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Titlebook: Econophysics of Markets and Business Networks; Arnab Chatterjee,Bikas K. Chakrabarti Book 2007 Springer-Verlag Milan 2007 Banking.Econophy

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41#
發(fā)表于 2025-3-28 17:34:30 | 只看該作者
42#
發(fā)表于 2025-3-28 19:37:09 | 只看該作者
Dynamical Structure of Behavioral Similarities of the Market Participants in the Foreign Exchange Ma and capacity of storages leads to accumulation of activity records of market participants, high frequency financial data. By utilizing the high frequency financial data one can observe behavior of the market participants with high resolutions and analyze a large amount of data enough to quantify them in the statistically significant.
43#
發(fā)表于 2025-3-29 00:02:19 | 只看該作者
Book 2007e current econophysics researches in the structure and functioning of these complex financial network systems. Leading researchers in the respective fields will report on their recent researches and review on the contemporary developments. The book will also include the comments and debates on the latest issues arising out of these.
44#
發(fā)表于 2025-3-29 03:53:04 | 只看該作者
https://doi.org/10.1007/978-3-322-91987-8aptures the dynamical variations quite well through Padē type of map equations. The low-pass coefficients representing the smooth part of the data has also been modelled. We further study the nature of the temporal variations in the returns.
45#
發(fā)表于 2025-3-29 07:34:41 | 只看該作者
https://doi.org/10.1007/978-1-4842-5995-5 studied in detail the variations of different network related quantities associated with the ITN. Our observation is that the ITN has also a scale invariant structure like many other real-world networks.
46#
發(fā)表于 2025-3-29 14:36:33 | 只看該作者
Daniela Sustac Roman,André B. Charettesicists network, an evolutionary model for weighted networks is proposed. The model shows the scale-free phenomena in degree and vertex weight distribution. The results of short term evolution are consistent well qualitatively with the empirical results.
47#
發(fā)表于 2025-3-29 18:07:43 | 只看該作者
48#
發(fā)表于 2025-3-29 23:42:43 | 只看該作者
49#
發(fā)表于 2025-3-30 00:59:49 | 只看該作者
Objektorientierte Programmierung, European day-ahead electricity markets (NordPool, APX, Powernext). We implement a generic non-parametric method, known as Cholesky factor algorithm, in order to remove the strong seasonality and the linear autocorrelation structure observed in power prices. The filtered NordPool and Powernext data
50#
發(fā)表于 2025-3-30 05:20:11 | 只看該作者
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