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.
Highlights
A financial system is an integral part of an economy, allowing for the exchange of funds between lenders, borrowers, investors, and government entities, and efficient resource allocation.Correct understanding of financial markets’ structures is important for the design of appropriate public policies, investment strategies and portfolios, or taxation and legal frameworks, which are major ingredients of a well-structured economy
The study of financial markets has long been based on the Random Walk Hypothesis (RWH) introduced by the authors of [1], which assumes that stock prices are described by a random walk, this being the basis of a fundamental theory of financial markets, namely, the Efficient Market Hypothesis (EMH) proposed in [2]
Market structures do not behave in this way and different research reveals that stock markets have ubiquitous properties [3,4,5], Symmetry 2020, 12, 1157; doi:10.3390/sym12071157
Summary
A financial system is an integral part of an economy, allowing for the exchange of funds between lenders, borrowers, investors, and government entities, and efficient resource allocation.Correct understanding of financial markets’ structures is important for the design of appropriate public policies, investment strategies and portfolios, or taxation and legal frameworks, which are major ingredients of a well-structured economy. Symmetry 2020, 12, 1157 with issues described in the literature as stylized facts like fat tails [6], long-term correlations [7], volatility clustering [8], fractals/multifractals [9], and chaos [10], with these properties making financial markets inconsistent with both EMH and RWH [11]. These inconsistencies required more logical explanation of market movements than the ones described by the EMH. The authors of [12,13] developed the Fractal Market
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