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A fractal is in essence a hierarchy with cascade structure, which can be described with a set of exponential functions. From these exponential functions, a set of power laws indicative of scaling can be derived. Hierarchy structure and…

Physics and Society · Physics 2017-07-13 Yanguang Chen

Detrended fluctuation analysis (DFA) [1] of the volatility series has been found to be useful in dentifying possible nonlinear/multifractal dynamics in the empirical sample [2-4]. Long-range volatile correlation can be an outcome of static…

Data Analysis, Statistics and Probability · Physics 2009-11-11 Radhakrishnan Nagarajan

Multifractal analysis is one of the important approaches that enables us to measure the complexity of various data via the scaling properties. We compare the most common techniques used for multifractal exponents estimation from both…

Statistical Finance · Quantitative Finance 2016-10-25 Petr Jizba , Jan Korbel

The financial market and turbulence have been broadly compared on account of the same quantitative methods and several common stylized facts they shared. In this paper, the She-Leveque (SL) hierarchy, proposed to explain the anomalous…

Statistical Finance · Quantitative Finance 2015-06-11 Ya-Chun Gao , Shi-Min Cai , Bing-Hong Wang

We describe a new method that is both physically explicable and quantitatively accurate in describing the multifractal characteristics of intermittent events based on groupings of rank-ordered fluctuations. The generic nature of such…

Astrophysics · Physics 2009-06-23 Tom Chang , Cheng-chin Wu

The bitcoin price has surged in recent years and it has also exhibited phases of rapid decay. In this paper we address the question to what extent this novel cryptocurrency market can be viewed as a classic or semi-efficient market. Novel…

Statistical Finance · Quantitative Finance 2019-06-26 Josselin Garnier , Knut Solna

We introduce the self-excited multifractal (SEMF) model, defined such that the amplitudes of the increments of the process are expressed as exponentials of a long memory of past increments. The principal novel feature of the model lies in…

Statistical Mechanics · Physics 2011-05-12 Vladimir Filimonov , Didier Sornette

We focus on the importance of $q$ moments range used within multifractal detrended fluctuation analysis (MFDFA) to calculate the generalized Hurst exponent spread and multifractal properties of signals. Different orders of detrending…

Data Analysis, Statistics and Probability · Physics 2013-07-26 Grzegorz Pamuła , Dariusz Grech

Nonlinear dynamic volatility has been observed in many financial time series. The recently proposed quantile periodogram offers an alternative way to examine this phenomena in the frequency domain. The quantile periodogram is constructed…

Statistical Finance · Quantitative Finance 2026-03-26 Ta-Hsin Li

We describe new families of random fractals, referred to as "V-variable", which are intermediate between the notions of deterministic and of standard random fractals. The parameter V describes the degree of "variability" : at each…

Probability · Mathematics 2007-05-23 Michael Barnsley , John E. Hutchinson , Örjan Stenflo

We use Fourier analysis to access risk in financial products. With it we analyze price changes of e.g. stocks. Via Fourier analysis we scrutinize quantitatively whether the frequency of change is higher than a change in (conserved) company…

Statistical Finance · Quantitative Finance 2024-08-21 Michael Grabinski , Galiya Klinkova

The multifractal behavior for tick data of prices is investigated in Korean financial market. Using the rescaled range analysis(R/S analysis), we show the multifractal nature of returns for the won-dollar exchange rate and the KOSPI. We…

Statistical Mechanics · Physics 2008-12-02 Kyungsik Kim , Seong-Min Yoon

In this paper we extend the known methodology for fitting stable distributions to the multivariate case and apply the suggested method to the modelling of daily cryptocurrency-return data. The investigated time period is cut into 10…

Applications · Statistics 2018-10-24 Szabolcs Majoros , András Zempléni

Complex networks have been studied in recent years due to their relevance in biological, social and technical real systems, such as the world wide web, social networks and biochemical interactions. One of the most current features of…

Physics and Society · Physics 2024-02-13 Pablo Pavón-Domínguez , Soledad Moreno-Pulido

Fractals are self-similar recursive structures that have been used in modeling several real world processes. In this work we study how "fractal-like" processes arise in a prediction game where an adversary is generating a sequence of bits…

Machine Learning · Computer Science 2013-04-30 Rina Panigrahy , Preyas Popat

The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual Minority Game (MG)…

Trading and Market Microstructure · Quantitative Finance 2008-12-10 Antonio F. Crepaldi , Camilo Rodrigues Neto , Fernando F. Ferreira , Gerson Francisco

The multifractal detrended fluctuation analysis technique is employed to analyze the time series of gold consumer price index (CPI) and the market trend of three world's highest gold consuming countries, namely China, India and Turkey for…

Statistical Finance · Quantitative Finance 2015-07-01 Provash Mali , Amitabha Mukhopadhyay

Multivariate functional principal component analysis (MFPCA) is a powerful dimension reduction technique for analyzing multiple functional variables simultaneously. However, existing MFPCA methods assume that all functional observations are…

In this paper we will try to assess the multifractality displayed by the high-frequency returns of Madrid's Stock Exchange IBEX35 index. A Multifractal Detrended Fluctuation Analysis shows that this index has a wide singularity spectrum…

Statistical Finance · Quantitative Finance 2015-06-16 Pablo Suárez-García , David Gómez-Ullate

Accurately assessing financial risk requires capturing both individual asset volatility and the complex, asymmetric dependence structures that emerge during extreme market events. While modern diffusion-based models have advanced…

Machine Learning · Statistics 2026-05-20 David Huk , Dongshan Wang , Miha Bresar