Investigating efficiency of frontier stock markets using multifractal detrended fluctuation analysis

Aslam, Faheem; Ferreira, Paulo; Mohti, Wahbeeah

doi:10.1108/ijoem-11-2020-1348

Cited by 12 publications

(7 citation statements)

References 93 publications

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“…However, some scholars have studied the effectiveness of financial market is anti-persistent. For example, Aslam et al (2021) found that markets in Kenya, Morocco, Romania, and Serbia exhibit anti-persistent behavior when studying the efficiency of frontier markets. Diao et al ( 2020) explored the efficiency of the five ASEAN countries' markets and found that the Chinese market has anti-persistent and so on.…”

Section: Time-varying Hurst Index Analysismentioning

confidence: 99%

Efficiency Analysis of Private Lending Market in China—Based on Hurst Index

Wang²

2022

JEPF

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This paper explored the efficiency of the private lending market based on the fractal market theory. We used the rescaled range analysis method and the generalized Hurst exponent analysis method respectively, and we got that the private lending market had not yet reached the weakly efficient level and was anti-persistent. Then we further used the time-varying Hurst index to describe the dynamic changes in the efficiency of the private lending market and analyzed the Chinese stock market and foreign exchange market as a comparative analysis. We found that among the three markets, the efficiency of the private lending market was the lowest, and that there was a correlation between the efficiencies of the three markets, and its effectiveness was affected by the other two markets. Finally, based on the above analysis results, we put forward relevant suggestions on the development of the private lending market and provided a decision basis for investors in the private financing market.

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Section: Time-varying Hurst Index Analysismentioning

confidence: 99%

Efficiency Analysis of Private Lending Market in China—Based on Hurst Index

Wang²

2022

JEPF

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“…Later, an extension of the DFA, i.e., multifractal detrended fluctuation analysis (MFDFA) by Kantelhardt, et al [74] was derived, and this has been employed to examine the multifractality of various financial time series such as crude oil [75], stock markets [76][77][78], cryptocurrencies [79], and even sin markets [80]. Meanwhile, based on the concept of the DFA, Podobnik, et al [81] developed the detrended cross-correlation analysis (DCCA) to examine the long-range cross-correlations between two non-stationary time series, which has been applied to various analyses [82,83].…”

Section: Introductionmentioning

confidence: 99%

Application of Multifractal Analysis in Estimating the Reaction of Energy Markets to Geopolitical Acts and Threats

et al. 2022

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Since the industrial revolution, the geopolitics of energy has been a driver of global prosperity and security, and determines the survival of life on our planet. This study examines the nonlinear structure and multifractal behavior of the cross-correlation between geopolitical risk and energy markets (West Texas Intermediate (WTI), Brent, natural gas and heating oil), using the multifractal detrended cross-correlation analysis. Furthermore, an in-depth analysis reveals different associations of the indices of overall geopolitical risk, geopolitical acts, and geopolitical threats against the four energy products. Based on daily data ranging from 1 January 1985 to 30 August 2021, the findings confirm the presence of nonlinear dependencies, suggesting that geopolitical risk and energy markets are interlinked. Furthermore, significant multifractal characteristics are found and the degree of multifractality is stronger between the overall geopolitical risk and WTI while the lowest degree of multifractality is with Brent. Overall, for the WTI and heating-oil markets, the influence of geopolitical threats is more pronounced rather than their fulfilment. Contrarily, the Brent and natural gas are more correlated to geopolitical acts. Energy products exhibit heterogeneous persistence levels of cross-correlation with all the indicators of geopolitical risk, being more persistent in the case of small fluctuations compared to large fluctuations.

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Section: Introductionmentioning

confidence: 99%

“…In this context, this study aims to investigate asymmetric MF in leading Middle East and North Africa (MENA) stock markets. Previously most of the studies focus on the symmetric MF analysis of markets by assuming similar reactions of market participants in bearish and bullish market conditions (Aslam et al, 2021). However, market participants behave differently during the upward and downward market conditions (Cao et al, 2013;Shahzad et al, 2020;Mensi et al, 2021a, b), which motivate us to do asymmetric multifractality (A-MF) analysis rather than focussing on aggregate behaviour based symmetric MF analysis.…”

Section: Introductionmentioning

confidence: 99%

Multifractality during upside/downside trends in the MENA stock markets: the effects of the global financial crisis, oil crash and COVID-19 pandemic

Mensi

Yousaf

et al. 2022

IJOEM

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Purpose This paper examines asymmetric multifractality (A-MF) in the leading Middle East and North Africa (MENA) stock markets under different turbulent periods (global financial crisis [GFC] and European sovereign debt crisis [ESDC], oil price crash and COVID-19 pandemic).Design/methodology/approach This study applies the asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) method of Cao et al. (2013) to identify A-MF and MENA stock market efficiency during the COVID-19 pandemic.Findings The results show strong evidence of different patterns of MF during upward and downward trends. Inefficiency is higher during upward trends than during downward trends in most of the stock markets in the whole sample period, and the opposite is true during financial crises. The Turkish stock market is the least inefficient during upward and downward trends. A-MF intensifies with an increase in scales. The evolution of excessive A-MF for MENA stock returns is heterogeneous. Most of the stock markets are more inefficient during a pandemic crisis than during an oil crash and other financial crises. However, the inefficiency of the Saudi Arabia and Qatar stock markets is highly sensitive to oil price crashes. Overall, the level of inefficiency varies across market trends, scales and stock markets and over time. The findings of this study provide investors and policymakers with valuable insights into efficient investment strategies, risk management and financial stability.Originality/value This paper first explores A-MF in the MENA emerging stock markets. The A-MF analysis provides useful information to investors regarding asset allocation, portfolio risk management and investment strategies during bullish and bearish market states. In addition, this paper examines A-MF under different turbulent periods, such as the GFC, the ESDC, the 2014–2016 oil crash and the COVID-19 pandemic.

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Investigating efficiency of frontier stock markets using multifractal detrended fluctuation analysis

Cited by 12 publications

References 93 publications

Efficiency Analysis of Private Lending Market in China—Based on Hurst Index

Efficiency Analysis of Private Lending Market in China—Based on Hurst Index

Application of Multifractal Analysis in Estimating the Reaction of Energy Markets to Geopolitical Acts and Threats

Multifractality during upside/downside trends in the MENA stock markets: the effects of the global financial crisis, oil crash and COVID-19 pandemic

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