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Visualization and statistical modeling of financial big data: double-log modeling with skew-symmetric error distributions
2018
Japanese Journal of Statistics and Data Science
This study considers the visualization and statistical modeling of financial data (e.g., sales, assets, etc.) for a large data set of global firms that are listed and delisted. We present exploratory data analysis carried out in the R programming language. The results show that a double-log model with a skew-t error distribution is useful for modeling a firm's total sales volume (in thousands of U.S. dollars) as a function of its number of employees and total assets (in thousands of U.S.
doi:10.1007/s42081-018-0019-1
fatcat:xin5pg7nmvgdfddmsfcbk6mgnq