic variables. Treasury yield and federal spending to GDP ratio are significant variables ...
EurekAlert!

DVRE: dominator-based variables reduction of encoding for model-based diagnosis

DVRE cuts MaxSAT encoding size offline and clauses online, delivering the fastest complete MBD on ISCAS-85 for both single- ...

Critical Assumptions Economists Make in Economic Models

Discover how economists' assumptions shape economic models, affecting predictions about consumer behavior, resource ...
JSTOR Daily

Dropping Highly Collinear Variables from a Model

This is a preview. Log in through your library . Abstract Objective. To change the common practice of eliminating independent variables from models because they produce multicollinearity in an ...
ascopubs.org

Computing the Hazard Ratios Associated With Explanatory Variables Using Machine Learning Models of Survival Data

The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models ...
Bloomberg L.P.

Imputation of missing ESG data using deep latent variable models

In finance, data is often incomplete because the data is unavailable, inapplicable or unreported. Unfortunately, many classical data analysis techniques — for instance, linear regression — cannot ...