Multifractal analysis of Asian markets during 2007–2008 financial crisis

Hasan, Rashid; Mohammad, Salim M.

doi:10.1016/j.physa.2014.10.030

Cited by 75 publications

(27 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…While it would be interesting, in part for robustness purposes, to extend our analyses to subsequent time periods, perhaps that pertaining to the 2007-2008 financial crisis, such data is not available to us. However, while the impact of the 2007-2008 financial crisis was felt globally, there is evidence to suggest that the Chinese stock market was not impacted to the same extent as other countries (Wang, 2014;Hasan and Mohammad, 2015). Such findings lead us to believe the financial crisis is unlikely to have changed stock market investment in China fundamentally.…”

Section: Datamentioning

confidence: 99%

Are investors consistent in their trading strategies? An examination of individual investor-level data

Duxbury

Yao

2017

International Review of Financial Analysis

View full text Add to dashboard Cite

show abstract

Section: Datamentioning

confidence: 99%

Are investors consistent in their trading strategies? An examination of individual investor-level data

Duxbury

Yao

2017

International Review of Financial Analysis

View full text Add to dashboard Cite

show abstract

“…Their results show that even though the multifractal strength is not different during the crisis, the shape of the multifractal spectrum has been clearly influenced by the crisis. Hasan and Salim (2014) also report that the 2008 crisis has distorted the shapes of multifractal spectra of the Asian stock markets. Siokis (2014) investigated the multifractal nature of the three distressed European stock markets (Greece, Ireland and Portugal) prior and after the memorandum of understanding (MoU).…”

Section: Studies About the Stock Marketsmentioning

confidence: 99%

“…By using q-generalised Hurst exponents H(q), one can obtain the multifractal spectrum f(α) through Legendre transform given in equation (9). As noted by Hasan and Salim (2014), multifractal singularity spectrum f(α) can provide valuable information about the price fluctuations, market risk and efficiency level of the market. The width of the singularity spectrum defines the intensity of multifractality, while its shape provides information about the sensitivity of multifractality to large and small fluctuations (Günay, 2014).…”

Section: Detection Of Multifractalitymentioning

confidence: 99%

Testing for multi-fractality and efficiency in selected sovereign bond markets: a multi-fractal detrended moving average (MF-DMA) analysis

Bayracı¹

2018

IJCEE

View full text Add to dashboard Cite

This study examines the multifractality and relative efficiency in sovereign bond markets, using the multifractal detrended moving average (MF-DMA) approach to quantify the degree of multifractality in the international sovereign bond yields. We use the daily values of the 2-year maturity government bond yields for 12 countries between 2003 and 2014 for empirical analysis. Our results document that all bond markets show multifractal characteristics in various levels. High degree of multifractality is seen in the Spanish, Portuguese and Italian bond markets while low multifractality features belong to the Canadian and the US bond market. The source of multifractality is mainly due to the structure of the bond markets where the recent Eurozone debt crisis has manifested itself as extreme observations.

show abstract

“…On the other hand, multifractal analysis is often used in other markets experiencing financial crisis or other events. Hasan et al [18] used the MF-DFA technique to investigate the multifractal structure of the U.S. and seven Asian stock markets during the crisis period, showing that the peaks of the singularity spectra shift to lower values of α and markets of the U.S., Japan, Hong Kong, Korea, and Indonesia exhibit increased long range correlations of large fluctuations in index returns and that the tail exponent increases across all markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficiency and Multifractality Analysis of the Chinese Stock Market: Evidence from Stock Indices before and after the 2015 Stock Market Crash

Han

Wang

2019

Sustainability

View full text Add to dashboard Cite

This paper examines the daily return series of four main indices, including Shanghai Stock Exchange Composite Index (SSE), Shenzhen Stock Exchange Component Index (SZSE), Shanghai Shenzhen 300 Index (SHSE-SZSE300), and CSI Smallcap 500 index (CSI500) in Chinese stock market from 2000 to 2018 by multifractal detrended fluctuation analysis (MF-DFA). The series of the daily return of the indices exhibit significant multifractal properties on the whole time scale and SZSE has the highest multifractal properties among the four indices, indicating the lowest market efficiency. The multifractal properties of four indices are due to long-range correlation and fat-tail characteristics of the non-Gaussian probability density function, and these two factors have different effects on the multifractality of four indices. This paper aims to compare the multifractility degrees of the four indices in three sub-samples divided by the 2015 stock market crash and to discuss its effects on efficiency of the Shanghai and Shenzhen stock market in each sub-sample. Meanwhile, we study the effect of the 2015 stock market crash on market efficiency from the statistical and fractal perspectives, which has theoretical and practical significance in the application of Effective Market Hypothesis (EMH) in China’s stock market, and it thereby affects the healthy and sustainability of the market. The results also provide important implications for further study on the dynamic mechanism and efficiency in stock market and they are relevant to portfolio managers and policy makers in a number of ways to maintain the sustainable development of China’s capital market and economy.

show abstract

Multifractal analysis of Asian markets during 2007–2008 financial crisis

Cited by 75 publications

References 49 publications

Are investors consistent in their trading strategies? An examination of individual investor-level data

Are investors consistent in their trading strategies? An examination of individual investor-level data

Testing for multi-fractality and efficiency in selected sovereign bond markets: a multi-fractal detrended moving average (MF-DMA) analysis

Efficiency and Multifractality Analysis of the Chinese Stock Market: Evidence from Stock Indices before and after the 2015 Stock Market Crash

Contact Info

Product

Resources

About