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Cokurtosis Tutorchrome
Cokurtosis can be defined as the statistical measure that calculates the degree of the peak of a variable's probability distribution. The variable probability distribution is in relation to another variable's peakedness and all other things equal. A higher co-kurtosis which means that the first variable has a flatter probability distribution.
Cokurtosis can be used as a supplement to the covariance calculation of risk estimation and usually, Cokurtosis is calculated using a security's historic price data as the first variable and the second variable is the market's historic price data. If the Cokurtosis is calculated in this way this provides an estimation of the security's risk in relation to the market. For a risk-adverse investor a Cokurtosis which is low is preferred and a lower Cokurtosis, in this case, depicts that the security's returns would not be much different from the market's returns
A Cokurtosis can be defined as the metric that is used to determine the probability of occurrence and this is used to measures the degree of the peak of one variable probability when compared to another variable and the price data is often used to assess a security risk when compared to the overall marketplace.
The co-kurtosis has an impact on asset pricing using a four-moment capital asset pricing model. Using this pricing model it is shown that, in the presence of skewness as well as kurtosis in asset return distribution, the excess rate of return that is expected is related not only to the systematic variance. It is also related to the systematic skewness as well as systematic kurtosis. Investors are remunerated in higher expected return for bearing the systematic variance and the systematic kurtosis risks and the investors will also forego the expected excess return for taking the benefit of increasing the systematic skewness.
Co-kurtosis has an impact on real estate pricing which shows that the presence of kurtosis and the expected excess rate of return is related not only to the systematic variance and systematic skewness as well as to systematic kurtosis. Investors should demand more compensation in terms of expected excess rate of return and results point out that real estate systematic kurtosis displays significant risk-return characteristic, and that systematic variance, as well as Cokurtosis, are more important than co-skewness in pricing real estate securities.
