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Regression is a statistical method used in finance, investing, and other disciplines that attempts to determine the strength and character of the relationship between one dependent variable usually denoted by Y and a series of other variables known as independent variables.

Regression helps investment and financial managers to value assets and understand the relationships between variables, such as commodity prices and the stocks of businesses dealing in those commodities.

Simple linear regression uses one independent variable to explain or predict the outcome of the dependent variable Y, while multiple linear regression uses two or more independent variables to predict the outcome.

Regression can help finance and investment professionals as well as professionals in other businesses. Regression can also help predict sales for a company based on weather, previous sales, GDP growth, or other types of conditions.

The capital asset pricing model CAPM is an often-used regression model in finance for pricing assets and discovering costs of capital.

The general form of each type of regression is:. There are two basic types of regression: simple linear regression and multiple linear regression.

Regression takes a group of random variables , thought to be predicting Y, and tries to find a mathematical relationship between them.

This relationship is typically in the form of a straight line linear regression that best approximates all the individual data points.

In multiple regression, the separate variables are differentiated by using subscripts. Regression is often used to determine how many specific factors such as the price of a commodity, interest rates, particular industries, or sectors influence the price movement of an asset.

The aforementioned CAPM is based on regression, and it is utilized to project the expected returns for stocks and to generate costs of capital.

Beta is the stock's risk in relation to the market or index and is reflected as the slope in the CAPM model. The return for the stock in question would be the dependent variable Y, while the independent variable X would be the market risk premium.

Additional variables such as the market capitalization of a stock, valuation ratios, and recent returns can be added to the CAPM model to get better estimates for returns.

These additional factors are known as the Fama-French factors, named after the professors who developed the multiple linear regression model to better explain asset returns.

Financial Ratios. Financial Analysis. Fundamental Analysis. Risk Management. Fixed Income Essentials.

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Quetelet was responsible for making the procedure well-known and for using it extensively in the social sciences.

From Wikipedia, the free encyclopedia. Main article: Linear least squares. Main article: Trend estimation. Main article: Econometrics.

This section needs expansion. You can help by adding to it. January Mathematics portal. Analysis of variance Blinder—Oaxaca decomposition Censored regression model Cross-sectional regression Curve fitting Empirical Bayes methods Errors and residuals Lack-of-fit sum of squares Line fitting Linear classifier Linear equation Logistic regression M-estimator Multivariate adaptive regression splines Nonlinear regression Nonparametric regression Normal equations Projection pursuit regression Segmented linear regression Stepwise regression Structural break Support vector machine Truncated regression model.

Freedman Statistical Models: Theory and Practice. Cambridge University Press. A simple regression equation has on the right hand side an intercept and an explanatory variable with a slope coefficient.

Seal The earliest form of the linear regression was the least squares method, which was published by Legendre in , and by Gauss in Legendre and Gauss both applied the method to the problem of determining, from astronomical observations, the orbits of bodies about the sun.

The Annals of Statistics. Criminal Justice Review. Gifted Child Quarterly. Journal of the American Statistical Association.

The American Statistician. Craig International Statistical Review. Understanding Consumption. Oxford University Press. International Economics: Theory and Policy 9th global ed.

Harlow: Pearson. New York: Harper Collins. Modern Labor Economics 10th international ed. London: Addison-Wesley.

University of Pittsburgh. Cambridge: Harvard. Cohen, J. The Variation of Animals and Plants under Domestication. Darwin uses the term "reversion".

Draper, N. Applied Regression Analysis 3rd ed. John Wiley. Francis Galton. Facsimile at: [1] Robert S. Pindyck and Daniel L. Rubinfeld , 4h ed.

Econometric Models and Economic Forecasts , ch. Least squares and regression analysis. Least squares Linear least squares Non-linear least squares Iteratively reweighted least squares.

Pearson product-moment correlation Rank correlation Spearman's rho Kendall's tau Partial correlation Confounding variable. Ordinary least squares Partial least squares Total least squares Ridge regression.

Simple linear regression Ordinary least squares Generalized least squares Weighted least squares General linear model. Polynomial regression Growth curve statistics Segmented regression Local regression.

Generalized linear model Binomial Poisson Logistic. Response surface methodology Optimal design Bayesian design.

Numerical analysis Approximation theory Numerical integration Gaussian quadrature Orthogonal polynomials Chebyshev polynomials Chebyshev nodes.

Curve fitting Calibration curve Numerical smoothing and differentiation System identification Moving least squares. Regression analysis category Statistics category Mathematics portal Statistics outline Statistics topics.

Outline Index. Descriptive statistics. Mean arithmetic geometric harmonic Median Mode. Central limit theorem Moments Skewness Kurtosis L-moments.

Index of dispersion. Grouped data Frequency distribution Contingency table. Beta is the stock's risk in relation to the market or index and is reflected as the slope in the CAPM model.

The return for the stock in question would be the dependent variable Y, while the independent variable X would be the market risk premium.

Additional variables such as the market capitalization of a stock, valuation ratios, and recent returns can be added to the CAPM model to get better estimates for returns.

These additional factors are known as the Fama-French factors, named after the professors who developed the multiple linear regression model to better explain asset returns.

Financial Ratios. Financial Analysis. Fundamental Analysis. Risk Management. Fixed Income Essentials. Technical Analysis. Investopedia uses cookies to provide you with a great user experience.

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