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The Blume beta shrinks the estimated OLS beta towards a mean of 1, calculating the weighted average of 2/3 times the historical OLS beta plus 1/3. A version based on monthly rates of return is widely distributed by Capital IQ and quoted on all financial websites.
Beta is an important measure of one type of risk, but it doesn’t encapsulate all of a stock’s risk. Stocks are shares of real-life businesses , which subjects them to the economic fortunes of ...
Even if unavailable directly, the complete and incomplete beta function values can be calculated using functions commonly included in spreadsheet or computer algebra systems. In Microsoft Excel , for example, the complete beta function can be computed with the GammaLn function (or special.gammaln in Python's SciPy package):
In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1) in terms of two positive parameters, denoted by alpha (α) and beta (β), that appear as exponents of the variable and its complement to 1, respectively, and control the shape of the distribution.
Beta in this context is calculated as the covariance of the portfolio's returns with its benchmark's returns, divided by the variance of the benchmark's returns. A beta of 1.5 means that for every 1% change in the value of the benchmark, the portfolio's value tends to change by 1.5%.
In investing, upside beta is the element of traditional beta that investors do not typically associate with the true meaning of risk. [1] It is defined to be the scaled amount by which an asset tends to move compared to a benchmark, calculated only on days when the benchmark's return is positive.
You can calculate this ratio by adding up the value of your investments (not including your home equity) and dividing that by your net worth. Generally, you want this ratio to be at least 50% ...
Standardization of the coefficient is usually done to answer the question of which of the independent variables have a greater effect on the dependent variable in a multiple regression analysis where the variables are measured in different units of measurement (for example, income measured in dollars and family size measured in number of individuals).