# R-squared

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## R Square

In statistics, the percentage of a portfolio's performance explainable by the performance of a benchmark index. The R square is measured on a scale of 0 to 100, with a measurement of 100 indicating that the portfolio's performance is entirely determined by the benchmark index, perhaps by containing securities only from that index. A low R square indicates that there is no significant relationship between the portfolio and the index. An R Square is also called the coefficient of determination. See also: Beta.

## R-squared.

R-squared is a statistical measurement that determines the proportion of a security's return, or the return on a specific portfolio of securities, that can be explained by variations in the stock market, as measured by a benchmark index.

For example, an r-squared of 0.08 shows that 80% of a security's return is the result of changes in the market -- specifically that 80% of its gains are due to market gains and 80% of its losses are due to market losses. The other 20% are the result of factors particular to the security itself.

References in periodicals archive ?
The correlation is found between anxiety and depression (p<0.0005), Where R-squared value is 0.1063.
En la Tabla 2, se observa el coeficiente de correlacion de Pearson (R-squared) igual a 0,2343 afirmando con este valor, que si existe relacion entre el Apalancamiento financiero y el precio de la accion.
This is why the single or multivariate models with or without change-points (Models 1, 2, and 3) produce very poor results with the very low R-squared values shown in Table 2, specifically for Buildings 1, 2, and 3 that have more different data clusters.
R-squared, the coefficient of determination, generally shows the percentage of the variation in the data the equation explains.
Extensive work has been done on SPS using R-squared obtained from the regression of individual stock return to stock market returns (Morck, Yeung, & Yu, 2000; Durnev, Li, Morck, & Yeung, 2004; Farooq & Ahmed, 2014; Farooq & ElBannan, 2016).
1 -0.001 (**) -1.61E-04 0.001 [3.17E-04] [2.54E-04] [4.17E-04] Constant 0.723 (***) 0.462 (***) 0.313 (***) [0.007] [0.006] [0.009] Individual Yes Yes Yes Fixed Effects Observations 10,781 16,109 9,041 R-squared 0.160 0.076 0.070 (4) (5) (6) VARIABLES Points Assists Steals After Jan.
The value of R-squared for the model is calculated as 0.9816 that is very close to one.
. regress TargetTotal Age Gender Baseline Control Source SS df MS Model 58.3156961 4 14.578924 Residual 3279.81 1252 2.61965655 Total 3338.1257 1256 2.65774339 Number of obs = 1257 F (4, 1252) = 5.57 Prob > F = 0.0002 R-squared = 0.017 Adj R-squared = 0.0143 Root MSE = 1.6185 TargetTotal Coef.
R-squared is a determination coefficient that represents the estimation of the total variation of the data described by the model.
Specifically, a linear fit (solid lines in Figure 5) yields R-squared of 0.066 (slope of 8.81 x [10.sup.-3]) for the airport size and of 0.067 (slope of 88.32) for the standard delay multiplier.
To validate the survey items, seven indices were computed: R-Squared, Adjusted R-Squared, Q-Squared, Cronbach's alpha, Average Variance Extracted (AVE), Average Block Variance Inflation Factor (VIF), and Average Full collinearity VIF (AFVIF).
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