Search

This study examines the upward and downward multifractality, long-memory process, and efficiency of the Shanghai stock exchange composite index of mainland China and the Hang Seng index (HSI) of Hong Kong using the symmetric multifractal detrended fluctuation analysis (MF-DFA), asymmetric MF-DFA (A-MF-DFA), and the Hurst exponent. The results reveal significant differences in upward and downward multifractality, indicating asymmetric multifractality regardless of the frequencies. Moreover, we find evidence of excess asymmetry in multifractality for both markets and for all frequencies, which is more pronounced during downward stock price movements for Hang Seng Index (HSI) markets. The Hong Kong market is less inefficient than Chinese markets. Additionally, Bitcoin (BTC) volumes and BTC trading capitalizations affect the efficiency level across quantiles. Finally, robustness tests confirm our results are robust. [ABSTRACT FROM AUTHOR]

This study seeks to investigate the extreme risk spillovers from crude oil to four major Asian stock markets from a market sentiment perspective. A copula-CoVaR (Conditional Value-at-Risk) approach is adopted to construct a dynamic network to capture the contributions of different types of market sentiment to the evolution of oil-stock risk nexus. The empirical evidence shows the presence of significant risk spillover effects from crude oil to equity markets. The dynamics of the oil-to-stock risk spillovers is shown to be significantly driven by market sentiments, mainly market fears in both stock markets and crude oil market triggered by prominent systemic events. As an extreme event unfolds, the oil-to-stock risk spillover dynamics is increasing susceptible to escalating market fears. [ABSTRACT FROM AUTHOR]

Sri Lanka holds a pivotal position in the Indian Ocean, fostering significant economic ties with South Asia, the Middle East, and Africa. This study examines the financial linkages and stock market behavior between Sri Lanka and key Asian economies (India, China, Pakistan, and Japan) from 2015 to 2021. Using daily stock prices from Bloomberg.com, the analysis employs the EGARCH (1,1) model to assess return and volatility spillovers. Results reveal negative return spillovers from India to Sri Lanka and cross-volatility spillovers from India, China, Pakistan, and Japan to Sri Lanka. Conversely, Sri Lanka exhibits negative return spillovers to India and Pakistan and cross-volatility spillovers to China and Japan. Sub-analysis identifies structural breaks in December 2019, indicating shifts in spillover dynamics pre- and post-Covid-19. These findings offer insights for investors, policymakers, fund managers, and governments to optimize investment strategies, formulate stable policies, and enhance portfolio diversification. [ABSTRACT FROM AUTHOR]

This study investigates whether China's crude oil futures (INE) and West Texas Intermediate (WTI) markets hold valuable information for estimating the realized volatility of seven Asian stock markets. This study has several notable findings. First, China's oil futures can trigger forecast accuracy for three equity indices (Nikkei 225, NSEI, and FT Straits Times), whereas WTI helps forecast the volatility of the two indices (KSE 100 and KOSPI). Second, comparing China's crude oil futures with WTI's crude oil futures, we find that the former could be an effective indicator for all seven Asian stock markets during a high‐volatility period, while WTI information is helpful in forecasting the volatility of the KSE 100, NSEI, and FT Strait Times during the low‐volatility period. Further, information of both oil futures is ineffective for the Hang Seng and SSEC equity indices. Our results are robust in several robustness checks, including alternative evaluation methods, recursive window approach, and alternative realized measures, even during the COVID‐19 pandemic. [ABSTRACT FROM AUTHOR]

This study aims to investigate bidirectional risk spillovers between the Chinese and other Asian stock markets. To achieve this, we construct a dynamic Copula-EVT-CoVaR model based on 11 Asian stock indexes from 1 January 2007 to 31 December 2021. The findings show that, firstly, synchronicity exists between the Chinese stock market and other Asian stock markets, creating conditions for risk contagion. Secondly, the Chinese stock market exhibits a strong risk spillover to other Asian stock markets with time-varying and heterogeneous characteristics. Additionally, the risk spillover displays an asymmetry, indicating that the intensity of risk spillover from other Asian stock markets to the Chinese is weaker than that from the Chinese to other Asian stock markets. Finally, the Chinese stock market generated significant extreme risk spillovers to other Asian stock markets during the 2007–2009 global financial crisis, the European debt crisis, the 2015–2016 Chinese stock market crash, and the China–US trade war. However, during the COVID-19 pandemic, the risk spillover intensity of the Chinese stock market was weaker, and it acted as the recipient of risk from other Asian stock markets. The originality of this study is reflected in proposing a novel dynamic copula-EVT-CoVaR model and incorporating multiple crises into an analytical framework to examine bidirectional risk spillover effects. These findings can help Asian countries (regions) adopt effective supervision to deal with cross-border risk spillovers and assist Asian stock market investors in optimizing portfolio strategies. [ABSTRACT FROM AUTHOR]

This study aims to investigate the causal relationship between stock returns and stock volume, using the data of eight developing and developed countries of Asia over nine year, including Pakistan, India, Malaysia, China, Japan, South Korea, Hong Kong, and Taiwan (that carry 40 percent share of the world's GDP). By incorporating the bivariate GARCH approach, to examine how stock returns affect trading volume and vice versa. According to the results, there is a contemporary relationship between stock return and trading volume before testing Granger causality; hence, a rise in the market index returns is accompanied by mounting volume, whereas the declining market is accompanied by falling volume. So, the Granger causality predicts the trends among stock markets of sample Asian countries. [ABSTRACT FROM AUTHOR]

The main aim of this study is to measure the dynamic connectedness and spillover effects among emerging stock markets in Asia and the developed stock markets of the US and Europe in the ongoing Ukrainian crisis. The paper also aims to provide a comparative analysis of return and volatility spillovers during the global financial crisis in 2008, the COVID-19 pandemic, and the Ukrainian crisis. This paper utilizes the multiple structural beak test of Bai & Perron (2003) and also depicts the risk and return transmissions among these markets using the Diebold & Yilmaz (2012) method. The main outcomes of this study indicate that the stock markets in Asia are less affected by the political crisis in Ukraine as compared to the previous effects during the GFC and COVID-19 periods. The results also show that sensitivity of Asian financial markets to global shocks has been weakened in the wake of the Ukrainian crisis in favour of increased resilience of Asian stock indices to external shocks. These results carry an important implication for international and local investors as well as for policy makers in Asia, where investors have greater potentials for portfolio diversify and risk reduction across Asian markets. Doi: 10.28991/ESJ-2023-07-02-04 Full Text: PDF

This research aims to investigate the kind of link and potential long-term and short-term relationships between the stock market indexes of India and certain Asian and African nations. The stock market indexes of India, Indonesia, South Africa, Japan, Singapore, and China are studied using annual data from 2000 to 2021. There is a strong correlation between the stock markets. With a correlation coefficient ranging from 0.68 to 0.82, all nations have substantial correlations with the Indian stock market, with the exception of the Chinese stock market. Augmented Dickey-Fuller Test is used to determine whether the time series data is stationary or not, it is discovered that all values of the series are stationary at their level form. The Johansen Co-integration Approach is used to analyse the long-term linkages between the stock market indexes. The result demonstrated that the NSE Nifty and other key stock exchange indexes in Asian and African markets have a long-term relationship.

The economic growth of China has been driven by the development of its real estate market, especially after the 2008 crisis. This growth is mostly related to the huge housing bubble and growing amounts of sovereign debt that have been redirected to corporations in the sector. Evergrande is one of those corporations; it is a Chinese company in the construction and real estate sector, a global giant with investments in many parts of the world. Its bond default in September 2021 sounded alerts in financial markets. Several news outlets spoke of the "next Lehman Brothers", and apprehension was very high, especially in Asian markets. This research work aims to evaluate the impact of Evergrande's bond default on six Asian stock markets, using an event study approach. The results show a strong reaction from the markets towards the event in study, even anticipating it. Furthermore, it is worth mentioning a quick reversion to "normal" behavior, indicating the rapid absorption of information by the markets. [ABSTRACT FROM AUTHOR]

This paper examines stock market integration between the five ASEAN countries and both the US and China in turn, over the period from November 2002 to August 2020. The linkages between both aggregate and financial sector stock indices (both weekly and monthly) are analyzed using fractional integration and fractional cointegration methods. Further, recursive cointegration analysis is carried out for the weekly series to study the impact of the 2007–8 global financial crisis and the 2015 China stock market crash on the pattern of stock market co-movement. The main findings are the following. All stock indices exhibit long-range dependence. There is cointegration between the five ASEAN countries and the US but almost none between the former and China, except between Indonesia and China in the case of the financial sector. The 2007–8 global financial crisis and the 2015 Chinese stock market plunge weakened the linkages between the ASEAN five and both China and the US. The implications of these results for market participants and policy makers are discussed. [ABSTRACT FROM AUTHOR]

This study analyzes why the negative momentum effect appears in Asian (China, Japan, Korea) stock markets, contrary to the U.S. market. We use principal component momentum (PMOM), a newly devised momentum measure. The PMOM is constructed by extracting commonalities from traditional momentum measures using principal component analysis. The results show evidence of positive and negative momentum profits in the U.S. and Asian markets, respectively. Negative momentum profits in Asian markets are attributable to the strong performance reversal of small stocks in the loser portfolio. Conversely, the positive momentum profits of the U.S. market are driven by the performance continuity of small stocks in the winner portfolio. The PMOM strategy is significantly more advantageous than traditional momentum strategies, based on the economic and statistical perspectives of momentum profits. These results are robust to changes in empirical designs. [Display omitted] • Principal Component Momentum measure (PMOM) is introduced as a new measure. • Momentum is investigated by combining PMOM with the arbitrage-weighting method. • The Asian stock markets are attributed to small-cap stocks in the loser portfolio. • The U.S. stock markets are attributed to small-cap stocks in the winner portfolio. • This study robustly shows the applicability and expandability of the PMOM methodology. [ABSTRACT FROM AUTHOR]

The analysis and prediction of stock markets in Asian is an important issue which can help to promote the integration and globalization of financial cooperation. However, owning to the non-stationary and complexity of the stock market fluctuation, it is challenging to predict the stock price accurately. Especially after the decomposition of the original series, how to solve the problem of pseudo information and filter the exogenous variables is often certain challenging. This paper presents a hybrid model based on secondary decomposition (SD), multi-factor analysis (MFA) and attention-based long short-term memory (ALSTM) to predict the stock market price trends of four major Asian countries. The original stock price series is preprocessed by two decomposition algorithms so as to capture further non-linear feature and better filter the noise. Multi-factor analysis is introduced as a supplement to the original data information. In the prediction stage, attention layer is added in long short-term memory model to increase the weights of effective information. Finally, four datasets about Asian stock markets and nine compared models were used to verify the performance of the proposed model. The empirical analysis results show that compared to the general long short-term memory, our proposed model can obtain higher 30% accuracy at least. The mean average percentage errors of the system were also the lowest among all models mentioned in this paper (0.612%, 0.903%, 0.606% and 0.402% respectively), which proves the effectiveness of the hybrid model. [ABSTRACT FROM AUTHOR]

The current research intends to examine the commodities' dynamism connection with stock prices under the COVID-19 crisis. DCC-GARCH modeling was applied to the data of Asian economies, including China, India, Sri Lanka, Bangladesh, and Pakistan to achieve the study objectives. The study's results indicated a significant connection between gold prices with stock prices and oil prices for all Asian stock markets. The results of the study constructs were symmetrical. In general, the connection grows with the frequency. The lowest frequency months contributed the most to the total relationship, followed by more than 12 months. Overall, gold and oil prices influence the Asian stock markets. These research findings can avoid contagion in times of economic uncertainty. This study also suggested policy implications for better decision-making of key stakeholders. Dynamic coefficient values were about 0.8 of β2 because nations' internal markets were more closely linked. There are also dynamic relationship factors between crude oil and foreign currency markets, where the correlations in India and China have always been around 0., (© 2022 Elsevier Ltd. All rights reserved.)