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Different methodologies and uses of the Hurst exponent in econophysics

Nieves López García, María de las; Ramos-Requena, J. P. - In: Estudios de economía aplicada : revista promovida por … 37 (2019) 2, pp. 107-119

Persistent link: https://www.econbiz.de/10012063553

Evidence of intraday multifractality in European stock markets during the recent coronavirus (covid-19) outbreak

Aslam, Faheem; Mohti, Wahbeeah; Ferreira, Paulo - In: International Journal of Financial Studies : open … 8 (2020) 2/31, pp. 1-13

This study assesses how the coronavirus pandemic (COVID-19) affects the intraday multifractal properties of eight European stock markets by using five-minute index data ranging from 1 January 2020 to 23 March 2020. The Hurst exponents are calculated by applying multifractal detrended fluctuation...

Persistent link: https://www.econbiz.de/10012239424

Multifractal analysis of volatility for detection of herding and bubble : evidence from CNX Nifty HFT

Ghosh, Bikramaditya; Kozarević, Emira - In: Investment management and financial innovations 16 (2019) 3, pp. 182-193

Persistent link: https://www.econbiz.de/10012159372

Predictability and herding of bourse volatility : an econophysics analogue

Ghosh, Bikramaditya; Krishna, Mysore Chidambareswaran; … - In: Investment management and financial innovations 15 (2018) 2, pp. 317-326

Persistent link: https://www.econbiz.de/10012055468

Multifractal models, intertrade durations and return volatility

Segnon, Mawuli - 2015

Persistent link: https://www.econbiz.de/10011299266

A Markov-switching multifractal approach to forecasting realized volatility

Lux, Thomas; Morales-Arias, Leonardo; Sattarhoff, Cristina - 2011

The volatility specification of the Markov-switching Multifractal (MSM) model is proposed as an alternative mechanism … for realized volatility (RV). We estimate the RV-MSM model via Generalized Method of Moments and perform forecasting by … volatility models of asset returns. An intra-day data set for five major international stock market indices is used to evaluate …

Persistent link: https://www.econbiz.de/10009314521

Quantifying volatility clustering in financial time series

Tseng, Jie-jun; Li, Sai-ping - In: International review of financial analysis 23 (2012), pp. 11-19

Persistent link: https://www.econbiz.de/10009690145

The Markov-switching multifractal model of asset returns : GMM estimation and linear forecasting of volatility

Lux, Thomas - In: Journal of business & economic statistics : JBES ; a … 26 (2008) 2, pp. 194-210

Persistent link: https://www.econbiz.de/10003675695

Investigating efficiency of frontier stock markets using multifractal detrended fluctuation analysis

Aslam, Faheem; Ferreira, Paulo; Mohti, Wahbeeah - In: International journal of emerging markets 18 (2023) 7, pp. 1650-1676

Persistent link: https://www.econbiz.de/10014333916

A cluster driven log-volatility factor model : a deepening on the source of the volatility clustering

Verma, Anshul; Buonocore, R. J.; Di Matteo, Tiziana - In: Quantitative finance 19 (2019) 6, pp. 981-996

Persistent link: https://www.econbiz.de/10012194736

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