Wavelet analysis reveals limitations in detecting multifractality in signals with isolated singularities.
problem Detecting multifractality in signals with isolated singularities using detrended fluctuation analysis and wavelet leaders.
method Comparison of detrended fluctuation analysis and wavelet leaders on signals with isolated singularities.
result Signals with isolated singularities can artefactually give rise to broad multifractal spectra, leading to incorrect inference of multifractality.
The miltifractal properties and scaling behaviour of the exchange rate variations of the Iranian rial against the US dollar from a daily perspective is numerically investigated. For this purpose the multifractal detrended fluctuation analysis (MF-DFA) is used. Through multifractal analysis, the scaling exponents, gener…
Multifractal time series analysis is a approach that shows the possible complexity of the system. Nowadays, one of the most popular and the best methods for determining multifractal characteristics is Multifractal Detrended Fluctuation Analysis (MFDFA). However, it has some drawback. One of its core elements is detrend…
Study examines multifractality in European power loads over 5 years.
problem Understanding multifractality in European power load time series.
method Applied Multifractal Detrended Fluctuation Analysis (MF-DFA) with improved methodology.
result European power loads exhibit multifractality in both distribution and autocorrelation functions.
The intraday pattern, long memory, and multifractal nature of the intertrade durations, which are defined as the waiting times between two consecutive transactions, are investigated based upon the limit order book data and order flows of 23 liquid Chinese stocks listed on the Shenzhen Stock Exchange in 2003. An inverse…
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 the period: 1993-July 2013. Various multifractal variables, such as the generaliz…
The performance of the multifractal detrended analysis on short time series is evaluated for synthetic samples of several mono- and multifractal models. The reconstruction of the generalized Hurst exponents is used to determine the range of applicability of the method and the precision of its results as a function of t…
Intertrade duration of equities is an important financial measure characterizing the trading activities, which is defined as the waiting time between successive trades of an equity. Using the ultrahigh-frequency data of a liquid Chinese stock and its associated warrant, we perform a comparative investigation of the sta…
The detrending moving average (DMA) algorithm is a widely used technique to quantify the long-term correlations of non-stationary time series and the long-range correlations of fractal surfaces, which contains a parameter θ determining the position of the detrending window. We develop multifractal detrending moving a…
Bid-ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation functi…
Detrended fluctuation analysis (DFA) is a simple but very efficient method for investigating the power-law long-term correlations of non-stationary time series, in which a detrending step is necessary to obtain the local fluctuations at different timescales. We propose to determine the local trends through empirical mo…
New analysis reveals multi-branched multifractality in time series.
problem Analyzing non-monotonic behavior in mean inter-event times.
method Modified Multifractal Detrended Fluctuation Analysis with Legendre-Fenchel transform.
result Discovery of multi-branched multifractality leading to phase transitions.
Study uses detrended cross-correlation to analyze cryptocurrency market, revealing robust collective modes and distinguishing interdependencies.
problem Nonstationarity, long-range memory, and heavy-tailed fluctuations obscure traditional correlations in complex systems.
method Constructs detrended correlation matrices using multifractal detrended cross-correlation coefficient ρr to emphasize different fluctuations. result Detrending and fluctuation analysis reveal distinct spectral properties from random case, identifying market and sectoral components.
We propose a novel algorithm - Multifractal Cross-Correlation Analysis (MFCCA) - that constitutes a consistent extension of the Detrended Cross-Correlation Analysis (DCCA) and is able to properly identify and quantify subtle characteristics of multifractal cross-correlations between two time series. Our motivation for …
Model allocates portfolios based on multifractal cross-correlations across different scales.
problem Heterogeneous scales and amplitude-dependent financial correlations.
method Constructs a portfolio allocation model using multifractal cross-correlation analysis (MFCCA) with signed fluctuation functions.
result Reduces tail risk and improves risk-adjusted performance compared to mean-variance model.
Study on wind speed variability in Switzerland using multifractal analysis.
problem Understanding wind speed variability in mountainous regions.
method Multifractal detrended fluctuation analysis applied to daily wind speed data.
result Persistent and multifractal nature of wind speed series, with larger fluctuations in Swiss plateau.
We investigate the temporal correlations and multifractal nature of trading volume of 22 liquid stocks traded on the Shenzhen Stock Exchange in 2003. We find that the trading volume exhibit size-dependent non-universal long memory and multifractal nature. No crossover in the power-law dependence of the detrended fluctu…
Study finds intrinsic multifractality in maize and barley spot markets, but not in wheat and rice.
problem Understanding the complex price behavior of global grain spot markets.
method Utilized multifractal fluctuation analysis (MF-DFA) to investigate intrinsic multifractality.
result Intrinsic multifractality found in maize and barley sub-indices, but not in wheat and rice.
Study uses multifractal detrended cross-correlation to detect Forex arbitrage opportunities.
problem Detecting arbitrage opportunities in Forex markets.
method Multifractal detrended cross-correlation analysis applied to Forex time series.
result Strong cross-correlations found between exchange rates involved in triangular relations, including AUD and NZD.
Long-range correlation and fluctuation in the gold market time series of world's two leading gold consuming countries, namely China and India, are studied. For both the market series during the period 1985-2013 we observe a long-range persistence of memory in the sequences of maxima (minima) of returns in successive ti…
An average instantaneous cross-correlation function is introduced to quantify the interaction of the financial market of a specific time. Based on the daily data of the American and Chinese stock markets, memory effect of the average instantaneous cross-correlations is investigated over different price return time inte…
Study on cryptocurrency trading patterns using multifractal analysis.
problem Lack of systematic study on temporal structure of cryptocurrency trading.
method Multifractal detrended cross-correlation analysis of price returns, trades, and volume.
result All analyzed quantities exhibit multifractal structure, both univariate and bivariate.
Order cancellation process plays a crucial role in the dynamics of price formation in order-driven stock markets and is important in the construction and validation of computational finance models. Based on the order flow data of 18 liquid stocks traded on the Shenzhen Stock Exchange in 2003, we investigate the empiric…
Multifractality in time series arises from temporal correlations, not just fat tails.
problem Understanding the origin of multifractality in time series data.
method Mathematical arguments and numerical simulations using MFDFA approach.
result Genuine multifractality requires temporal correlations, not just fat tails.
Based on the Multifractal Detrended Fluctuation Analysis (MFDFA) and on the Wavelet Transform Modulus Maxima (WTMM) methods we investigate the origin of multifractality in the time series. Series fluctuating according to a qGaussian distribution, both uncorrelated and correlated in time, are used. For the uncorrelated …
By applying the multifractal detrended fluctuation analysis to the high-frequency tick-by-tick data from Deutsche Börse both in the price and in the time domains, we investigate multifractal properties of the time series of logarithmic price increments and inter-trade intervals of time. We show that both quantities rev…
We investigate the presence of residual multifractal background for monofractal signals which appears due to the finite length of the signals and (or) due to the long memory the signals reveal. This phenomenon is investigated numerically within the multifractal detrended fluctuation analysis (MF-DFA) for artificially g…
Improved MF-DFA model analyzes precious metals market efficiency and multifractality.
problem Analyze price fluctuations in precious metals market.
method Proposed Bi-OSW-MF-DFA method compared to MF-DFA.
result Bi-OSW-MF-DFA method shows better efficiency in precious metals market analysis.
A new method uses q-dependent MSTs to analyze stock market correlations.
problem Analyzing correlations between different fluctuation amplitudes and time scales.
method Introduces q-dependent minimum spanning trees (qMST) based on q-dependent detrended cross-correlation coefficients (ρq). result The qMST graphs provide more information about correlation structure than conventional MSTs. Study compares Bitcoin, gold, and gas price complexity using multifractal and multiscale entropy methods.
problem Quantifying complexity of financial time series for market analysis.
method Employed MF-DFA and RCMSE to analyze Bitcoin, GBP/USD, gold, and natural gas price log-return time series.
result Bitcoin shows higher complexity compared to other markets, linked to higher nonlinear correlations.
Study finds long-term linear correlations in Chinese stock order aggressiveness.
problem Investigating long-term correlations in order aggressiveness of Chinese stocks.
method Used detrending moving average and multifractal detrending moving average analyses on order flow data.
result Strong long-term linear correlations found in order aggressiveness, with some exceptions.
New analysis of stock market correlations reveals unique properties and optimal portfolio construction.
problem Understanding the unique properties of stock market correlations at different magnitudes.
method Used q-dependent cross-correlation analysis, random matrix theory, and complex network representation.
result Optimal multifractal order for portfolio optimization is approximately q=2.
Study finds Bitcoin volatility exhibits roughness, not constant over time.
problem Investigating roughness in Bitcoin volatility.
method Multifractal detrended fluctuation analysis and shuffled time series analysis.
result Bitcoin volatility exhibits roughness (generalized Hurst exponent < 1/2).
Recently the statistical characterizations of financial markets based on physics concepts and methods attract considerable attentions. We used two possible procedures of analyzing multifractal properties of a time series. The first one uses the continuous wavelet transform and extracts scaling exponents from the wavele…
We study the nature of fluctuations in variety of price indices involving companies listed on the New York Stock Exchange. The fluctuations at multiple scales are extracted through the use of wavelets belonging to Daubechies basis. The fact that these basis sets satisfy vanishing moments conditions makes them ideal to …
The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, non-stationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and c…
A new method for direct determination of multifractal spectrum from moving average analysis.
problem Direct determination of multifractal spectrum from moving average analysis.
method Proposes a new approach based on detrending moving average method (MF-DMA) to directly determine multifractal spectrum.
result Direct determination of multifractal spectrum is possible with less computation cost compared to traditional approach.
Study reveals multifractal nature in Chinese stock markets and predicts future returns.
problem Predicting future stock market returns using multifractal characteristics.
method Multifractal detrended fluctuation analysis (MF-DFA) on high-frequency stock data.
result Spectral width Δα is a significant predictor of future stock returns.
Digital currencies exhibit multifractality due to heavy-tailed returns and temporal correlations.
problem Understanding market inefficiencies and predicting volatility in digital currencies.
method Multifractal cross-correlation analysis (MFCCA) and multifractal detrended fluctuation analysis (MFDFA).
result Temporal correlations are the primary source of multifractality in digital currency markets.
Study shows multifractality emerging in decentralized cryptocurrency trading.
problem Understanding financial dynamics in decentralized cryptocurrency markets.
method Multifractal Detrended Fluctuation Analysis (MFDFA) on tick-by-tick transaction data.
result Multifractality is emerging in decentralized cryptocurrency trading, with larger fluctuations dominating.
There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. The multifractal detrended cross-correlation analysis (MF-DCCA) approaches can be used to quantify such cross-correlations, such as the MF-DCCA based on detrend…
Study shows how COVID-19 pandemic affected China's crude oil futures market efficiency.
problem Impact of COVID-19 on China's crude oil futures market efficiency.
method Multifractal analysis to compare market efficiency before and during the pandemic.
result Market efficiency of SC and its cross-correlations with other assets increased significantly after the outbreak of COVID-19.
It is ubiquitous in natural and social sciences that two variables, recorded temporally or spatially in a complex system, are cross-correlated and possess multifractal features. We propose a new method called multifractal detrended cross-correlation analysis (MF-DXA) to investigate the multifractal behaviors in the pow…
New study finds day-of-the-week effects in stock market returns using multifractal analysis.
problem Exploring calendar anomalies in stock markets, particularly day-of-the-week effects.
method Multifractal Detrended Fluctuation Analysis (MF-DFA) applied to daily returns of market indices.
result Monday returns exhibit more persistent behavior and richer multifractal structures than other days.
Study analyzes foreign exchange rates using MFDFA, revealing multifractality and its sources.
problem Analyzing multifractality in foreign exchange rates.
method Multifractal Detrended Fluctuation Analysis (MFDFA) applied to shuffled and phase-randomized return series.
result Sources of multifractality differ among currencies: US dollar fat tails, British Pound and Euro long-range correlations, Japanese Yen broad tails.
We perform an analysis of fractal properties of the positive and the negative changes of the German DAX30 index separately using Multifractal Detrended Fluctuation Analysis (MFDFA). By calculating the singularity spectra f(α) we show that returns of both signs reveal multiscaling. Curiously, these spectra display a s…
We report an empirical study of Tehran Price Index (TEPIX). To analyze our data we use various methods like as, rescaled range analysis (R/S), modified rescaled range analysis (Lo's method), Detrended Fluctuation Analysis (DFA) and generalized Hurst exponents analysis. Based on numerical results, the scaling range of…
New method detects intrinsic cross-correlations in non-stationary time series affected by common factors.
problem Bias in cross-correlation analysis due to common external factors.
method Multifractal temporally weighted detrended partial cross-correlation analysis (MF-TWDPCCA).
result MF-TWDPCCA accurately detects intrinsic cross-correlations between non-stationary time series.