Visualization and statistical modeling of financial big data: double-log modeling with skew-symmetric error distributions

Masayuki Jimichi, Daisuke Miyamoto, Chika Saka, Shuichi Nagata
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.
more » ... ). This result is obtained by comparing the Akaike information criteria of several double-log models with independent and identically distributed random error terms with skew-symmetric distributions and by further evaluating the models using cross-validation.
doi:10.1007/s42081-018-0019-1 fatcat:xin5pg7nmvgdfddmsfcbk6mgnq