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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]

We provide evidence that the use of technical trading rules provides traders the opportunity to generate profits from actively buying and selling individual stocks across Asian markets. We test the trading performance of three widely used technical trading strategies, the Arithmetic Moving Average, the Relative Strength Index, and the Stochastic Oscillator, as well as variations to each trading strategy. We compare the results of these trading rules to a long-term buy-and-hold strategy across 4822 stocks traded in 39 Asian countries. Our results, when applying a simple behavior intervention filter of only selling a position when a trade is profitable, show that these technical trading rules, on average, were able to outperform the buy-and-hold strategy for 66% of the stocks listed in our sample. Additionally, given any of the listed Asian stocks, we found that, on average, a trader could apply any technical trading strategy and have a greater than 50–50 chance of outperforming the buy-and hold strategy for that stock for 63% of all stocks. [ABSTRACT FROM AUTHOR]

This study investigated the Value at Risk (VaR) and the Component Expected Shortfall (CES) to find an optimal portfolio investment for 15 Asian stock markets. The data is collected from 2006 to 2019, and then categorized into three precrisis periods, crisis, and post-crisis of the global financial crisis in 2008. Empirical results showed that the VaR had increased from 0.0034 to 0.0062 (82.35%) during the crisis period, but it had decreased from 0.0062 to 0.0035 (43.55%) after the crisis . Obviously, the crisis influenced the risk of Asia stock markets. According to the portfolio analysis, the result revealed that Malaysian stock was suggested as the highest investment proportion for pre-crisis, and crisis period. After the crisis, Indonesian stocks are suggested as the highest investment proportion, whereas the investment in stock markets of Singapore, Turkey, and Russian is not suggested. [ABSTRACT FROM AUTHOR]

The corona virus outbreak, which originated in China, has infected lakhs of people. Its spread has left businesses around the world counting costs. The corona virus is going global, and it could bring the world economy to a standstill. COVID-2019 that began in the depths of China's Hubei province is spreading rapidly, persuading the World Health Organization to declare it as a pandemic. There are now significant outbreaks from South Korea to Italy and Iran, from America to Britain. The ongoing spread of the new corona virus has become one of the biggest threats to the global economy and financial markets. The economic impact of the COVID-2019 pandemic has introduced extraordinary volatility in global financial markets, as participants are obliged to reassess their valuations of all investments and associated derivatives as the situation develops. In an environment where uncertainty makes it unusually hard to price assets and for market-makers to operate, exchanges are providing the only way to establish consensus on these valuations in real time. Volatility has reached levels comparable with the Global Financial Crisis of 2008, with one-day losses not seen since 1987. The situation is made more challenging by high levels of indebtedness and already low interest rates. The financial markets are all integrated into one as global markets in the current era of globalization. It is important that financial markets remain able to perform their role — providing investors with liquidity, facilitating price discovery, and allowing for risk transfer and the transmission of monetary policy. This study aims at examining the performance of the selected Asian stock markets amidst the times of COVID-2019. This study intends to examine the interlinkages of Asian stock markets selected and to observe the impact of COVID-2019 on these markets. The period of study is from 1st December, 2019 to 31st March, 2020. The tools adopted for the study are correlation, regression, ANOVA and paired sample t test. [ABSTRACT FROM AUTHOR]

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.

Based on the time-varying regression model of Chow et al. (J Comp Econ 39(4):577-583, 2011. doi:10.1016/j.jce.2011.06.001), this paper simultaneously analyzes the ebb and flow of change by China and the U.S. as leading players in relation to their comovement on various Asian stock markets. We include several important controls for worldwide economy performance, the stock market return rates of major importing nations, and linear/non-linear time trend fixed effects to stress the influence of China and U.S. on eight Asian economies. The empirical results indicate the increasing influence of the China stock market during the subprime mortgage crisis. Moreover, the U.S. market remains influential on the Chinese region, but loses/decreases its influence, especially on the Four Asian Tigers, significantly during/after the subprime mortgage crisis. [ABSTRACT FROM AUTHOR]

This study investigated the impact of Muslim Holy Days on daily stock returns of Asian financial markets for a period of 2001–2014. These markets include Pakistan, Bahrain, Saudi Arabia, and Turkey. The study has tried to isolate the effect of Gregorian calendar anomalies from Muslim Holy Days to certify that the documented effect is actually a result of Muslim Holy Days rather than Gregorian calendar anomalies. Pooled fixed/random effect Panel Regression is used to check the underlined effect. The results reveal that Eid-ul-Fitr is the only Holy day, which has significant positive effect on stock returns of Asian markets, while all other Holy Days have no effect. Friday is the only Gregorian calendar anomaly, which exists in Asian markets. These results provide support to the fact that both Islamic and Gregorian calendar anomalies exist in Asian markets.

In this study, we examined the fractal structure of the Nikkei225, HangSeng, Shanghai Stock Exchange and Straits Times Index of Singapore. Empirical analysis was performed via non-parametric, semi-parametric long memory tests and also fractal dimension calculations. In order to avoid spurious long memory features, besides the Detrended Fluctuations Analysis (DFA), we also used Smith’s (2005) modified GPH method. As for fractal dimension calculations, they were conducted via Box-Counting and Variation tests. According to the results, while there is no long memory property in log returns of any index, we found evidence for long memory properties in the volatility of the HangSeng, the Shanghai Stock Exchange and the Straits Times Index. However, we could not find any sign of long memory in the volatility of Nikkei225 index using either the DFA or modified GPH test. Fractal dimension analysis also demonstrated that all raw index prices have fractal structure properties except for the Nikkei225 index. These findings showed that the Nikkei225 index has the most efficient market properties among these markets.

Diebold–Yilmaz spillover indexes are computed for weekly return volatilities based on daily benchmark stock indexes of the US, the UK, and 10 Asian countries. We found (i) the strengthening of overall volatility spillovers is not a temporary surge but persisted after the crisis; (ii) the susceptibility of individual Asian stock markets to inward volatility transfers is linked to its degree of openness; and (iii) the Asian bourses are becoming more important emitters of financial shocks since the crisis. Rolling regressions on volatility linkages reveal the relative dominance of the US over the Japanese and Chinese bourses, and the level of influence on Asian stock markets from the Chinese bourse has risen to that of Japan. [ABSTRACT FROM PUBLISHER]

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 objective of this research isto measure and examine volatilities among important stock markets of Asia and to ascertain a causal relation between volatility and stock returns. For this purpose six markets KSE100 (Karachi, Pakistan), BSE Sensex (Mumbai, India), NIKKEI 225 (Tokyo, Japan), Hang Seng (Hong Kong), Shanghai Stock Exchange (SSE) (Shanghai, China) and KOSPI (Seoul, South Korea) were considered. Stock market indices comprise of daily data from the period January 2002 to December 2009. The graphical representation of time series shows the preliminary examination of stock behaviors. The analysis shows the high correlation and heteroskedastic trend (volatility) among the stock markets in selected time period. After preliminary analysis the formal descriptive method of mean, standard deviation and coefficient of variation have been applied for measuring and ranking purposes. The results show that KOSPI has the highest average annual return of 12.67% and followed by BSE with 11.61%, whereas, KSE 100 has the least annual average returns of 9.31%. The highest volatility coefficient of 3.097 has been observed in Hang Seng (Hong Kong) followed by 2.87 in Nikkei (Tokyo). However, the KSE 100 observed the lowest volatility coefficient of 2.078. Bartlett’s test is applied for the inferential analysis to investigate whether the equality of volatility is the same in each market return. Finally, GARCH (1, 1) model is applied which concludes a significant ARCH (1) and GARCH (1) effects and confirms all markets’ returns are statistically significant since p < 0.01 and their Long Run Average Variances (LRAV) range from 1.52% to 2.54% for KSE100 Index and Shanghai Stock Exchange respectively. First published online: 23 Nov 2016

Both practitioners and academics demand a linkage model across financial markets, particularly among regional capital markets, for both risk management and portfolio selection purposes. Researchers frequently use cointegration and causality analysis in investigating the dependence or co-movement of three or more stock markets in different countries. However, they mostly conduct causality in mean tests but not causality in variance tests. This study assesses the cointegration and causal relations among seven developed Asian markets, i.e., Tokyo, Hong Kong, Korea, Taiwan, Shanghai, Singapore, and Kuala Lumpur stock exchanges, using more frequent time series data. It employs the recently developed techniques for investigating unit roots, cointegration, time-varying volatility, and causality in variance. For estimating portfolio market risk, this study employs Value-at-Risk with delta normal approach. The results would recommend whether fund managers are able to diversify their portfolio in these developed stock markets either in long run or in short run.

The objective of this research isto measure and examine volatilities among important stock markets of Asia and to ascertain a causal relation between volatility and stock returns. For this purpose six markets KSE100 (Karachi, Pakistan), BSE Sensex (Mumbai, India), NIKKEI 225 (Tokyo, Japan), Hang Seng (Hong Kong), Shanghai Stock Exchange (SSE) (Shanghai, China) and KOSPI (Seoul, South Korea) were considered. Stock market indices comprise of daily data from the period January 2002 to December 2009. The graphical representation of time series shows the preliminary examination of stock behaviors. The analysis shows the high correlation and heteroskedastic trend (volatility) among the stock markets in selected time period. After preliminary analysis the formal descriptive method of mean, standard deviation and coefficient of variation have been applied for measuring and ranking purposes. The results show that KOSPI has the highest average annual return of 12.67% and followed by BSE with 11.61%, whereas, KSE 100 has the least annual average returns of 9.31%. The highest volatility coefficient of 3.097 has been observed in Hang Seng (Hong Kong) followed by 2.87 in Nikkei (Tokyo). However, the KSE 100 observed the lowest volatility coefficient of 2.078. Bartlett’s test is applied for the inferential analysis to investigate whether the equality of volatility is the same in each market return. Finally, GARCH (1, 1) model is applied which concludes a significant ARCH (1) and GARCH (1) effects and confirms all markets’ returns are statistically significant since p < 0.01 and their Long Run Average Variances (LRAV) range from 1.52% to 2.54% for KSE100 Index and Shanghai Stock Exchange respectively. [ABSTRACT FROM AUTHOR]

The role of stock index futures (SIFs) in the stock market is very much under debate in the literature. This article studies the effect of the introduction of SIFs to the spot market in China and six other Asian markets. Based on the previous literature, we develop a hypothesis that in a bull market in which bubbles and noise traders are more likely to exist, the introduction of SIFs as an arbitrage instrument may cause price reversal and increase short-term volatility in the underlying market. We examine China and six other major stock markets in Asia to test this hypothesis. Pre- and post-launch standard volatility comparison, rolling windows estimation of volatility, and Markov Switching ARCH estimation are employed in our empirical analysis. Our results are found to support our hypothesis. [ABSTRACT FROM PUBLISHER]

We conduct predictability tests for selected Asian stock markets using monthly data from the period March 2001–April 2012. Asian market bears and returns are predicted using the U.S. stock market bears and returns. A two-state Markov-switching model is employed to distinguish between the bull and bear regimes in the U.S. and Asian stock markets. The in-sample predictability analysis suggests that the U.S. market returns and bears are important predictors of Asian market returns and some Asian bears. The out-of-sample predictability exercise is not able to reinforce the in-sample results, which is in large part due to the small forecasting sample size. [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]

In this study, we examined the fractal structure of the Nikkei225, HangSeng, Shanghai Stock Exchange and Straits Times Index of Singapore. Empirical analysis was performed via non-parametric, semi-parametric long memory tests and also fractal dimension calculations. In order to avoid spurious long memory features, besides the Detrended Fluctuations Analysis (DFA), we also used Smith's (2005) modified GPH method. As for fractal dimension calculations, they were conducted via Box-Counting and Variation (p=1) tests. According to the results, while there is no long memory property in log returns of any index, we found evidence for long memory properties in the volatility of the HangSeng, the Shanghai Stock Exchange and the Straits Times Index. However, we could not find any sign of long memory in the volatility of Nikkei225 index using either the DFA or modified GPH test. Fractal dimension analysis also demonstrated that all raw index prices have fractal structure properties except for the Nikkei225 index. These findings showed that the Nikkei225 index has the most efficient market properties among these markets. [ABSTRACT FROM AUTHOR]

The article assesses the response of Tehran stock prices to exogenous monetary policy shocks, using a vector error correction model for the 1998Q1–2013Q2 period. Monetary policy is transmitted to stock market price through three routes: money by itself, exchange rate and inflation. Our result in this paper points to the fact that stock prices increase persistently in response to an exogenous easing monetary policy. Variance deposition results show that, after ten periods, the forecast error variance of more than 53 per cent of the Tehran Stock Exchange Price Index (TEPIX) can be explained by the exogenous shocks to the US dollar–Iranian rial exchange rate, while this ratio for exogenous shocks to the Iranian real gross domestic product was only 17 per cent. The article argues that such evidence can be accounted for by an endogenous response of the stock prices to the monetary policy shocks. [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.)

The study investigates the interdependence of Indian Stock Market with other Asian equity markets like Pakistan, Sri Lanka, Malaysia, Korea, Japan, Singapore, Taiwan and China. Study uses monthly data over the period July 1997 to September 2012. By applying Augmented Dickey Fuller Unit Root Test, Johansen Co-integration Test, Granger Causality Test and Vector Error Correction Model (VECM) study find that all Asian stock indices are first difference stationary and long run equilibrium relationship exist among Asian markets. Study uncovers that causality run from stock markets of Sri Lanka, Korea, Singapore and China to India and from India to Pakistan. It also implies that Indian stock market is affected by stock indices of Sri Lanka, Japan, Singapore, and China. Major implication study derives is that Indian government should monitor movements of Asian equity markets very closely, because crisis in any Asian country may affect the performance of Indian stock market. Further robust research can be done by reducing the frequency of data which will be helpful in validating the result of this study. [ABSTRACT FROM AUTHOR]

The most appropriate approach to test for weak-form market efficiency is to examine whether the stock returns are Martingale Difference Sequence (MDS). However, the MDS tests have been largely ignored by previous studies, as the empirical analysis is dominated by Variance Ratio (VR) tests and Independent and Identically Distributed (IID)-based nonlinearity tests. This article re-examines the weak-form efficiency of 14 Asian stock markets using the generalized spectral martingale test. The result shows that all the return series are not MDSs, indicating the presence of return predictability and hence market inefficiency. [ABSTRACT FROM AUTHOR]

Abstract: Stock market integration and volatility spillover between India and its major Asian counterparties is studied. Apart from different degrees of correlations, contemporaneous intraday return spillovers between India and its Asian counterparts are found to be positively significant and bi-directional. Hong Kong, Korea, Singapore and Thailand are found to be four Asian markets from where there is significant flow of information in India. Though most of the information gets transmitted between the markets without much delay, some amount of information still remains unsent and is found to be successfully transmitted as soon as the domestic market opens in the next day. [Copyright &y& Elsevier]

This study re-examines the price behaviour of Asian stock markets in light of the random walk hypothesis. With a new statistical tool, namely the Brock- Dechert-Scheinkman (BDS) test, it is possible for researchers to detect more complex form of dependencies in series of financial returns that often appear completely random to standard statistical tests, such as serial correlation tests, runs test, variance ratio test and unit root tests. Our results suggest that all the returns series in general do not follow a random walk process. This conclusion holds in both sub-periods (pre- and post-crisis) for Bangkok S.E.T. (BSET), Jakarta SE Composite (JSE), Kuala Lumpur SE Composite (KLSE), Korea SE Composite (KSE), and the Philippines SE Composite (PSE). For Hong Kong Hang-Seng (HKHS), the empirical results support our conjecture that the Asian financial crisis in 1997 adversely affected the market's ability to price stocks efficiently, thus preventing stock prices from following a random walk process. In particular, the price behaviour of this market experienced a dramatic change from random walk in the pre-crisis period to non-random during the crisis.

Abstract: This paper investigates the returns to value strategies in four Asian stock markets: Hong Kong, Korea, Singapore and Taiwan. Hong Kong, Korea and Singapore exhibit value premia while Taiwan shows value discounts. The impact of firm characteristics on value premia differs across the four markets. The robustness tests indicate that the value premia are time-varying. They become greater in the post-crisis period across all four countries, indicating that high volatility during the crisis period did understate the value premia. The value strategy''s excess return is sensitive to the sample selection rule and the firm size and liquidity effects. With tighter sample selection criteria, value premia tend to decline, which indicates that both the firm size effect and the liquidity effect are important sources of value premia. Unequal weighting assigned to financial variables in constructing the Average Price Rank (APR) based on the overall performance of single-variable approach does not necessarily improve the results. [Copyright &y& Elsevier]

Abstract: This paper investigates regime-switching behaviour in the return-generating processes of six East Asian emerging stock markets over the period from 1970 to 2004 and examines the specific characteristics of each regime by utilizing Markov-switching variance models. The results show very strong evidence of more than one regime in each of these stock markets. In addition, the conditional probabilities of each regime derived from the model provide mixed evidence regarding the impact of financial liberalization on return volatility. [Copyright &y& Elsevier]

This paper examines autocorrelation and cross-autocorrelation patterns for selected Asian stock returns. Special attention is given to examination of Asian stock returns and the impact on them of the past information. By employing a class of asymmetric specification of conditional mean and conditional variance models, we find the autocorrelation coefficient to be negative for the Japanese market and positive for the rest of the Asian markets studied. Our findings suggest that the Asian markets respond sensitively to the US market, especially on the down side. The asymmetric effects are found to be present in both mean and variance equations. The evidence is consistent with behavior in which investors in Asian markets tend to react more significantly to negative stock news originating from US sources than they do to positive news. [ABSTRACT FROM AUTHOR]

The objective of this study is to analyze the degree of long-term and short-term co-movements in the stock markets of five ASEAN countries and to shed some light on the long-term and short-term market efficiency/inefficiency in the region. We observe a long-run relationship among the stock markets of Indonesia, Malaysia, Singapore, and Thailand, but the Philippine market does not share this relationship. Thus, four cointegrated markets reveal long-term market inefficiency in the region but the Philippine market can be considered efficient. Next, given that the four indices are cointegrated, the number of common cycles are investigated in these markets and each stock index series is decomposed into its trend and cyclical components. The trend–cycle decomposition reveals that in the short-run four ASEAN markets can be categorized into two efficient groups, i.e., Malaysian and Singaporean markets in one group and Indonesian and Thai markets in the other. However, the markets within each group are inefficient. [Copyright &y& Elsevier]