Are developed and emerging agricultural futures markets multifractal? A comparative perspective

被引:35
作者
He, Ling-Yun [1 ]
Chen, Shu-Peng [1 ]
机构
[1] China Agr Univ, Ctr Futures & Financial Derivat, Coll Econ & Management, Campus Mailbox 108,East Campus,Qinghuadonglu St, Beijing 100083, Peoples R China
基金
中国博士后科学基金;
关键词
Agricultural futures markets; MF-DFA; Multifractal properties; Nonlinear temporal correlation; Non-Gaussian probability distribution; The strength of multifractality; DETRENDED FLUCTUATION ANALYSIS; PRICE FLUCTUATIONS; FRACTAL STRUCTURE; MOVING AVERAGE; HURST EXPONENT; STOCK-MARKET; TIME;
D O I
10.1016/j.physa.2010.05.021
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Although there are many reports on the empirical evidence of the existence of multifractality in various financial or commodity markets in current literature, few can be found to compare the multifractal properties of emerging and developed economies, especially for agricultural futures markets in those countries (regions). We therefore chose China as the representative of the transition and emerging economies, and USA as the representative of developed ones. We attempt to find the answers to the following questions: (1) Are all those different markets multifractal? (2) What are the dynamical causes for multifractality in those markets (if any)? (3) Are the multifractality strengths in those markets of the transition and emerging economies weaker (or stronger) than those of the developed ones? To answer these questions, Multifractal Detrended Fluctuation Analysis (MF-DFA) are applied to study some of the representative agricultural futures markets in China and USA, namely, wheat, soy meal, soybean and corn. Our results suggest that all the markets of China and USA exhibit multifractal properties except US soybean market, which is much closer to mono-fractal comparing with China's soybean market. To investigate the sources of multifractality, shuffling and phase randomization procedures are applied to destroy the temporal correlations and nonGaussian distributions respectively. We found that multifractality can be mainly attributed to the non-Gaussian probability distribution and secondarily to the nonlinear temporal correlation mechanism for all the markets, except US soybean and soy meal, which derives from some other unknown factors. Furthermore, the average of tau (q) are applied to obtain the multifractal spectra of the two markets as a whole. The results show that the width of the multifractal spectrum of US agricultural futures markets is significantly narrower than that of China's. Based on our findings, we proposed a hypothesis that the strength of multifractality in developed economies may be weaker than that in emerging and transition ones. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:3828 / 3836
页数:9
相关论文
共 41 条
[1]   Chaos in oil prices? Evidence from futures markets [J].
Adrangi, B ;
Chatrath, A ;
Dhanda, KK ;
Raffiee, K .
ENERGY ECONOMICS, 2001, 23 (04) :405-425
[2]   Second-order moving average and scaling of stochastic time series [J].
Alessio, E ;
Carbone, A ;
Castelli, G ;
Frappietro, V .
EUROPEAN PHYSICAL JOURNAL B, 2002, 27 (02) :197-200
[3]   Multifractal Hurst analysis of crude oil prices [J].
Alvarez-Ramirez, J ;
Cisneros, M ;
Ibarra-Valdez, C ;
Soriano, A .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2002, 313 (3-4) :651-670
[4]   Short-term predictability of crude oil markets: A detrended fluctuation analysis approach [J].
Alvarez-Ramirez, Jose ;
Alvarez, Jesus ;
Rodriguez, Eduardo .
ENERGY ECONOMICS, 2008, 30 (05) :2645-2656
[5]  
[Anonymous], 1964, RANDOM CHARACTER STO
[6]   Detrending moving average algorithm: A closed-form approximation of the scaling law [J].
Arianos, Sergio ;
Carbone, Anna .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2007, 382 (01) :9-15
[7]   MULTIFRACTAL SPECTRA OF MULTI-AFFINE FUNCTIONS [J].
BARABASI, AL ;
SZEPFALUSY, P ;
VICSEK, T .
PHYSICA A, 1991, 178 (01) :17-28
[8]   Time-dependent Hurst exponent in financial time series [J].
Carbone, A ;
Castelli, G ;
Stanley, HE .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2004, 344 (1-2) :267-271
[9]   Analysis of clusters formed by the moving average of a long-range correlated time series [J].
Carbone, A ;
Castelli, G ;
Stanley, HE .
PHYSICAL REVIEW E, 2004, 69 (02) :026105-1
[10]   Directed self-organized critical patterns emerging from fractional Brownian paths [J].
Carbone, A ;
Stanley, HE .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2004, 340 (04) :544-551