scholarly journals Jump Intervals of Stock Price Have Power-Law Distribution: An Empirical Study

2016 ◽  
Vol 06 (05) ◽  
pp. 770-777 ◽  
Author(s):  
Hongduo Cao ◽  
Ying Li ◽  
Huaping He ◽  
Zhi He
Keyword(s):  
Empirical Study ◽  
Power Law ◽  
Stock Price ◽  
Power Law Distribution

EMPIRICAL LAWS OF A STOCK PRICE INDEX AND A STOCHASTIC MODEL

2003 ◽  
Vol 06 (03) ◽  
pp. 303-312 ◽  
Author(s):  
TAISEI KAIZOJI ◽  
MICHIYO KAIZOJI
Keyword(s):  
Stochastic Model ◽  
Power Law ◽  
Stock Prices ◽  
Stock Price ◽  
Price Index ◽  
Probability Function ◽  
The Other ◽  
Power Law Distribution ◽  
Exponential Distributions ◽  
Daily Data

Recent works by econo-physicists [5,8,15,19] have shown that the probability function of the share returns and the volatility satisfies a power law with an exponent close to 4. On the other hand, we investigated quantitatively the return and the volatility of the daily data of the Nikkei 225 index from 1990 to 2003, and we found that the distributions of the returns and the volatility can be accurately described by the exponential distributions [11]. We then propose a stochastic model of stock markets that can reproduce these empirical laws. In our model the fluctuations of stock prices are caused by interactions among traders. We indicate that the model can reproduce the empirical facts mentioned above. In particular, we show that the interaction strengths among traders are a key variable that can distinguish the emergence of the exponential distribution or the power-law distribution.

An Empirical Study on the Characteristics of Complex Network of Firms' Innovation Network-Taking Taiyuan Stainless Steel Firms as an Example

2014 ◽  
Vol 644-650 ◽  
pp. 6261-6264
Author(s):  
Bin Qiao ◽  
Lin Ji ◽  
Xiao Xiao Wang
Keyword(s):  
Stainless Steel ◽  
Empirical Study ◽  
Power Law ◽  
Path Length ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Innovation Network ◽  
Power Law Distribution ◽  
Simulation Results ◽  
Two Stages

Research shows the degree distribution of firms' innovation network in accordance with power-law distribution as continuous evolution of firms' innovation network, which has larger clustering coefficient and smaller average path length. Therefore, the network structure and simulation results of two stages are compared with the data of Taiyuan stainless steel firms' innovation network. The size of Taiyuan stainless steel firms' innovation network is constantly expanding, so is the clustering coefficient, while the average path length is constantly shrinking.

An Econophysics Approach to Introduction Uncertainty in Dynamics of Complex Market Structural Models

2018 ◽  
pp. 1-22 ◽  
Author(s):  
Cem Cagri Donmez
Keyword(s):  
Power Law ◽  
Stock Price ◽  
Structural Models ◽  
Statistical Correlation ◽  
Extreme Value ◽  
Extreme Value Statistics ◽  
Power Law Distribution ◽  
Critical Limit ◽  
Theoretical Approaches ◽  
Price Movements

Econophysicists have begun to make progress in answering significant questions. In particular, these collaborations have the potential to change the paradigm for understanding fluctuations. New theoretical approaches to predict complex markets may be proposed, by the captivating formulation of the stock market concerning statistical correlation to be given, where some simple (non-differential, non-fractal) expressions are also suggested as general stock price formulae in a closed form that can generate a variety of possible price movements in time. A given attribute of mechanics may be submitted as a likely option to cover the price movements regarding traditional concepts where utilising stock mechanics to grow the portfolios in real markets may be realised. The ideas prove useful in risk evaluation, extreme value statistics, critical limit theorems for sums of independent variables with power law distribution, random walks, fractals, and multfractal formalisms, etc.

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

scholarly journals Power-law behavior of transcription factor dynamics at the single-molecule level implies a continuum affinity model

2021 ◽  
Author(s):  
David A Garcia ◽  
Gregory Fettweis ◽  
Diego M Presman ◽  
Ville Paakinaho ◽  
Christopher Jarzynski ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Single Molecule ◽  
Power Law ◽  
Dwell Time ◽  
Specific Binding ◽  
Power Law Distribution ◽  
Single Molecule Level ◽  
Binding Behavior ◽  
Chromatin Template ◽  
Nuclear Domains

Abstract Single-molecule tracking (SMT) allows the study of transcription factor (TF) dynamics in the nucleus, giving important information regarding the diffusion and binding behavior of these proteins in the nuclear environment. Dwell time distributions obtained by SMT for most TFs appear to follow bi-exponential behavior. This has been ascribed to two discrete populations of TFs—one non-specifically bound to chromatin and another specifically bound to target sites, as implied by decades of biochemical studies. However, emerging studies suggest alternate models for dwell-time distributions, indicating the existence of more than two populations of TFs (multi-exponential distribution), or even the absence of discrete states altogether (power-law distribution). Here, we present an analytical pipeline to evaluate which model best explains SMT data. We find that a broad spectrum of TFs (including glucocorticoid receptor, oestrogen receptor, FOXA1, CTCF) follow a power-law distribution of dwell-times, blurring the temporal line between non-specific and specific binding, suggesting that productive binding may involve longer binding events than previously believed. From these observations, we propose a continuum of affinities model to explain TF dynamics, that is consistent with complex interactions of TFs with multiple nuclear domains as well as binding and searching on the chromatin template.

EVOLUTION OF SHANGHAI STOCK MARKET BASED ON MAXIMAL SPANNING TREES

2012 ◽  
Vol 27 (03) ◽  
pp. 1350022 ◽  
Author(s):  
CHUNXIA YANG ◽  
YING SHEN ◽  
BINGYING XIA
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Spanning Tree ◽  
Stock Price ◽  
Spanning Trees ◽  
Turning Points ◽  
Single Step ◽  
P Value ◽  
Power Law Distribution ◽  
Structure Variation

In this paper, using a moving window to scan through every stock price time series over a period from 2 January 2001 to 11 March 2011 and mutual information to measure the statistical interdependence between stock prices, we construct a corresponding weighted network for 501 Shanghai stocks in every given window. Next, we extract its maximal spanning tree and understand the structure variation of Shanghai stock market by analyzing the average path length, the influence of the center node and the p-value for every maximal spanning tree. A further analysis of the structure properties of maximal spanning trees over different periods of Shanghai stock market is carried out. All the obtained results indicate that the periods around 8 August 2005, 17 October 2007 and 25 December 2008 are turning points of Shanghai stock market, at turning points, the topology structure of the maximal spanning tree changes obviously: the degree of separation between nodes increases; the structure becomes looser; the influence of the center node gets smaller, and the degree distribution of the maximal spanning tree is no longer a power-law distribution. Lastly, we give an analysis of the variations of the single-step and multi-step survival ratios for all maximal spanning trees and find that two stocks are closely bonded and hard to be broken in a short term, on the contrary, no pair of stocks remains closely bonded for a long time.

scholarly journals Explaining the power-law distribution of human mobility through transportationmodality decomposition

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Kai Zhao ◽  
Mirco Musolesi ◽  
Pan Hui ◽  
Weixiong Rao ◽  
Sasu Tarkoma
Keyword(s):  
Power Law ◽  
Human Mobility ◽  
Power Law Distribution

MASS FUNCTION OF HALOS: A NEW ANALYTICAL APPROACH

2004 ◽  
Vol 13 (07) ◽  
pp. 1345-1349 ◽  
Author(s):  
JOSÉ A. S. LIMA ◽  
LUCIO MARASSI
Keyword(s):  
Power Law ◽  
Free Parameter ◽  
Analytical Approach ◽  
Mass Function ◽  
New Method ◽  
Power Law Distribution ◽  
The Press ◽  
The Universe ◽  
Special Case

A generalization of the Press–Schechter (PS) formalism yielding the mass function of bound structures in the Universe is given. The extended formula is based on a power law distribution which encompasses the Gaussian PS formula as a special case. The new method keeps the original analytical simplicity of the PS approach and also solves naturally its main difficult (the missing factor 2) for a given value of the free parameter.

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