Suppose each stock in Andre’s portfolio has a correlation coefficient of 0.40 (ρ = 0.40) with each of the other stocks. The market’s average standard deviation is approximately 20%, and the weighted average of the risk of the individual securities in the partially diversified four-stock portfolio is 33%. If 40 additional, randomly selected stocks with a correlation coefficient of 0.30 with the other stocks in the portfolio were added to the portfolio, what effect would this have on the portfolio’s standard deviation (σpσp)? It would gradually settle at approximately 20%. It would decrease gradually, settling at about 0%. It would stay constant at 33%. It would gradually settle at approximately 50%.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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