Predictive Models

Adaptive Expectations: Understanding Economic Forecasting
An in-depth explanation of adaptive expectations in economics, where future values are calculated based on previous predictions and outcomes. Learn about its significance, models, and practical applications.
Delphi Technique: Predicting Future Outcomes Through Expert Consensus
The Delphi Technique is a structured communication method used to gather forecasts from a panel of experts, initially independently and subsequently by consensus. It is often used to predict future events or outcomes in various fields such as Economics, Technology, and Social Sciences.
Feature: An Attribute Used to Train Models
In machine learning, a feature is an attribute used to train models, playing a crucial role in the predictive performance of algorithms.
Feature Engineering: A Key Component in Machine Learning
Feature Engineering is the process of using domain knowledge to create features (input variables) that make machine learning algorithms work effectively. It is essential for improving the performance of predictive models.
Monte Carlo Simulation: A Comprehensive Overview
An in-depth article on Monte Carlo Simulation, its historical context, applications, models, examples, and significance in various fields such as finance, risk management, and decision-making.
Positive Economics: An Empirical Approach to Economics
Positive economics focuses on describing and explaining economic phenomena, making predictions without value judgements. It contrasts with normative economics, which prescribes policies based on subjective criteria.
Residuals: The Difference Between Observed and Predicted Values
An in-depth look at residuals, their historical context, types, key events, explanations, mathematical formulas, importance, and applicability in various fields.

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