周炜星
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 姓名：周炜星
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学术头衔：
教育部“新世纪优秀人才支持计划”入选者
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学科领域：
道路工程
 研究兴趣：
周炜星，2001年5月华东理工大学毕业，获工学博士学位，博士论文为“分形与应用多重分形及其在气液两相湍射流中的应用”，导师于遵宏教授。2001年6月至2004年5月在美国加利福尼亚大学洛杉矶分校师从Didier Sornette教授进行博士后研究，从事金融物理学和流体力学研究。2004年7月回华东理工大学国家重点化学工程联合实验室工作，副研究员，硕士生导师。2005年9月调华东理工大学商学院金融学系工作，金融学教授，担任应用数学专业博士生导师。主要从事金融物理学、复杂性科学、金融市场微观结构、虚拟世界、分形、流体力学等方向研究，截止2007年11月，已在国际学术期刊上发表文章四十余篇，被SCI和SSCI收录43篇，其中SSCI收录13篇。2003年获全国百篇优秀博士论文提名(未得奖)，2004年获上海市研究生优秀成果（学位论文）奖，2006年入选上海市青年科技启明星计划，2007年入选教育部新世纪优秀人才支持计划。

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18
【期刊论文】Predictability of large future changes in major financial indices
周炜星， Didier Sornette， ， WeiXing Zhou
International Journal of Forecasting 22 (2006)153168，0001，（）：
1年11月30日
We present a systematic algorithm which tests for the existence of collective selforganization in the behavior of agents in social systems, with a concrete empirical implementation on the Dow Jones Industrial Average index (DJIA) over the 20th century and on the Hong Kong Hang Seng composite index (HSI) since 1969. The algorithm combines ideas from critical phenomena, the impact of agents’ expectations, multiscale analysis, and the mathematical method with pattern recognition of sparse data. Trained on the three major crashes in DJIA of the century, our algorithm exhibits a remarkable ability for generalization and detects in advance 8 other significant drops or changes of regimes. An application to HSI gives promising results as well. The results are robust with respect to the variations of the recognition algorithm. We quantify the prediction procedure with error diagrams.
Econophysics， Multiscale analysis， Pattern recognition， Predictability， Multiscale analysis， Criticality， Logperiodicity

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周炜星， WeiXing Zhou ， ， Didier Sornette
Journal of Macroeconomics 28 (2006) 195224，0001，（）：
1年11月30日
We introduce a novel nonparametric methodology to test for the dynamical time evolution of the lag–lead structure between two arbitrary time series. The method consists in constructing a distance matrix based on the matching of all sample data pairs between the two time series. Then, the lag–lead structure is searched as the optimal path in the distance matrix landscape that minimizes the total mismatch between the two time series, and that obeys a onetoone causal matching condition. We apply our method to the question of the causality between the US stock market and the treasury bond yields and confirm earlier results on a causal arrow of the stock markets preceding the Federal Reserve Funds adjustments as well as the yield rates at short maturities in the period 2000–2003. The application to inflation, inflation change, GDP growth rate and unemployment rate unearths nontrivial causal relationships: the GDP changes lead inflation especially since the 1980s, inflation changes lead GDP only in the 1980 decade, and inflation leads unemployment rates since the 1970s. In addition, we detect multiple competing causality paths in which one can have inflation leading GDP with a certain lag time and GDP feeding back/leading inflation with another lag time.
Causality， Timedependent correlation， Distance matrix， Lead–lag， Time series， Stock markets， Bond yields， Inflation， GDP growth， Unemployment

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【期刊论文】Fundamental factors versus herding in the 2000–2005 US stock market and prediction
周炜星， WeiXing Zhou， Didier Sornette，
Physica A 360 (2006) 459482，0001，（）：
1年11月30日
We present a general methodology to incorporate fundamental economic factors to the theory of herding developed in our group to describe bubbles and antibubbles. We start from the strong form of rational expectation and derive the general method to incorporate factors in addition to the logperiodic power law (LPPL) signature of herding developed in ours and others’ works. These factors include interest rate, interest spread, historical volatility, implied volatility and exchange rates. Standard statistical AIC and Wilks tests allow us to compare the explanatory power of the different proposed factor models. We find that the historical volatility played the key role before August of 2002. Around October 2002, the interest rate dominated. In the first six months of 2003, the foreign exchange rate became the key factor. Since the end of 2003, all factors have played an increasingly large role. However, the most surprising result is that the best model is the secondorder LPPL without any factor. We thus present a scenario for the future evolution of the US stock market based on the extrapolation of the fit of the secondorder LPPL formula, which suggests that herding is still the dominating force and that the unraveling of the US stock market antibubble since 2000 is still qualitatively similar to (but quantitatively different from) the Japanese Nikkei case after 1990.
Econophysics， Stock markets， Antibubble， Modeling， Critical point， Logperiodicity， Economic factors， Prediction

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周炜星， Didier Sornette， ， WeiXing Zhou
Physica A 370 (2006) 704726，0001，（）：
1年11月30日
Following a long tradition of physicists who have noticed that the Ising model provides a general background to build realistic models of social interactions, we study a model of financial price dynamics resulting from the collective aggregate decisions of agents. This model incorporates imitation, the impact of external news and private information. It has the structure of a dynamical Ising model in which agents have two opinions (buy or sell) with coupling coefficients, which evolve in time with a memory of how past news have explained realized market returns. We study two versions of the model, which differ on how the agents interpret the predictive power of news. We show that the stylized facts of financial markets are reproduced only when agents are overconfident and misattribute the success of news to predict return to herding effects, thereby providing positive feedbacks leading to the model functioning close to the critical point. Our model exhibits a rich multifractal structure characterized by a continuous spectrum of exponents of the power law relaxation of endogenous bursts of volatility, in good agreement with previous analytical predictions obtained with the multifractal random walk model and with empirical facts.
Ising model， Overconfidence， Imitation and herding， Econophysics

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【期刊论文】Is there a realestate bubble in the US?
周炜星， WeiXing Zhou， Didier Sornette，
Physica A 361 (2006) 297308，0001，（）：
1年11月30日
Using a methodology developed in previous papers, we analyze the quarterly average sale prices of new houses sold in the USA as a whole, in the Northeast, Midwest, South, and West of the USA, in each of the 50 states and the District of Columbia of the USA, to determine whether they have grown at a fasterthanexponential rate which we take as the diagnostic of a bubble. We find that 22 states (mostly Northeast and West) exhibit clearcut signatures of a fastgrowing bubble. From the analysis of the S&P 500 Home Index, we conclude that the turning point of the bubble will probably occur around mid2006.
Econophysics， Real estate， Bubble， Prediction

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【期刊论文】Inverse statistics and multifractality of exit distances in 3D fully developed turbulence
周炜星， WeiXing Zhou， Didier Sornette， ， WeiKang Yuan
Physica D 214 (2006) 5562，0001，（）：
1年11月30日
The inverse structure functions of exit distances have been introduced as a novel diagnostic of turbulence which emphasizes the more laminar regions [1–4]. Using Taylor’s frozen field hypothesis, we investigate the statistical properties of the exit distances of empirical 3D fully developed turbulence. We find that the probability density functions of exit distances at different velocity thresholds ξ v can be approximated by stretched exponentials with exponents varying with the velocity thresholds below a critical threshold. We show that the inverse structure functions exhibit clear extended selfsimilarity (ESS). The ESS exponents ξ(p, 2) for small p (p < 3.5) are well described byζ(p, 2) = p/2, which derives from the observed approximate universality of the distributions of the exit distances for different velocity thresholds ξ v. The data is not sufficient to reject the hypothesis that monofractal ESS is sufficient to explain the data. In contrast, a measure taking into account the dependence between successive exit distances at a given velocity threshold exhibits clear multifractality with negative dimensions, suggesting the existence of a nontrivial dependence in the time series of exit times.
Turbulence， Inverse statistics， Exit distance， Extended selfsimilarity， Multifractal analysis

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【期刊论文】Detrended fluctuation analysis for fractals and multifractals in higher dimensions
周炜星， GaoFeng Gu， ， WeiXing Zhou
PHYSICAL REVIEW E 74, 061104 (2006)，0001，（）：
1年11月30日
Onedimensional detrended fluctuation analysis (DFA) and multifractal detrended fluctuation analysis (MFDFA) are widely used in the scaling analysis of fractal and multifractal time series because they are accurate and easy to implement. In this paper we generalize the onedimensional DFA and MFDFA to higher dimensional versions. The generalization works well when tested with synthetic surfaces including fractional Brownian surfaces and multifractal surfaces. The twodimensional MFDFA is also adopted to analyze two images from nature and experiment, and nice scaling laws are unraveled.

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周炜星， JianLiang Xu， WeiXing Zhou， HaiFeng Liu， Xin Gong， FuCheng Wang， ZunHong Yu
PHYSICAL REVIEW E 73, 056308 (2006)，0001，（）：
1年11月30日
The concept of inverse statistics in turbulence has attracted much attention in recent years. It is argued that the scaling exponents of the direct structure functions and the inverse structure functions satisfy an inversion formula. This proposition has already been verified by numerical data using the shell model. However, no direct evidence was reported for experimental threedimensional turbulence. We propose to test the inversion formula using experimental data of threedimensional fully developed turbulence by considering the energy dissipation rates instead of the usual efforts on the structure functions. The moments of the exit distances are shown to exhibit nice multifractality. The inversion formula between the direct and inverse exponents is then verified.

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周炜星， WeiXing Zhou， Bin Li， Tao Liu， GuiPing Cao， Ling Zhao， and WeiKang Yuan
PHYSICAL REVIEW E 73, 011801 (2006)，0001，（）：
1年11月30日
We have investigated the fractal characteristics and shape complexity of the fracture surfaces of swelled isotactic polypropylene Y1600 in supercritical carbon dioxide fluid through the consideration of the statistics of the regions embedded in the contours at different height of fracture landscapes (also called islands in the literature) of binary scanning electronic micrography images. The probability density functions of the areas A , perimeters L , and shape complexities C (defined by L/2πA ) of islands are shown to follow power laws p(A)˜A‑(μA+1) , p(L)˜L‑(μL+1) , and p(C)˜C‑(ν+1) , with the scaling ranges spanning over two orders. The perimeter and shape complexity scale respectively as Ltilde AD/2 and Ctilde Aq in two scaling regions delimited by A≈103 . The fractal dimension and shape complexity increase when the temperature decreases. In addition, the relationships among different powerlaw scaling exponents μA , μB , ν , D , and q have been derived analytically, assuming that A , L , and C follow powerlaw distributions.

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【期刊论文】Process Flow Diagram of an Ammonia Plant as a Complex Network
周炜星， ZhiQiang Jiang， WeiXing Zhou， Bing Xu， and WeiKang Yuan
AIChE Journal February 2007, Vol. 53, No. 2，0001，（）：
1年11月30日
Complex networks have attracted increasing interests in almost all disciplines of natural and social sciences. However, few efforts have been afforded in the field of chemical engineering. An example of complex technological network, investigating the process flow of an ammonia plant (AP) is presented. The AP network is a smallworld network with scalefree distribution of degrees. Adopting Newman’s maximum modularity algorithm for the detection of communities in complex networks, evident modular structures are identified in the AP network, which stem from the modular sections in chemical plants. In addition, it is found that the resultant AP tree exhibits excellent allometric scaling.
ammonia plant， complex network， smallworld effect， scale free,， modular Sections

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