The multifractal behaviors in financial markets results from temporal correlations as well as broad distribution. To evaluate the intrinsic multifractality caused by temporal correlations, surrogate approach is employed under the rank order remapping technique and sign randomization. In contrast to raw multifractality, it is found that intrinsic multifractality is more stable across many years. In this work, we utilize ANFIS model for estimating the intrinsic multifractality in financial returns. Furthermore, the intrinsic multifractality of serial major instruments are highly correlated, which can be served as an index of global market.
GrechD. and PamułaG., Multifrl background noise of monofractal signals, Acta Physica Polonica A121 (2012), B34–B39.
2.
GrechD. and PamułaG., On the multifrl effects generated by monofractal signals, Physica A: Statistical Mechanics and its Applications392(23) (2013), 5845–5864.
3.
PamułaG. and GrechD., Influence of the maximal fluctuation moment order q on multifractal records normalized by finite-size effects, Europhysics Letters105(5) (2014), 50004.
4.
Clara-RaholaJ., PuertasA.M., Sanchez-GraneroM.A., Trinidad-SegoviaJ.E. and de las NievesF.J., Diffusive and arrestedlike dynamics in currency exchange markets, Phys Rev Lett118 (2017), 068301.
5.
KwapienJ., OswieçimkaP. and DrozdżS., Components of multifractality in high-frequency stock returns, Physica A: Statistical Mechanics and its Applications350(2) (2005), 466–474.
6.
KantelhardtJ.W., ZschiegnerS.A., Koscielny-BundeE., HavlinS., BundeA. and StanleyH., Multifractal detrended fluctuation analysis of nonstationary time series, Physica A: Statistical Mechanics and its Applications316(1) (2002), 87–114.
7.
MatiaK., AshkenazyY. and StanleyH.E., Multifractal properties of price fluctuations of stocks and commodities, Europhysics Letters61(3) (2003), 422–428.
8.
IvanovP.C., AmaralL.A.N., GoldbergerA.L., HavlinS., RosenblumM.G., StruzikZ.R. and StanleyH.E., Multifractality in human heartbeat dynamics, Nature399(6735) (1999), 461–465.
9.
GencayR., SelcukF. and WhitcherB., Scaling properties of foreign exchange volatility, Physica A: Statistical Mechanics and its Applications289(1) (2001), 249–266.
10.
MoralesR., MatteoT.D. and AsteT., Non-stationary multifractality in stock returns, Physica A: Statistical Mechanics and its Applications392(24) (2013), 6470–6483.
11.
RakR. and GrechD., Quantitative approach to multifractality induced by correlations and broad distribution of data, Physica A: Statistical Mechanics and its Applications508 (2018), 48–66.
12.
DrozdżS., KwapieṅJ., ÓswieçimkaP. and RakR., The foreign exchange market: return distributions, multifractality,anomalous multifrlity and the Epps effect, New Journal of Physics12(10) (2010), 105003.
13.
GhashghaieS., BreymannW., PeinkeJ., TalknerP. and DodgeY., Turbulent cascades in foreign exchange markets, Nature381(6585) (1996), 767–770.
14.
ZhouW.-X., Finite-size effect and the components of multifractality in financial volatility, Chaos, Solitons Fractals45(2) (2012), 147–155.
15.
ZhouW.-X., The components of empirical multifractality in financial returns, Europhysics Letters88(2) (2009), 28004.
16.
AshkenazyY., IvanovP.C., HavlinS., PengC.-K., GoldbergerA.L. and StanleyH.E., Magnitude and sign correlations in heartbeat fluctuations, Phys Rev Lett86 (2001), 1900–1903.
17.
XuZ. and GencayR., Scaling, self-similarity and multifractality in fx markets, Physica A: Statistical Mechanics and its Applications323 (2003), 578–590.
