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The purpose of this paper is to assess the sources of Dubai Financial Market Index volatility shocks if they are from its own or previous shocks on the one hand, or if they are out board shocks (FSTE and S&P500) on the other.

A daily time series data were collected over the period 1st January 2014-31st December 2015 and the generalized autoregressive conditional heteroskedasticity (GARCH) methodology was implemented.

Empirically, the authors find that the current volatility of Dubai Financial Market Index is largely dependent on its own shocks and part of the external shock; in particular, S&P500. However, other external volatility (FSTE) cannot contribute to this volatility. Furthermore, our findings indicate that Abu Dhabi stock Exchange (APX) affects Dubai Financial Market Index.

These results conclude that Securities Regulation Department in the federal state of United Arab Emirates had captured the effect of outside shocks from the UK only, but not from USA; this is basically due to the strong ties between the two countries. Accordingly, UAE investors seek capital outside their home country within a climate of increasing overseas’ investment options in the UK. More transparency of transactions via information technology will increase the efficiency of Dubai Financial Market.

To the best of the knowledge, this is the first work that shows the external and internal sources of volatility shocks at once; previous studies have focused almost exclusively on one type of shocks. To investigate DFM volatility shocks, the authors employed GARCH methodology; this method is an advanced econometric method and is often a preferred method to depict actual effects because it provides a more real-world context than other forms when trying to predict volatility shocks of financial instruments.

The purpose of this paper is to examine the inter-relations among the US stock indices.

Data of nine US stock indices spanning a period of sixteen years (2000-2015) are employed for this purpose. Asymmetries are examined via an error correction model. Non-linear inter-relations are researched via Breitung’s nonlinear cointegration, a M-G nonlinear causality model, shocks to the forecast error variance, a shock spillover index and an asymmetric VAR-GARCH (VAR-ABEKK) approach.

The inter-relations are significant. The results are robust across all types of inter-relations. They are highest in the Lehman Brothers sub-period. Higher stability after the EU debt crisis, enhances independence and growth for the US stock indices.

To the best of the knowledge, this is the first study to examine the inter-relations of US stock indices. Most studies on inter-relations concentrate on the portfolio analysis to reveal diversification benefits among various asset markets internationally. Hence this study contributes to this literature on the inter-relations of a specific asset market (stock), and in a specific nation (USA). The evident inter-relations support the notion of diversification benefits in the US stock markets.

Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.

The purpose of this paper is to investigate whether the crude oil volatility index (OVX) plays any key role in explaining the trend in emerging market stock returns from a global standpoint.

At the empirical stage, different forms of the GARCH-jump model have been estimated.

The findings confirm the effects of OVX on equity returns. In addition, the results document that there exist time-varying jumps in the stock market returns. Besides, the impacts of OVX shocks appear to be symmetric. The analysis further shows that the magnitude of OVX impact is marginally bigger than that of the conventional oil price shocks.

Since various financial assets are traded on the basis of oil and equity markets, investors, for instance, could use the findings of this study for taking proper investment decisions and gaining better portfolio diversification benefits. Additionally, policymakers could utilize the results to develop effective measures and strategies in order to minimize the oil price risk.

This study aims to investigate the impact of the COVID-19 pandemic on both of stock prices and investor's sentiment in China during the onset of the COVID-19 crisis.

In this study, the ADCC-GARCH model was used to analyze the asymmetric volatility and the time-varying conditional correlation among the Chinese stock market, the investors' sentiment and its variation. The authors relied on Diebold and Yilmaz (2012, 2014) methodology to construct network-associated measures. Then, the wavelet coherence model was applied to explore the co-movements between these variables. To check the robustness of the study results, the authors referred to the RavenPack COVID sentiments and the Chinese VIX, as other measures of the investor's sentiment using daily data from December 2019 to December 2021.

Using the ADCC-GARCH model, a strong co-movement was found between the investor's sentiment and the Shanghai index returns during the COVID-19 pandemic. The study results provide a significant peak of connectivity between the investor's sentiment and the Chinese stock market return during the 2015–2016 and the end of 2019–2020 turmoil periods. These periods coincide, respectively, with the 2015 Chinese economy recession and the COVID-19 pandemic outbreak. Furthermore, the wavelet coherence analysis confirms the ADCC results, which revealed that the used proxies of the investor's sentiment can detect the Chinese investors' behavior especially during the health crisis.

This study provides two main types of implications: on the one hand, for investors since it helps them to understand the economic outlook and accordingly design their portfolio strategy and allocate decisions to optimize their portfolios. On the other hand, for portfolios managers, who should pay attention to the volatility spillovers between investor sentiment and the Chinese stock market to predict the financial market dynamics during crises periods and hedge their portfolios.

This study attempted to examine the time-varying interactions between the investor's sentiment proxies and the stock market dynamics. Findings showed that the investor's sentiment is considered a prominent channel of shock spillovers during the COVID-19 crisis, which typically confirms the behavioral contagion theory.

The main objective of this paper is to investigate whether the investors' behavior under optimistic (pessimistic) conditions has an impact on risk transmission between the Chinese stock and bond markets and the sector indices mainly during the COVID-19 pandemic.

This study uses a new measure of the investor's sentiment based on Google trend to construct a Chinese investor's sentiment index and a quantile causal approach to examine the causal relationship between googling investor's sentiment and the Chinese stock and bond markets as well as the sector indices. On the other hand, the network connectedness is used to estimate the spillover effect on the investor's sentiment and index returns. To check the robustness of the study results, the authors employed the Chinese VIX, as another measure of the investor's sentiment using daily data from May 2019 to December 2020.

In fact, the authors found a dual causality between the investor's sentiment and the financial market indices in optimistic or pessimistic situations, which indicates that positive and negative financial market returns may have an effect on the Chinese investor's sentiment. In addition, the results indicated that a pessimistic investor's sentiment has a negative impact on the banking, healthcare and utility sectors. In fact, the study results provide a significant peak of connectivity between the investor's sentiment, the stock market and the sector indices during the 2015–2016 and 2019–2020 turmoil periods that coincide respectively with the 2015 recession of the Chinese economy and the COVID-19 pandemic.

This finding suggests that the Chinese googling investor's sentiment is considered as a prominent channel of shock spillovers during the coronavirus crisis, which confirms the behavioral contagion. This study also identifies the contribution of a particular interest for portfolio managers and investors, which helps them to accordingly design their portfolio strategy.

This chapter examines the impact of price fluctuations in foreign stock markets on the stock prices of domestic banks in Korea, Malaysia, Singapore, and Thailand. Some studies have argued that the 2007–2009 global financial crisis (GFC) affected domestic banks less in East Asia, even though the supporting evidence is rather limited. Employing a multinomial logit model, we estimate how changes in the United States and Japanese stock markets affected the banking sectors in the sampled countries before the 1997 Asian financial crisis, and before and during the more recent GFC. We interpret the number of banks in a given country that experienced a large price shock on the same day (or “coexceedance”) as shocks to the domestic banking sector. The results suggest that fluctuations in foreign stock market indices exerted a larger impact on the prices of East Asian banking stocks during the 2000s than during the 1990s. In addition, although the shocks brought about by the deterioration of foreign stock markets were significant before the GFC, both increases and decreases in foreign stock prices significantly affected the banking sectors of the respective countries during the crisis. Lastly, we conclude that increasing foreign capital flows and foreign assets and liabilities greatly influenced domestic banking systems in East Asia during the 2000s.

This paper investigates the static and dynamic directional return spillovers and dependence among green investments, carbon markets, financial markets and commodity markets from January 2013 to September 2020.

This study employed both the quantile vector autoregression (QVAR) and time-varying parameter VAR (TVP-VAR) technique to examine the magnitude of static and dynamic directional spillovers and dependence of markets.

Results show that the magnitude of connectedness is extremely higher at quantile levels (q = 0.05 and q = 0.95) compared to those in the mean of the conditional distribution. This connotes that connectedness between green bonds and other assets increases with shock size for both negative and positive shocks. This further indicates that return shocks spread at a higher magnitude during extreme market conditions relative to normal periods. Additional analyses show the behavior of return transmission between green bond and other assets is asymmetric.

The findings of this study offer significant implications for portfolio investors, policymakers, regulatory authorities and investment community in terms of carefully assessing the unique characteristics offered by each markets in terms of return spillovers and dependence and diversifying the portfolios.

The study, first, uses a relatively new statistical technique, the QVAR advanced by Ando et al. (2018), to capture upper and lower tails’ quantile price connectedness and directional spillover. Therefore, the results possess adequate power against departure from mean-based conditional connectedness. Second, using a portfolio of green investments, carbon markets, financial markets and commodity markets, the uniqueness of this study lies in the examination of the static and dynamic dependence of the markets examined.

Several studies focus on asymmetric impact of shocks on conventional stocks. However, only few studies explore Islamic stocks, but none has examined the asymmetric impact of shocks on Islamic stocks. This study aims to fill the gap by investigating the asymmetric impact of shocks on Islamic stocks. Specifically, it identifies the effect of good and bad news on Islamic stock market. The study also aims to examine the returns and volatility spillover effects across different Islamic markets.

To carry out the empirical analysis, the authors have applied the exponential generalized autoregressive conditional heteroscedasticity (ARCH) model on daily Islamic stock indices of 18 countries. The study covers the period from July 2009 to July 2016. The authors have started their empirical analysis by examining the time series properties and testing the presence of ARCH effects. Further, the authors have applied several post-estimation tests to ensure the robustness of the results.

The results indicate that there is significant leverage effect in Islamic stocks traded in the sampled countries. That is, negative shocks or bad news have stronger effects on Islamic stock returns’ volatility as compared to positive shocks or good news. The authors also found that there are significant mean spillover effects for the examined countries. This finding implies that increased Islamic stock returns in country have significant and positive effects in Islamic stocks’ returns in another other. Similarly, the results regarding the volatility spillover effects suggest that there are significant volatility spillover effects across all examined countries. However, the authors found both positive and negative volatility spillover effects. It should also be noted that in some cases, the authors did not find any significant volatility spillover effect.

The findings of this study have several important policy implications for both investors and policymakers. As the findings suggest that Islamic stock indices are integrated across countries both in terms of returns (mean) and risk (volatility), they are useful for investors to design well-diversified portfolios. The significant volatility spillovers suggest policymakers to design such policy that may help in reducing the adverse effects of increased volatility of Islamic stock of other/foreign countries on the Islamic stocks of the home countries. The significant evidence of the presence of leverage (asymmetric) effects suggest investors to use effective and active hedging instruments to hedge risk, particularly, in bad times.

Unlike other studies on Islamic stocks, this study takes into account the asymmetric effects of positive and negative shocks. Further, the study examines the mean and variance spillover effects for a large panel of countries having Islamic stocks. Finally, several pre- and post-estimation tests are applied to ensure the robustness of the results.

By reinforcing monetary policy independence, reducing international financing pressures and avoiding high-risk takings, capital controls strengthen the stability of the financial system and then reduce the volatility of capital inflows. The objective of this study was to conduct an empirical examination of this hypothesis. This topic has received strong support in the theoretical literature; however, empirical work has been quite limited, with few empirical studies that provide direct empirical support to this hypothesis.

This study analyzed quarterly data of 32 emerging economies over the period between 2000 and 2015 and proposes two methods to identify capital control actions. Using panel analysis, Autoregressive Distributed Lag and local projections approaches.

This study found that tighter capital controls may diminish monetary and exchange rate shocks and reduce capital inflows volatility. Furthermore, capital controls respond counter-cyclically to monetary shocks. Under capital controls, countries with floating exchange rate regimes have more potential to buffer monetary shocks. We also found that capital controls on inflows are more effective for reducing the volatility of capital inflows compared to capital controls on outflows.

This study contributes to the question of the effectiveness of capital controls in attenuating the effects of international shocks and reducing the volatility of capital flows. Previous studies have mostly focused on the role of macroprudential regulation; however, there is a lack of systematic effects of capital controls on monetary and exchange rate policies. To our knowledge, this is the first preliminary study to suggest that capital controls may buffer monetary and exchange rate shocks and reduce the volatility of capital inflows. This study investigates the novel notion that capital controls allow for a notable counter-cyclical response of monetary and exchange rate policies to international financial shocks.