The relationship among two or more than two sets of data can be measured with regression analysis.
Regression Analysis A statistical technique for fitting best line through data.
Regular Dividend Dividend that is expected to be maintained at regular time intervals.
Regression analysis could be used to estimate the unknown parameters β0, β1, and β2 in the relationship, using data on price, income, and quantity.
I use regression analysis on the whole S&P 500, where 'x' is the ROIC/COC ratio and 'y' is the Market Cap/Investment Capital ratio.
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Used in regression analysis, Kappa represents the ratio of the dollar price change in the price of an option to a 1% change in the expected price volatility.
Knock-In Option ...
coefficient of determination A measure of the correlation between the dependent and independent variables in a regression analysis. COGS Acronym for Cost Of Goods Sold. On an income statement, the cost of purchasing...
Simple linear regression A regression analysis between only two variables, one dependent and the other explanatory.
It is calculated through regression analysis and gives the trader an indication of what to expect based on how the benchmark index performs.
Several options exist for selecting the range of prices that will be included in the regression analysis (Data Range).
The Time Series Forecast indicator shows any statistical trend in a stock's price over a time period of length 'n' using linear regression analysis techniques.
Advice: The beta of a stock is calculated by running a regression analysis. The result is a beta coefficient. If the beta coefficient is 1, the stock tends to be as volatile as the stock market.
The trend is based on linear regression analysis. Rather than plotting a straight linear regression trendline, the Time Series Forecast plots the last point of multiple linear regression trendlines.
He devotes more than 100 pages to demonstrating regression analysis, a mathematical tool used in fundamental analysis.
While Linear Regression analysis can be helpful in determining where this point will fall, Standard Error Channel analysis can show if prices are cycling higher or lower than equilibrium and if a change in trend may be about to occur.
Beta Coefficient used in regression analysis. A beta of 1 indicates that the security's price will move with the market. A beta of less than 1 means that the security will be less volatile than the market.
Independent variable
Term used in regression analysis to represent the element or condition that is expected to influence another (so-called dependent) variable.
The Beta is difficult to calculate and it requires a regression analysis. Once you have the Beta for a particular investment portfolio, however, the calculation is simple.
A measure of the goodness of Fit of the relationship between the Dependent and independent variables in a Regression analysis; for instance, the percentage of variation in the Return of an Asset explained by the market Portfolio return.
This indicator attempts to forecast the price of the security using linear regression analysis.
Note in this case α is defined as excess return not the risk-adjusted excess return or Jensen's alpha calculated using regression analysis.
The longer term market can be analyzed using a regression analysis in channels, illustrating support and resistance levels that are based on longer term fundamentals and economic activity and the fundamental forecast into the future.
The trend is based on linear regression analysis. The Time Series Forecast plots the last point of multiple linear regression trendlines. The Time Series Forecast does not exhibit as much delay as a Moving Average when adjusting to price changes.
It may be estimated using ordinary least squares (OLS) regression analysis. Often an attribute vector (or dummy variable) is assigned to each characteristic or group of characteristics.
guess what a particular security's price would be tomorrow, a logical guess would be "fairly close to today's price." If prices are trending up, a better guess might be "fairly close to today's price with an upward bias." Linear regression analysis ...
Note: If you are unfamiliar with the formulas above, do not use this study without seeking assistance from a good statistics book. Regression analysis is a powerful statistical method when used properly.
By measuring exactly how large and significant each independent variable has historically been in its relation to the dependent variable, the future value of the dependent variable can be estimated. Essentially, regression analysis attempts to ...
Determining exactly how each of these variables effects the futures price is done through regression analysis which borrows heavily on economics and statistics.
Multicolinearity: The situation in which the independent variables used in a regression analysis are related to each other.
 See also: Analysis, Regression, Future, Market, Stock
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