Econophysics Approaches to Large-Scale Business Data and Financial Crisis: Proceedings of Tokyo Tech-Hitotsubashi Interdisciplinary Conference + APFA7
Misako Takayasu, Tsutomu Watanabe, Hideki Takayasu
Springer Science & Business Media, Apr 27, 2010 - Science - 315 pages
In recent years, as part of the increasing “informationization” of industry and the economy, enterprises have been accumulating vast amounts of detailed data such as high-frequency transaction data in nancial markets and point-of-sale information onindividualitems in theretail sector. Similarly,vast amountsof data arenow ava- able on business networks based on inter rm transactions and shareholdings. In the past, these types of information were studied only by economists and management scholars. More recently, however, researchers from other elds, such as physics, mathematics, and information sciences, have become interested in this kind of data and, based on novel empirical approaches to searching for regularities and “laws” akin to those in the natural sciences, have produced intriguing results. This book is the proceedings of the international conference THICCAPFA7 that was titled “New Approaches to the Analysis of Large-Scale Business and E- nomic Data,” held in Tokyo, March 1–5, 2009. The letters THIC denote the Tokyo Tech (Tokyo Institute of Technology)–Hitotsubashi Interdisciplinary Conference. The conference series, titled APFA (Applications of Physics in Financial Analysis), focuses on the analysis of large-scale economic data. It has traditionally brought physicists and economists together to exchange viewpoints and experience (APFA1 in Dublin 1999, APFA2 in Liege ` 2000, APFA3 in London 2001, APFA4 in Warsaw 2003, APFA5 in Torino 2006, and APFA6 in Lisbon 2007). The aim of the conf- ence is to establish fundamental analytical techniques and data collection methods, taking into account the results from a variety of academic disciplines.
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algorithm analysis analyze approach asset autocorrelation average banks behavior best price communicability communities complex consider correlation dimension correlations corresponding crash crisis data set decreasing distribution DJIA dynamics Econ economic econophysics empirical estimated evolution example exponential fear factor financial markets financial time series finite-time singularities firms fluctuations fractal function Gaussian global Havlin Hloc house price housing bubble Hurst exponent increasing indices inter-trade inverse statistics log-periodic loss Lyapunov exponents macroeconomics market price maximum microtrends multifractal negative microtrends nodes noise nonlinear number of adherents observed obtained order book parameters partition plot power law predicted price time series price-to-rent ratio probability random walk religions Renormalized return intervals risk scaling Sect shown in Fig shows simulated Sornette Springer Stanley state-space model statistical physics stochastic stock market stylized facts symbolic dynamics Takayasu H trading trend volatility volume