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An Empirical Study on the Logarithmic Return of Securities

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Objective: Previous studies have shown that the distribution of security returns has the characteristics of peak and fat tail, and it is not realistic to use logarithmic normal distribution to describe security returns. This paper mainly studies the specific form of security returns distribution and conducts empirical research. Methods: We first assume that the security returns follow a logarithmic t-distribution. Then, the maximum likelihood estimation and moment estimation are used to explore the degree of freedom of the distribution. Finally, the goodness of fit test is used to conduct an empirical analysis about Shanghai Securities Composite Index. Results: The specific expression formulas for the estimator of the degree of freedom are obtained. Empirical testing shows that the security returns follow a logarithmic t-distribution. Conclusion: The probability distribution of security returns is unrealistic to assume that the security returns follow the logarithmic normal distribution. It is more practical to use the logarithmic t-distribution to characterize the distribution of security returns. Our results provide theoretical assistance for exploring the pricing of financial derivatives.
Title: An Empirical Study on the Logarithmic Return of Securities
Description:
Objective: Previous studies have shown that the distribution of security returns has the characteristics of peak and fat tail, and it is not realistic to use logarithmic normal distribution to describe security returns.
This paper mainly studies the specific form of security returns distribution and conducts empirical research.
Methods: We first assume that the security returns follow a logarithmic t-distribution.
Then, the maximum likelihood estimation and moment estimation are used to explore the degree of freedom of the distribution.
Finally, the goodness of fit test is used to conduct an empirical analysis about Shanghai Securities Composite Index.
Results: The specific expression formulas for the estimator of the degree of freedom are obtained.
Empirical testing shows that the security returns follow a logarithmic t-distribution.
Conclusion: The probability distribution of security returns is unrealistic to assume that the security returns follow the logarithmic normal distribution.
It is more practical to use the logarithmic t-distribution to characterize the distribution of security returns.
Our results provide theoretical assistance for exploring the pricing of financial derivatives.

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