期刊文献+

大宗商品期货市场收益率的多重分形分析 被引量:3

Multifractal Analysis on the Series of Returns of Commodity Futures Market
下载PDF
导出
摘要 运用改进的多重分形消除趋势波动分析法,对大宗商品期货市场中大豆及铝两种期货合约的对数收益率序列进行多重分形分析,并结合多重分形谱方法,对它们的多重分形强度进行比较。实证研究表明,这两种合约的对数收益率序列均具有明显的多重分形特征,且大豆期货序列的多重分形强度更大。证实了大宗商品市场的多重分形性是由序列的波动相关性及厚尾概率分布两个因素共同引起的。对于大豆和铝的对数收益率序列,序列的波动相关性是形成多重分形性的主要原因。此外,研究还发现,虽然买入大豆期货合约的风险较铝的风险更大,但获利的机会也更大。 Using the improved method of the multifractal detrended fluctuation analysis, we investigate the muhifractal na- tures of the series of logarithmic returns for two futures contracts, soybean and aluminum futures contracts, in the commodities futures market. Combined with the muhifractal spectrum method, we make a comparison between their strengths of muhifractal- ity. The empirical results show that they all have muhifractal natures, and the strength of multifractality for the series of soy- bean is greater than that of aluminum. Further study points out that the multifractal natures of the commodity market are deter- mined by two factors, and the fluctuation correlation is the main factor that forms a muhifractal nature. Besides, the study also finds that the risk of buying soybean futures contract is greater than that of aluminum, but at the same time its profit opportunity is bigger.
出处 《南京财经大学学报》 2013年第1期43-50,共8页 Journal of Nanjing University of Finance and Economics
基金 教育部人文社会科学研究规划基金项目:金融系统复杂性的表征 成因及演化研究(12YJAZH020) 南京财经大学预研究项目(A2011019)
关键词 期货市场 MF-DFA 多重分形谱 多重分形分析 futures market MF-DFA multifractal spectrum multifractal analysis
  • 相关文献

参考文献11

二级参考文献52

  • 1施锡铨,艾克凤.股票市场风险的多重分形分析[J].统计研究,2004,21(9):33-36. 被引量:30
  • 2黄诒蓉.中国股票市场多重分形结构的实证研究[J].当代财经,2004(11):53-56. 被引量:7
  • 3Alvarez-Ramirez J,Cisneros M,Ibarra-Valdez C. Multifractal Hurst analysis of crude oil prices. Physica A, 2002, 313: 651~670. 被引量:1
  • 4Schmitt F,Schertzer D,Lovejoy S. Multifractal fluctuations in finance. Int.J.Theor.Appl.Fin., 2000, 3(3):361~364. 被引量:1
  • 5Kantelhardt J W, Zschiegner S A, Koscielny-Bunde E, et al. Multifractal detrended fluctuation analysis of nonstationary time series. Physica A, 2002,316: 87~114. 被引量:1
  • 6Ausloos M,Vandewalle N, Boveroux P H, et al.Applications of statistical physics to economic and financial topics. Physica A, 1999, 274: 229--240. 被引量:1
  • 7Andreadis I,Serletis A. Evidence of a random multifractal turbulent structure in the Dow Jones industrial average. Chaos, Solitons and Fractals, 2002,13(6): 1309~1315. 被引量:1
  • 8Bandiera L, Cester A, Paccagnella A, et al.Detrended fluctuation analysis of the soft breakdown current.Microelectronic Engineering, 2001, 59(1): 49~ 53. 被引量:1
  • 9Govindan R B, Vjushin D,Brenner S, et al.Long-range correlations and trends in global climate models:Comparison with real data. Physica A, 2001, 294: 239~248. 被引量:1
  • 10Peng C K, Havlin S, Stanley H E, et al. Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos, 1995, 5(1): 82~87. 被引量:1

共引文献132

同被引文献22

引证文献3

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部