The process of creating representations of economic processes to analyze and predict market behaviors.

Digital or virtual currency that uses cryptography for security and operates on decentralized networks.

Techniques used to analyze current and historical data to make predictions about future events.

Quantitative metrics used to assess the financial health and performance of an economy or investment.

The process of ensuring that data is accurate, complete, and meets the quality standards required for analysis.

A statistical measure of the dispersion of returns for a given security, indicating its risk level.

Statistics that provide insights into the economic performance and health of a market.

A statistical method used to determine the relationships between variables and predict outcomes.

A subset of artificial intelligence that enables systems to learn from data and improve over time.

Past data used to analyze trends and patterns, crucial for validating predictive models.

Conditions accepted as true for the purpose of building a model, influencing its outcomes.

The process of evaluating a model's performance and reliability against real-world data.

A field of economics that studies how psychological factors affect economic decision-making.

Unpredictable occurrences that can impact market dynamics, such as political changes or natural disasters.

A method of comparing different data sets or indicators to draw insights and conclusions.

A process where colleagues evaluate each other's work to ensure quality and accuracy.

The written record of the modeling process, including methodologies, assumptions, and findings.

Specific situations where a model can be applied to solve real-world problems.

Understanding gained from data analysis that can inform decision-making and strategy.

Constraints or weaknesses in a model that may affect its applicability or accuracy.

An in-depth analysis of a specific instance or application of a model in a real-world scenario.

The ability to effectively communicate findings and methodologies to an audience.

The completed outputs of a project, including models, reports, and presentations.

The ability to interpret data and draw meaningful conclusions, essential for effective modeling.

The forces that impact the supply and demand of goods and services in a market.

The degree to which data can be depended upon for accurate analysis and decision-making.