What is an 'Error Term'
An error term is a variable in a statistical or mathematical model, which is created when the model does not fully represent the actual relationship between the independent variables and the dependent variables. As a result of this incomplete relationship, the error term is the amount at which the equation may differ during empirical analysis. The error term is also known as the residual, disturbance or remainder term.
BREAKING DOWN 'Error Term'
An error term represents the margin of error within a statistical model, referring to the sum of the deviations within the regression line, that provides an explanation for the difference between the results of the model and actually observed results. The regression line is used as a point of analysis when attempting to determine the correlation between one independent variable and one dependent variable.The error term essentially means that the model is not completely accurate and results in differing results during realworld applications. For example, assume there is a multiple linear regression function that takes the form:
When the actual Y differs from the Y in the model during an empirical test, then the error term does not equal 0, which means there are other factors that influence Y.
Within a linear regression model that is tracking a stock’s price over time, the error term is the difference between the expected price at a particular time and the price that was actually observed. In instances where the price is exactly what was anticipated at a particular time, it will fall on the trend line and the error term is zero.
Points that do not fall directly on the trend line exhibit the fact that the dependent variable, in this case the price, is influenced by more than just the independent variable, representing the passage of time. The error term stands for any influence being exerted on the price variable, such as changes in market sentiment.
The two data points with the greatest distance from the trend line should be an equal distance from the trend line, representing the largest margin of error.
Linear Regression, Error Term and Stock Analysis
Linear regression is a form of analysis that relates to current trends experienced by a particular security or index by providing a relationship between a dependent and independent variable, such as the price of a security and the passage of time, resulting in a trend line that can be used as a predictive model.
A linear regression exhibits less delay than that experienced with a moving average, as the line is fit to the data points instead of based on the averages within the data. This allows the line to change more quickly and dramatically than a line based on numerical averaging of the available data points.

Regression
A statistical measure that attempts to determine the strength ... 
Heteroskedastic
A measure in statistics that refers to the variance of errors ... 
Stepwise Regression
The stepbystep iterative construction of a regression model ... 
Nonlinear Regression
A form of regression analysis in which data is fit to a model ... 
Least Squares Method
A statistical technique to determine the line of best fit for ... 
Accounting Error
An error in an accounting item that was not caused intentionally. ...

Insights
Understanding Regression
Regression is a statistical analysis that attempts to predict the effect of one or more variables on another variable. 
Investing
Regression Basics For Business Analysis
This tool is easy to use and can provide valuable information on financial analysis and forecasting. Find out how. 
Investing
3 Reasons Tracking Error Matters
Discover three ways investors can use tracking error to measure performance for a mutual fund or ETF, whether indexed or actively managed. 
Trading
The Linear Regression Of Time and Price
This investment strategy can help investors be successful by identifying price trends while eliminating human bias. 
Investing
Explaining Linear Relationships
A linear relationship describes the proportionality between an independent variable and a dependent variable. 
Investing
What's a Sensitivity Analysis?
Sensitivity analysis is used in financial modeling to determine how one variable (the target variable) may be affected by changes in another variable (the input variable). 
Investing
Calculating Tracking Error
Tracking error is the difference between the return on a portfolio or fund, and the benchmark it is expected to mirror (or track). 
Trading
When Is A Bull Market Not A Bull Market?
During some bull or bear moves in the stock markets, investors will be going with the trend, but day traders may find they cannot. 
Investing
Explaining Standard Error
Standard error is a statistical term that measures the accuracy with which a sample represents a population. 
Small Business
Calculating (Small) Company Credit Risk
Determining creditworthiness of smaller and mediumsized corporations isn't as easy as for larger companies, but these tips can help.

What are some of the more common types of regressions investors can use?
Learn about the most common types of regressions investors use to model asset prices including linear regressions and multiple ... Read Answer >> 
What is the difference between linear regression and multiple regression?
Learn the difference between linear regression and multiple regression and how multiple regression encompasses not only linear ... Read Answer >> 
How is the standard error used in trading?
Understand how the standard error is used in statistics and what it measures. Learn how the standard error is used in trading ... Read Answer >> 
How can I use a regression to see the correlation between prices and interest rates?
Learn how to use linear regression to calculate the correlation between stock prices and interest rates by taking the square ... Read Answer >> 
How can I run linear regressions in MATLAB?
Learn how to run linear regressions in MATLAB by loading data, specifying dependent and independent variables and using the ... Read Answer >> 
What is a relative standard error?
Find out how to distinguish between mean, standard deviation, standard error and relative standard error in statistical survey ... Read Answer >>