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Econometrics & Regression

Regression and econometric methods used to estimate relationships, exposures and causal-looking associations with appropriate diagnostics. This category groups related methods so readers can move from the underlying idea to implementation, interpretation and model risk without searching across an undifferentiated master list.

32 conceptsDefinitions + formulasWorked mini-examples

What this category covers

Regression and econometric methods used to estimate relationships, exposures and causal-looking associations with appropriate diagnostics. Each concept page explains the quantitative meaning, how the idea is used in portfolio or market analysis, the relevant formula or analytical framework, variables, a compact example and the main limitations to keep in view.

Core concepts

Quick entry points

All Econometrics & Regression concepts

32 entries
Quantitative Finance

ANOVA for Regression

ANOVA for Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Arellano-Bond Estimator

Arellano-Bond Estimator is a quantitative-finance concept used within econometrics & regression. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Bayesian Linear Regression

Bayesian Linear Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Bayesian Regression

Bayesian Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Between Estimator

Between Estimator is a quantitative-finance concept used within econometrics & regression. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Breusch-Godfrey Test

Breusch-Godfrey Test is a statistical diagnostic used in econometrics & regression to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.

Quantitative Finance

Breusch-Pagan Test

Breusch-Pagan Test is a statistical diagnostic used in econometrics & regression to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.

Quantitative Finance

Cross-Sectional Regression

Cross-Sectional Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Dynamic Panel Model

Dynamic Panel Model is a quantitative model or framework used in econometrics & regression to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.

Quantitative Finance

Elastic Net Regression

Elastic Net Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Errors-in-Variables Model

Errors-in-Variables Model is a quantitative model or framework used in econometrics & regression to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.

Quantitative Finance

Fama-MacBeth Regression

Fama-MacBeth Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

First-Difference Estimator

First-Difference Estimator is a quantitative-finance concept used within econometrics & regression. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Fixed Effects Model

Fixed Effects Model is a quantitative model or framework used in econometrics & regression to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.

Quantitative Finance

Generalized Additive Model

Generalized Additive Model is a quantitative model or framework used in econometrics & regression to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.

Quantitative Finance

Generalized Least Squares Regression

Generalized Least Squares Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Hausman Test

Hausman Test is a statistical diagnostic used in econometrics & regression to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.

Quantitative Finance

Heckman Selection Model

Heckman Selection Model is a quantitative model or framework used in econometrics & regression to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.

Quantitative Finance

Hierarchical Bayesian Model

Hierarchical Bayesian Model is a quantitative model or framework used in econometrics & regression to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.

Quantitative Finance

Huber Regression

Huber Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Instrumental Variables Regression

Instrumental Variables Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Kernel Regression

Kernel Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Lasso Regression

Lasso Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Least Absolute Deviations Regression

Least Absolute Deviations Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Local Polynomial Regression

Local Polynomial Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Logistic Regression

Logistic Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Median Regression

Median Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Mixed Effects Model

Mixed Effects Model is a quantitative model or framework used in econometrics & regression to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.

Quantitative Finance

Multilevel Model

Multilevel Model is a quantitative model or framework used in econometrics & regression to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.

Quantitative Finance

Multiple Linear Regression

Multiple Linear Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Negative Binomial Regression

Negative Binomial Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

Quantitative Finance

Nonparametric Regression

Nonparametric Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.

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