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This chapter investigates the correlation dynamics in the equity markets of 13 Asia-Pacific countries, Europe and the US using the asymmetric dynamic conditional correlation GARCH model (AG-DCC-GARCH) introduced by Cappiello, Engle, and Sheppard (2006). We find significant variation in correlation between markets through time. Stocks exhibit asymmetries in conditional correlations in addition to conditional volatility. Yet asymmetry is less apparent in less integrated markets. The Asian crisis acts as a structural break, with correlations increasing markedly between crisis countries during this period though the bear market in the early 2000s is a more significant event for correlations with developed markets. Our findings also provide further evidence consistent with increasing global market integration. The documented asymmetries and correlation dynamics have important implications for international portfolio diversification and asset allocation.

In recent decades, interconnections between countries have increased substantially worldwide as the process of integration and globalisation intensifies, with a positive impact in terms of economic development, but, also with a vulnerability to external shocks, such as the financial contagion phenomenon. The analysis of this research field becomes even more relevant in the context of a new major exogenous shock, but which, this time, has different specificities, being a sanitary crisis. Thus, the chapter aims to investigate the impact of crises on capital market volatility for the period of 1995–2021, using the bibliometric analysis highlighting the dynamics of the literature and potential future research directions through a science mapping that enables investigating scientific knowledge. In order to explore the development of the research field in terms of publications, author impact, affiliated institutions and countries, citation patterns, trending topics, relationship between keywords–authors–journals, abstracts’ analysis, authors and documents clustering by coupling, multiple correspondence analysis of major research themes, keyword analysis, co-citation analysis and authors, institutions and countries collaboration analysis have been applied. Hence, almost 500 publications from Web of Science database covering the period 1995–2021 have been extracted. The empirical findings emphasise the conceptual structure, with clusters focussing mainly on long-term receivables, market efficiency, volatility, dynamic conditional correlation (DCC)-GARCH models, asymmetric effects. According to the intellectual structure of the field, Lambertides N., Zopiatis A., McAleer M. or Savva C. S. are the most representative authors for the sub-area of volatility topic; whilst Balcerzak A. P., Pietrzak M. B., Zinecker M., Meluzin T. and Faldzinski M. are the reference names for the whole spectrum of DCC-GARCH models’ topic. Jayasekera R., Lundblad C., Choundhry T., Gupta R. and Demirer R. are the authors mostly associated with asymmetric effects’ topic, whilst Thorp S., Bouchaud J. P. and Dungey M. with the quantitative finance. The Journal of Banking & Finance, the Journal of International Money and Finance and the International Review of Financial Analysis as well as Economic Modelling, Research in International Business and Finance and the International Journal of Finance & Economics are the most prolific journals in the field of capital flow and financial crises. This chapter’s main contribution is to build a structure of knowledge for the impact of crises on capital market volatility, elaborate and classify empirical research into relevant dimensions that can be used as a reference for comprehensively developing research. Finally, the bibliometric analysis results may provide insight into future research prospects. Our conclusions offer some recommendations for market practitioners and policy-making.

The ratio between share price and current earnings per share, the Price Earning (PE) ratio, is widely considered to be an effective gauge of under/overvaluation of a corporation’s stock. Arguably, a more reliable indicator, the Cyclically Adjusted Price Earning ratio or CAPE, can be obtained by replacing current earnings with a measure of permanent earnings i.e. the profits that a corporation is able to earn, on average, over the medium to long run. In this study, we aim to understand the cross-sectional aspects of the dynamics of the valuation metrics across global stock markets including both developed and emerging markets. We use a time varying DCC model to exploit the dynamics in correlations, by introducing the notion of value spread between CAPE and the respective Market Index from 2002 to 2014 for 34 countries. Value spread is statistically significant during the 2008 crisis for asset allocation. The signal can be utilized for better asset allocation as it allows one to interpret the common movements in the stock market for under/overvaluation trends. These estimates clearly indicate periods of misvaluation in our sample. Furthermore, our simulations suggest that the model can provide early warning signs for asset mispricing in real time on a global scale and formation of asset bubbles.

After the collapse of communist and socialist regimes at the beginning of 1990s, a number of Central and Eastern European (CEE) economies started their journey into capitalism by establishing private property and capital markets. As a result, a number of stock markets have since been established in the region. Since then, they have displayed considerable growth in size and degree of sophistication, and they have attracted the interest of academics for a number of reasons. First, these markets provide a possibility to re-examine existing asset-pricing models and pricing anomalies in the conditions of the evolving markets. Market efficiency of the CEE markets is tested in Ratkovicova (1999) and Gilmore and McManus (2001); a version of the CAPM is tested in Charemza and Majerowska (2000); Mateus (2004) explores the predictability of European emerging market returns within an unconditional asset-pricing framework while the January-pricing anomaly is studied in Henke (2003). Second, in the light of growing interdependencies between world equity markets due to enhanced capital movements, numerous studies have investigated the extent to which emerging European stock markets are integrated with global markets, and the extent to which they are subjects to global shocks (Gelos & Sahay, 2000; Gilmore & McManus, 2002; Scheicher, 2001). Among the CEE markets, those of the Vysegrad countries (Poland, Hungary and the Czech Republic) have attracted most of the attention of the academics due to their economies faster growth relative to their regional counterparts (Slovakia, Slovenia, Bulgaria, Croatia and Baltic countries), in addition to political stability and their (successfully realized) prospects of joining the European Union (EU).

In this paper, we search to evaluate the systemic risk of the Moroccan banking sector. Indeed, we concentrate on the analysis and the evaluation on transverse dimension of the systemic. From this point of view, two approaches were used. First is based on the estimate on value at risk conditional allowing to measure the systemic importance of each banking institution. In addition, the second approach uses the heteroscedasticity models in order to consider the conditional correlations, making it possible, to measure the dependence between the Moroccan banks and with the whole of the financial system. The results obtained with through these two approaches confirm that ATW, BMCI and the BMCE are the most systemic banks in Moroccan banking system and who can initiate a systemic crisis. On another register and by using the conditional correlations of each bank we built an index of systemic risk. Moreover, a macrofinancial model was developed, connecting the index of the systemic risk and the principal macroeconomic variables. This model affirmed that the contagion dimension of systemic risk is procyclical.

The opening up of B-share markets to domestic investors in 2001 is a landmark event in the development of the Chinese stock markets. This chapter aims to assess the possible changes in the market mechanism associated with this important event. A VECM-DCC-MVGARCH model is employed to investigate the market integration process in Chinese stock markets around the opening up of the B-share market to domestic investors. Our empirical results reveal that the Chinese stock markets were segmented before the opening up whereas they were integrated to some extent in the long-run after the opening up of B-share markets. Moreover, it is also found that A-share markets played a dominant role on the information flows between A-share and B-share markets; the short-run information flows between A-share and B-share markets were more rapid after the opening up of B-share markets.

Introduction – Increases in prices of commodity markets may be associated with increased volatility in financial markets. That is why analysing time-varying co-movements of commodity prices can be of great importance for investors who take into consideration optimal asset allocation.

Purpose – The aim of this study is to investigate the volatility spillover from oil to precious metals under high-volatility and low-volatility regimes.

Methodology – The data covered daily closing prices of assets such as oil, palladium, and platinum for the period January 2010–December 2018. GARCH models were analysed in order to determine the most appropriate volatility structure, and it was determined that GARCH (1,1) model was the most suitable model for all commodities. Markov Switching model was used to analyse the volatility spillover from oil to precious metals.

Findings – According to the analyses, the results showed that there were volatility spillovers from oil to palladium and platinum in low-volatility regimes and from oil to platinum in high-volatility regimes. On the other hand, there was no volatility spillover from oil to palladium in high-volatility regimes. Investing into oil and palladium in the same portfolio can provide diversification benefits for investors in high-volatility regimes. On the other hand, investing into oil and palladium in the same portfolio may not provide diversification benefits for investors in low-volatility regimes. The findings of the analyses can be beneficial for investors, market participants, and portfolio managers to make an accurate portfolio management.