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£80.65
Springer Statistical Properties in Firms’ Large-scale Data: 26 (Evolutionary Economics and Social Complexity Science, 26)
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Description
This is the first book to provide a systematic description of statistical properties of large-scale financial data. Specifically, the power-law and log-normal distributions observed at a given time and their changes using time-reversal symmetry, quasi-time-reversal symmetry, Gibrat's law, and the non-Gibrat's property observed in a short-term period are derived here. The statistical properties observed over a long-term period, such as power-law and exponential growth, are also derived. These subjects have not been thoroughly discussed in the field of economics in the past, and this book is a compilation of the author's series of studies by reconstructing the data analyses published in 15 academic journals with new data. This book provides readers with a theoretical and empirical understanding of how the statistical properties observed in firms’ large-scale data are related along the time axis. It is possible to expand this discussion to understand theoretically and empirically how the statistical properties observed among differing large-scale financial data are related. This possibility provides readers with an approach to microfoundations, an important issue that has been studied in economics for many years.
Product Specifications
- Brand
- Springer
- Format
- Paperback
- ASIN
- 981162299X
- Domain
- Amazon UK
- Release Date
- 27 June 2022
- Listed Since
- 30 May 2022
Barcode
No barcode data available
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