Mixed-correlated ARFIMA processes for power-law cross-correlations

We introduce a general framework of the Mixed-correlated ARFIMA (MC-ARFIMA) processes which allows for various specifications of univariate and bivariate long-term memory. Apart from a standard case when Hxy=12(Hx+Hy), MC-ARFIMA also allows for processes with Hxy<12(Hx+Hy) but also for long-range correlated processes which are either short-range cross-correlated or simply correlated. The major contribution of MC-ARFIMA lies in the fact that the processes have well-defined asymptotic properties for Hx, Hy and Hxy, which are derived in the paper, so that the processes can be used in simulation studies comparing various estimators of the bivariate Hurst exponent Hxy. Moreover, the framework allows for modeling of processes which are found to have Hxy<12(Hx+Hy).

[1]  Wen-Jen Tsay,et al.  Maximum likelihood estimation of stationary multivariate ARFIMA processes , 2010 .

[2]  Albert-László Barabási,et al.  Multifractal spectra of multi-affine functions , 1991 .

[3]  Jose Alvarez-Ramirez,et al.  Time-dependent correlations in electricity markets , 2010 .

[4]  Ling-Yun He,et al.  Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets , 2011 .

[5]  H. Stanley,et al.  Quantifying cross-correlations using local and global detrending approaches , 2009 .

[6]  Pierre-Olivier Amblard,et al.  Identification of the Multivariate Fractional Brownian Motion , 2011, IEEE Transactions on Signal Processing.

[7]  Vicsek,et al.  Multifractality of self-affine fractals. , 1991, Physical review. A, Atomic, molecular, and optical physics.

[8]  Frank Nielsen Local Whittle estimation of multi‐variate fractionally integrated processes , 2011 .

[9]  Jing Wang,et al.  MULTIFRACTAL CROSS-CORRELATION ANALYSIS BASED ON STATISTICAL MOMENTS , 2012 .

[10]  B. M. Tabak,et al.  Long-range dependence and multifractality in the term structure of LIBOR interest rates , 2007 .

[11]  L. Kristoufek On spurious anti-persistence in the US stock indices , 2010 .

[12]  Clifford M. Hurvich,et al.  The averaged periodogram estimator for a power law in coherency , 2011 .

[13]  Christian Kascha Three Essays in Time Series Econometrics , 2007 .

[14]  Dong-Hua Wang,et al.  Price–volume cross-correlation analysis of CSI300 index futures , 2013 .

[15]  Jose Alvarez-Ramirez,et al.  Multifractal Hurst analysis of crude oil prices , 2002 .

[16]  Zhi-Qiang Jiang,et al.  Multifractal detrending moving-average cross-correlation analysis. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  P. Norouzzadeh A multifractal detrended fluctuation description of Iranian rial–US dollar exchange rate , 2005 .

[18]  Katsumi Shimotsu,et al.  Gaussian semiparametric estimation of multivariate fractionally integrated processes , 2007 .

[19]  Gennady Samorodnitsky,et al.  Long Range Dependence , 2007, Found. Trends Stoch. Syst..

[20]  Chi Xie,et al.  Cross-correlations between Renminbi and four major currencies in the Renminbi currency basket , 2013 .

[21]  Borko Stosic,et al.  Correlations and cross-correlations in the Brazilian agrarian commodities and stocks , 2010 .

[22]  Ling-Yun He,et al.  A new approach to quantify power-law cross-correlation and its application to commodity markets , 2011 .

[23]  C. Peng,et al.  Mosaic organization of DNA nucleotides. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[24]  M. Nielsen Spectral Analysis of Fractionally Cointegrated Systems , 2002 .

[25]  T. D. Matteo,et al.  Multi-scaling in finance , 2007 .

[26]  Ladislav Kristoufek,et al.  Multifractal height cross-correlation analysis: A new method for analyzing long-range cross-correlations , 2011, 1201.3473.

[27]  H. Stanley,et al.  Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series. , 2007, Physical review letters.

[28]  Ling-Yun He,et al.  Nonlinear bivariate dependency of price–volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis , 2011 .

[29]  Long-range dependence in returns and volatility of Central European Stock Indices , 2010 .

[30]  H. Stanley,et al.  Cross-correlations between volume change and price change , 2009, Proceedings of the National Academy of Sciences.

[31]  Clifford M. Hurvich,et al.  Computationally Efficient Methods for Two Multivariate Fractionally Integrated Models , 2009 .

[32]  CONSISTENCY OF THE AVERAGED CROSS‐PERIODOGRAM IN LONG MEMORY SERIES , 1997 .

[33]  Wei‐Xing Zhou Multifractal detrended cross-correlation analysis for two nonstationary signals. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[34]  Ladislav Kristoufek,et al.  On Hurst exponent estimation under heavy-tailed distributions , 2010, 1201.4786.

[35]  Marcel Ausloos,et al.  CROSSING OF TWO MOBILE AVERAGES: A METHOD FOR MEASURING THE ROUGHNESS EXPONENT , 1998 .

[36]  Gabriel J. Power,et al.  Long-range dependence in the volatility of commodity futures prices: Wavelet-based evidence , 2010 .

[37]  T. D. Matteo,et al.  Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development , 2004, cond-mat/0403681.

[38]  H. Stanley,et al.  Time-dependent Hurst exponent in financial time series , 2004 .

[39]  A. Carbone,et al.  Second-order moving average and scaling of stochastic time series , 2002 .

[40]  Boris Podobnik,et al.  Modeling long-range cross-correlations in two-component ARFIMA and FIARCH processes , 2007, 0709.0838.

[41]  Wei-Xing Zhou,et al.  Detrending moving average algorithm for multifractals. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[42]  Feng Ma,et al.  Multifractal detrended cross-correlation analysis between the Chinese stock market and surrounding stock markets , 2013 .

[43]  Tomaso Aste,et al.  Scaling behaviors in differently developed markets , 2003 .