Degree distribution of the visibility graphs mapped from fractional Brownian motions and multifractal random walks

The dynamics of a complex system is usually recorded in the form of time series, which can be studied through its visibility graph from a complex network perspective. We investigate the visibility graphs extracted from fractional Brownian motions and multifractal random walks, and find that the degree distributions exhibit power-law behaviors, in which the power-law exponent $\alpha$ is a linear function of the Hurst index $H$ of the time series. We also find that the degree distribution of the visibility graph is mainly determined by the temporal correlation of the original time series with minor influence from the possible multifractal nature. As an example, we study the visibility graphs constructed from two Chinese stock market indexes and unveil that the degree distributions have power-law tails, where the tail exponents of the visibility graphs and the Hurst indexes of the indexes are close to the $\alpha\sim H$ linear relationship.Comment: 7 pages, 7 figure

A Comparative Analysis of Vietnamese and Chinese Stock Market Using Hurst Exponent Analysis

Vietnamese economy has developed tremendously since the early 1990s, keeping its GDP growth rate above 7% for a long time. After a few years’ slow down due to the Asian Crisis, it re-developed after 2002. Unfortunately, since the Subprime Loan Crisis broke out in 2007, its economy development became slow and had shown no sign of recovery. Before the global crisis, HoChiMinh Stock Exchanges was established in 2000 and five years later, in the capital of Vietnam – Hanoi, the Hanoi Stock Exchanges was opened. These two markets did not evolve as quickly as expected. On the contrary, it is still underdeveloped even though it has existed for more than ten years. This paper discusses and analyses the overview and present status of Vietnamese Stock Market. By comparing it with the Chinese Stock Market, the similarities and differences between the two markets are determined. Then, the reasons of underdevelopment of Vietnamese Stock Market are examined

The Evolution of Efficiency in the Chinese Stock Market

This dissertation examines the weak-form efficiency of the Chinese stock market and provides evidence on how the market efficiency evolved throughout the last three decades. The Shanghai Composite Index (SSEC) and the Shenzhen Component Index (SZSE) are the primary indicators of the Chinese stock market in this study. Both traditional economics and the complex systems’ methods are employed to evaluate market efficiency, with an additional focus on the effect of two parameter inputs (embedded dimension and noise filter) on entropy methods to improve their ability to detect phase transitions in stock market data. The traditional efficiency tests indicate that the Chinese stock market during the full sample period of 1990-2021 is inefficient, but some of the sub-sample periods indicate the weak-form efficiency, except for the ADF test. Meanwhile, the complex systems’ methods suggest that the level of randomness in returns increases over time. Additionally, I find that the bull periods of the Chinese market are less efficient than the bust periods, which may indicate that investors tend to commit more errors during the bull period. Generally, the study concludes that the complex systems’ methods provide a more comprehensive evaluation of the changes in the market efficiency than traditional methods. The empirical results suggest that the Chinese stock market is not completely efficient based on the traditional efficiency tests but the level of efficiency has improved over time based on the evidence of the complex systems’ analysis

Is the Chinese Stock Market Really Efficient

Groenewold et al (2004a) documented that the Chinese stock market is inefficient. In this paper, we revisit the efficiency problem of the Chinese stock market using time-series model based trading rules. Our paper distinguishes itself from previous studies in several aspects. First, while previous studies concentrate on the viability of linear forecasting techniques, we evaluate the profitability of the forecasts of the self-exciting threshold autoregressive model (SETAR), and compare it with the conventional linear AR and MA trading rules. Second, the finding of market inefficiency in earlier studies mainly rest on the statistical significance of the autocorrelation or regression coefficients. In contrast, this paper directly examines the profitability of various trading rules. Third, our sample covers an extensive period of 1991-2010. Sub-sample analysis shows that positive returns mainly concentrate in the pre-SOE reform period, suggesting that China’s stock market has become more efficient after the reform

Is the Chinese Stock Market Really Efficient

Groenewold et al (2004a) documented that the Chinese stock market is inefficient. In this paper, we revisit the efficiency problem of the Chinese stock market using time-series model based trading rules. Our paper distinguishes itself from previous studies in several aspects. First, while previous studies concentrate on the viability of linear forecasting techniques, we evaluate the profitability of the forecasts of the self-exciting threshold autoregressive model (SETAR), and compare it with the conventional linear AR and MA trading rules. Second, the finding of market inefficiency in earlier studies mainly rest on the statistical significance of the autocorrelation or regression coefficients. In contrast, this paper directly examines the profitability of various trading rules. Third, our sample covers an extensive period of 1991-2010. Sub-sample analysis shows that positive returns mainly concentrate in the pre-SOE reform period, suggesting that China’s stock market has become more efficient after the reform

Study on Time Varying Hurst Index and Multifractal Features of Shanghai and Shenzhen Stock Markets

随着人们对股市研究的深入，时变赫斯特指数及其与股指走势的关系、多重分形特征及其与股指波动的关系成为股市分形研究的热点。分形是非线性理论中非常重要的一种分析方法，它能有效解释自然中极其复杂的现象，因此日渐成为资本市场理论中强有力的分析工具，本文正是利用分形理论对股市的单分形和多重分形进行深入研究。 在总结研究综述的基础上，本文首先利用滚动窗口的消除波动趋势分析（DFA，DetrendedFluctuationsAnalysis）方法分析了上证指数和深圳成指的全局赫斯特指数、不同时间段和不同时间标度的分形特征以及时变Hurst指数，并提出基于时变Hurst指数的投资策略。之后本文又利用多重分形理...With the further research of fractal, time varing Hurst as well as its relation with the trend of the stock and multifractal which is related with volatility is more and more popular in the field of stock fractal. As one of the important unlinear theoris, fractal can explain many complicated phenomenon and has become a strong analysis tool in capital market theory. So this thesis is going to make ...学位：管理学硕士院系专业：管理学院管理科学系_技术经济及管理学号：1772008115126

Commodity price volatility, stock market performance and economic growth: evidence from BRICS countries

Abstracts in English, Afrikaans and ZuluThe study investigated the nexus between commodity price volatility, stock market performance, and economic growth in the emerging economies of Brazil, Russia, India, China, and South Africa (the BRICS) predicated on two hypotheses. First, the study hypothesised that in modern integrated financial systems, commodity price volatility predisposes stock market performance to be non-linearly related to economic growth. The second hypothesis was that financial crises are an inescapable feature of modern financial systems. The study used daily data on stock indices and selected commodity prices as well as monthly data on national output proxies and stock indices. The study analysed data for non-linearities, fractality, and entropy behaviour using the spectral causality approach, univariate GARCH, EGARCH, FIGARCH, DCC-GARCH, and Markov Regime Switching (MRS) – GARCH. The four main findings were: first, spectral causality tests signalled dynamic non-linearities in the relationship between the three commodity futures prices and the BRICS stock indices. Second, the predominantly non-linear relationship between commodity prices and stock prices was reflected in the nexus between the national output proxies and the indices of the five main commodity classes. Third, spectral causality analysis revealed that the causal structures between commodity prices and national output proxies were non-linear and dynamic. Fourth, the Nyblom parameter stability tests revealed evidence of structural breaks in the data that was analysed. The DCC-GARCH model uncovered strong evidence of contagion, spillovers, and interdependence. The study added to the body of knowledge in three ways. First, micro and macro levels of commodity price changes were linked with corresponding stock market performance indicator changes. Second, unlike earlier studies on the commodity price – stock market performance – economic growth nexus, the study employed spectral causality analysis, single - regime GARCH analysis, Dynamic Conditional Correlation (DCC) – GARCH and a two-step Markov – Regime – Switching – GARCH as a unified analytical approach. Third, spectral causality graphs depicting relationships between stock indices and national output proxies revealed benign business cycle effects, thus, contributing to broadening the scope of business cycle theoryBusiness ManagementPhD. (Management Studies