Investigating Long-Range Dependence of Emerging Asian Stock Markets Using Multifractal Detrended Fluctuation Analysis

Abstract

The use of multifractal approaches has been growing because of the capacity of these tools to analyze complex properties and possible nonlinear structures such as those in financial time series. This paper analyzes the presence of long-range dependence and multifractal parameters in the stock indices of nine MSCI emerging Asian economies. Multifractal Detrended Fluctuation Analysis (MFDFA) is used, with prior application of the Seasonal and Trend Decomposition using the Loess (STL) method for more reliable results, as STL separates different components of the time series and removes seasonal oscillations. We find a varying degree of multifractality in all the markets considered, implying that they exhibit long-range correlations, which could be related to verification of the fractal market hypothesis. The evidence of multifractality reveals symmetry in the variation trends of the multifractal spectrum parameters of financial time series, which could be useful to develop portfolio management. Based on the degree of multifractality, the Chinese and South Korean markets exhibit the least long-range dependence, followed by Pakistan, Indonesia, and Thailand. On the contrary, the Indian and Malaysian stock markets are found to have the highest level of dependence. This evidence could be related to possible market inefficiencies, implying the possibility of institutional investors using active trading strategies in order to make their portfolios more profitable.

Gold against Asian Stock Markets during the COVID-19 Outbreak

“…This can be true to the Asian stock markets that are globally and regionally integrated (e.g., Mohti et al (2019) and are closely linked with China due to the higher bilateral trade volume and foreign direct investment of China in Asian markets. Furthermore, Aslam et al (2020) find evidence of a long-range dependence in emerging Asian stock markets. The outbreak of COVID-19 has adversely affected the Chinese stock market, and therefore almost all other Asian stock markets.…”

Investigation of Fractal Market Hypothesis in Emerging Markets: Evidence from the MINT Stock Markets

“…Besides, self-similarity among fractal market conditions can be seen as market factors impacting investment decisions for the MINT stock market participants. Van Quang (2005), Aygören (2008), Ural and Demireli (2009), Panas and Ninni (2010), Sensoy (2013), Cevik andTopaloglu (2014, Kumar and Bandi (2015), Doorasamy and Sarpong (2018), Aslam et al (2020) conclude that the stock market prices exhibit long memory, and the FMH is valid. This study is consistent with the above findings, but inconsistent with Günay (2015).…”

Modeling Dynamic Multifractal Efficiency of US Electricity Market

“…Researchers have applied MFDFA in a variety of financial time series such as stock markets [42][43][44][45], foreign exchanges [46,47], cryptocurrency market [48,49], gold [50], futures market [51,52], green bonds [53], and the carbon emission trading market [54]. For example, Aslam et al [43] used MFDFA to examine the multifractal characteristics of MSCI in emerging Asian markets. The findings revealed the highest multifractality levels for India and Malaysia, while the Chinese and South Korean markets showed the lowest multifractality.…”