E-Book, Englisch, 315 Seiten, eBook
Takayasu / Watanabe Econophysics Approaches to Large-Scale Business Data and Financial Crisis
1. Auflage 2010
ISBN: 978-4-431-53853-0
Verlag: Springer Tokyo
Format: PDF
Kopierschutz: 1 - PDF Watermark
Proceedings of Tokyo Tech-Hitotsubashi Interdisciplinary Conference + APFA7
E-Book, Englisch, 315 Seiten, eBook
ISBN: 978-4-431-53853-0
Verlag: Springer Tokyo
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Financial Market Properties.- Trend Switching Processes in Financial Markets.- Nonlinear Memory and Risk Estimation in Financial Records.- Microstructure and Execution Strategies in the Global Spot FX Market.- Temporal Structure of Volatility Fluctuations.- Theoretical Base of the PUCK-Model with Application to Foreign Exchange Markets.- Financial Crisis and Macroeconomics.- Financial Bubbles, Real Estate Bubbles, Derivative Bubbles, and the Financial and Economic Crisis.- Global and Local Approaches Describing Critical Phenomena on the Developing and Developed Financial Markets.- Root Causes of the Housing Bubble.- Reconstructing Macroeconomics Based on Statistical Physics.- How to Avoid Fragility of Financial Systems: Lessons from the Financial Crisis and St. Petersburg Paradox.- General Methods and Social Phenomena.- Data Centric Science for Information Society.- Symbolic Shadowing and the Computation of Entropy for Observed Time Series.- What Can Be Learned from Inverse Statistics?.- Communicability and Communities in Complex Socio-Economic Networks.- On World Religion Adherence Distribution Evolution.
"Data Centric Science for Information Society (p. 211-212)
Genshiro Kitagawa
Abstract Due to rapid development of information and communication technologies, the methodology of scientific research and the society itself are changing. The present grand challenge is the development of the cyber-enabled methodology for scientific researches to create knowledge based on large scale massive data. To realize this, it is necessary to develop a method of integrating various types of information. Thus the Bayes modeling becomes the key technology. In the latter half of the paper, we focus on time series and present general state-space model and related recursive filtering algorithms. Several examples are presented to show the usefulness of the general state-space model.
1 Change of Society and Scientific Research
By the progress of information and communication technologies (ICT), large-scale massive heterogeneous data have accumulated in various fields of scientific researches and society. As examples, we may consider the microarray data in life science, POS data in marketing, high-frequency data in finance, all-sky CCD image in astronomy, and various data obtained in environmental science and earth science, etc.
These rapid developments changed the society and the research methodologies in science and technology. In the information society, the information became as worthy as the substances and the energy, and the quantity of information was the crucial factor for the success in the society. However, in this twenty-first century, the so-called ubiquitous society is becoming widespread, where everybody can access to huge amount of information anywhere and anytime.
If such ubiquitous society is actually realized, the value of information itself will be depreciated, because everybody can share most information in common. Therefore, the interest in the development of the methods and technologies for information extraction and knowledge creation has grown, because the success and failure in the ubiquitous society depends on whether one can extract essential information from massive data. everybody can share most information in common. Therefore, the interest in the development of the methods and technologies for information extraction and knowledge creation has grown, because the success and failure in the ubiquitous society depends on whether one can extract essential information from massive data.
2 Data Centric Science: A Cyber-Enabled Methodology
2.1 Expansion of Research Object and Change in Scientific Methodology Based on ICT
The scientific research until the nineteenth century has developed basically under Newton–Descartes paradigm based on a mechanic view of the world. In this deductive approach, i.e., in theoretical sciences, mathematics played an important role as the language of science. However, the evolutionism advocated by C. Darwin in mid-nineteenth century concluded that every creature in real world evolves and changes with time. Motivated by such changes of view on the real world, K. Pearson declared in 1891 that everything in the real world can be an object of scientific research, and advocated the grammar of science [15]."
