Asymmetric multi-fractality in the U.S. stock indices using index-based model of A-MFDFA

Lee, Minhyuk; Song, Jae Wook; Park, Ji Hwan; Chang, Woojin

doi:10.1016/j.chaos.2017.02.001

Cited by 42 publications

(20 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The case of temporal variations in the volatility, in particular stochastic volatility models in finance, have been considered in a huge number of papers in last decades, see for instance [41] for an overview. What we find from the analysis in this paper is a corroboration of the notion that modeling with a Hurst exponent that may change, corresponding to different roughness of the process in different epochs, is important [18,42]. We remark that a number of recent studies have considered such behavior in the context of the bitcoin market [43,44].…”

Section: Introductionsupporting

confidence: 83%

Emergence of turbulent epochs in oil prices

Garnier

Sølna

2019

Chaos, Solitons & Fractals

View full text Add to dashboard Cite

Oil price data have a complicated multi-scale structure that may vary with time. We use time-frequency analysis to identify the main features of these variations and, in particular, the regime shifts. The analysis is based on a wavelet-based decomposition and analysis of the associated scale spectrum. The joint estimation of the local Hurst exponent and volatility is the key to detect and identify regime shifting and switching of the oil price. The framework involves in particular modeling in terms of a process of "multi-fractional" type so that both the roughness and the volatility of the price process may vary with time. Special epochs then emerge as a result of these degrees of freedom, moreover, as a result of the special type of spectral estimator used. These special epochs are discussed and related to historical events. Some of them are not detected by standard analysis based on maximum likelihood estimation. The paper presents a novel algorithm for robust detection of such special epochs and multifractional behavior in financial or other types of data. In the financial context insight about such behavior of the asset price is important to evaluate financial contracts involving the asset.

show abstract

Section: Introductionsupporting

confidence: 83%

Emergence of turbulent epochs in oil prices

Garnier

Sølna

2019

Chaos, Solitons & Fractals

View full text Add to dashboard Cite

show abstract

“…The overheated bull market with false hope (irrationality in long position) and the crisis-phase bearish market with excessive fears (irrationality in short position) may be the source of inefficiency ( Lee et al, 2018 ). Therefore, testing the asymmetric market efficiency by dividing the commodity market according to the market trends in which the commodity asset price rises or falls is important for market development and the resource allocation ( Lee et al, 2017 ). Alvarez-Ramirez and Rodriguez (2015) find significant difference in inefficiency during oil price downturns and upturns.…”

Section: Introductionmentioning

confidence: 99%

Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices

et al. 2020

View full text Add to dashboard Cite

This paper examines the impacts of COVID-19 on the multifractality of gold and oil prices based on upward and downward trends. We apply the Asymmetric Multifractal Detrended Fluctuation Analysis (A-MF-DFA) approach to 15-min interval intraday data. The results show strong evidence of asymmetric multifractality that increases as the fractality scale increases. Moreover, multifractality is especially higher in the downside (upside) trend for Brent oil (gold), and this excess asymmetry has been more accentuated during the COVID-19 outbreak. Before the outbreak, the gold (oil) market was more inefficient during downward (upward) trends. During the COVID-19 outbreak period, we see that the results have changed. More precisely, we find that gold (oil) is more inefficient during upward (downward) trends. Gold and oil markets have been inefficient, particularly during the outbreak. The efficiency of gold and oil markets is sensitive to scales, market trends, and to the pandemic outbreak, highlighting the investor sentiment effect.

show abstract

“…Empirical studies using the A-MF-DFA method investigated and confirmed the asymmetric multifractal behavior in the daily returns of the DJIA index from 23 May 1980 to 25 August 2008 [352], the WTI oil price from 2 January 1986 to 14 December 2010 [352], the SSEC index from 19 December 1990 to 27 April 2012 and the SZCI index from 2 April 1991 to 27 April 2012 [353], and the DJIA, NASDAQ, NYSE, and S&P500 indices from 1 January 1991 to 31 December 2015 [354].…”

Section: Asymmetric Multifractal Analysismentioning

confidence: 74%

Multifractal analysis of financial markets

Jiang,

Xie,

Zhou

et al. 2018

Preprint

View full text Add to dashboard Cite

Multifractality is ubiquitously observed in complex natural and socioeconomic systems. Multifractal analysis provides powerful tools to understand the complex nonlinear nature of time series in diverse fields. Inspired by its striking analogy with hydrodynamic turbulence, from which the idea of multifractality originated, multifractal analysis of financial markets has bloomed, forming one of the main directions of econophysics. We review the multifractal analysis methods and multifractal models adopted in or invented for financial time series and their subtle properties, which are applicable to time series in other disciplines. We survey the cumulating evidence for the presence of multifractality in financial time series in different markets and at different time periods and discuss the sources of multifractality. The usefulness of multifractal analysis in quantifying market inefficiency, in supporting risk management and in developing other applications is presented. We finally discuss open problems and further directions of multifractal analysis.

show abstract

Asymmetric multi-fractality in the U.S. stock indices using index-based model of A-MFDFA

Cited by 42 publications

References 29 publications

Emergence of turbulent epochs in oil prices

Emergence of turbulent epochs in oil prices

Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices

Multifractal analysis of financial markets

Contact Info

Product

Resources

About