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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.
Produkteigenschaften
- Artikelnummer: 9789811622991
- Medium: Buch
- ISBN: 978-981-16-2299-1
- Verlag: Springer Nature Singapore
- Erscheinungstermin: 27.06.2022
- Sprache(n): Englisch
- Auflage: 1. Auflage 2021
- Serie: Evolutionary Economics and Social Complexity Science
- Produktform: Kartoniert
- Gewicht: 248 g
- Seiten: 140
- Format (B x H x T): 155 x 235 x 9 mm
- Ausgabetyp: Kein, Unbekannt