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13:40-14:00 USST President Prof. Xiaoming Xu and Prof. Yi-Cheng Zhang:
Symposium Welcome
14:00-14:50 Prof. Gene Stanley (Boston University,USA)
Title: ISOLATED NETWORKS AND COUPLED NETWORKS---A BRIEF INTRODUCTION
14:50-15:10 Photo Taking and Coffee Break
15:10-16:10 Prof. Luciano Pietronero (ISC-CNR and Univ. Sapienza, Roma, Italy)Title: THE ECONOMIC COMPLEXITY OF COUNTRIES AND PRODUCTS
16:10-17:00 Prof. Didier Sornette (ETH,Switzerland)
Title: The US stock market leads the Federal funds rate and Treasury bond yields
H. Eugene Stanley [hes@bu.edu]
Departments of Physics and Chemistry, Boston University, Boston, MA 02215 USA
We will introduce the ``modern theory of networks'' in terms understandable to the nonspecialist. Then we will describe specific examples that support the idea that there are universal features that characterize networks, whether they appear in internet, airline routes, or even networks of sexual contacts.
As an example, we will discuss very recent work [1-3], emphasizing its direct applicability to specific problems of preventing network breakdown. The key concept is that systems comprised of more than one network are vastly more susceptible to failure cascades than isolated networks. We also discuss potential applications to understanding financial breakdowns.
This work was carried out in collaboration with a number of colleagues, chief among whom are S. Havlin & R. Parshani (Bar-Ilan), S. V. Buldyrev (Yeshiva U), T. Preis and J. J. Schneider (Mainz), X. Gabaix (MIT and Princeton), X. Huang, J. Gao, V. Plerou, G. Paul, and P. Gopikrishnan (Boston University).
[1] S. V. Buldyrev, R. Parshani, G. Paul, H. E. Stanley, and S. Havlin, ``Catastrophic Cascade of Failures in Interdependent Networks'' Nature 464, 1025--1028 (2010). Accompanied by ``News Views'' article by A. Vespignani on pp. 984--985.
[2] J. Gao, S. V. Buldyrev, S. Havlin and H. E. Stanley, ``Robustness of a Network of Networks'' Phys. Rev. Lett. (under review).
[3] X. Huang, J. Gao, S. V. Buldyrev, S. Havlin, and H. E. Stanley, ``Robustness of Interdependent Networks under Targeted Attack'' Phys. Rev. Rapid Communications 83 (2011).
Title: THE ECONOMIC COMPLEXITY OF COUNTRIES AND PRODUCTS
Luciano Pietronero
ISC-CNR and Univ. Sapienza, Roma, Italy
luciano.pietronero@roma1.infn.it
We discuss a recent new approach to the complexity of countries and products in the spirit of the recent papers by Hidalgo and Hausmann (PNAS 2009). The basic information is represented by the matrix of countries and exported products. The standard economic analysis is essentially based on the GDP but the diversification of this into a series of different products provides an additional element of fitness in the spirit of biodiversification in a fluctuating enviroment. In fact the idea that specialization of countries towards certain specific products is considered as optimal in the standard analysis, but this could only be valid in a static situation. The strongly dynamical situation of the world market suggests that flexibility and adaptability are also important elements. The basic idea is to introduce a Fitness parameter for each country which is able to take into consideration this effect. Such an analysis, selfconsistently also leads to a ranking of the Quality of the products. These concepts are implemented with the use of statistical concepts inspired to the page rank (Google) problem may lead to a novel classification for the fitness of the countries and the quality of products which adds new information with respect to the standard economic analysis. This information can be used in various ways. The direct comparison of the Fitness with the country GDP gives an assessment of the non expressed potential of the country. Also for each country it is possible to define the quality of the products exported and how competitive is this country with respect to the other countries which produce the same product. Finally it is possible to make a planning for the optimal development of a country by considering its potential for adding a new product.
The US stock market leads the Federal funds rate
and Treasury bond yields
Didier Sornette
ETH
Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we find very similar lead-lag dependence between the S&P500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including and especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen at key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis. This TOP method used here is generic to compare two time series and is of broad interest for matching patterns in financial time series in a systematic, non-parametric and precise way.
Title: Dynamical Moment Neuronal Network: Model and Approach
Tian-Ping Chen
Fudan University, Shanghai, China
Abstract: I shall present a theoretical framework on spike activities of leaky-and-integrate networks by including the first-order (mean firing rate) and the second-order statistics (variance and correlation), based on a moment neuronal network (MNN) approach. The dynamics and distribution of neural activities are approximated as a Gaussian random field. Using this novel model, I shall introduce analysis of several interesting phenomena of MNN and illustrate the computation capability of this model with experimental data.
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