اثر سرریز جهانی و منطقه ای در بازارهای سهام در حال ظهور: آنالیز GARCH چند متغیره

This paper examines global (mature market) and regional (emerging market) spillovers in local emerging stock markets. Tri-variate VAR-GARCH(1,1)-in-mean models are estimated for 41 emerging market economies (EMEs) in Asia, Europe, Latin America, and the Middle East. The models capture a range of possible transmission channels: spillovers in mean returns, volatility, and cross-market GARCH-in-mean effects. Hypotheses about the importance of different channels are tested. The results suggest that spillovers from regional and global markets are present in the vast majority of EMEs. However, the nature of cross-market linkages varies across countries and regions. While spillovers in mean returns dominate in emerging Asia and Latin America, spillovers in variance appear to play a key role in emerging Europe. There is also some evidence of cross-market GARCH-in-mean effects. The relative importance of regional and global spillovers varies too, with global spillovers dominating in Asia, and regional spillovers in Latin America and the Middle East.

The empirical finance literature abounds with studies of cross-border links in stock market returns. This is not surprising. Empirical modelling of such links is relevant for trading and hedging strategies and provides insights into the transmission of shocks (news) across markets. Informed by standard asset pricing models and supported by advances in the econometric modelling of volatility, research in the past two decades has focused on interdependencies in terms of both first and second moments of return distributions. Early studies of spillovers across national stock markets primarily covered advanced countries. Prompted by the October 1987 stock market crash in the US, Hamao et al., 1990, King and Wadhwani, 1990 and Schwert, 1990 examined spillovers across major markets before and after the crash. Subsequent research refined and expanded the analysis of advanced market links by examining spillovers in high frequency (e.g., hourly) data (Susmel and Engle, 1990); asymmetry in the transmission of positive and negative shocks (Bae and Karolyi, 1994; Koutmos and Booth, 1995); differences in the transmission of global and local shocks (Lin et al., 1994), and interactions among larger sets of advanced markets (Theodossiou and Lee, 1993 and Fratzscher, 2002). Research into cross-border links in emerging stock markets was boosted by the growth and increasing openness of these markets, as well as the speed and virulence with which past financial crises in emerging market economies (EMEs) spread to other countries. Bekaert and Harvey, 1995, Bekaert and Harvey, 1997, Bekaert and Harvey, 2000 and Bekaert et al., 2005 analyse the implications of growing integration with global markets for local returns, volatility, and cross-country correlations, covering a diverse set of EMEs in Africa, Asia, Latin America, and the Mediterranean. Most other studies of EME stock markets focus on specific regions. Scheicher, 2001, Chelley-Steely, 2005 and Yang et al., 2006 examine extent and effects of stock market integration in Central and Eastern Europe, both within the region and with advanced markets, while Chen et al. (2002) look at evidence of regional linkages among Latin American stock markets. Floros (2008) focuses on the Middle East, while Ng, 2000, Tay and Zhu, 2000, Worthington and Higgs, 2004, Caporale et al., 2005, Caporale et al., 2006, Engle et al., 2008 and Li and Rose, 2008 examine stock markets in emerging Asia. These studies generally point to increasing links among emerging stock markets, and between these markets and mature markets. However, results are difficult to compare across countries because they are based on different methodologies, time periods, and data frequencies. This paper seeks to remedy this problem by applying a uniform specification to a large set of EMEs — 41 in all — spanning four regions: Asia, emerging Europe, the Middle East and North Africa, and Latin America. A downside of this approach is that, given the large number of countries in each region, we cannot model simultaneously the links among all local markets, and between these markets and major mature markets. We focus on links between local emerging markets and aggregate global and regional markets as we are interested in the impact of the latter on the former. The paper relies on a broad model framework that encompasses several channels through which news in global and regional markets may influence local emerging markets. More specifically, we apply a tri-variate VAR-GARCH-in-mean framework with the BEKK representation proposed by Engle and Kroner (1995) to model and test for cross-market spillovers in means and variances of stock returns as well as own and cross-market spillovers from second to first moments (GARCH-in-mean effects). This approach builds upon and expands existing studies such as Hamao et al., 1990, Ng, 2000, Bekaert et al., 2005 and Beirne et al., 2009. The use of a GARCH-in-mean specification enables us to estimate cross-market spillovers from second to first moments. This is a key contribution of the present study, which differentiates it from the earlier one by Beirne et al. (2009) and other related papers. The global market in each tri-variate model is a GDP-weighted average of the US, Japan, and Europe (Germany, France, Italy, and the UK),2 and the regional market is a weighted average of all emerging markets in the region included in our country sample, except for the model's local market.3 Our analysis is based on weekly stock returns in local currency. Time series end in mid-March 2008 and start in 1993 for emerging Asia, and in 1996 for Latin America, most markets in emerging Europe, South Africa, the Middle East and North Africa. We use Wald tests to examine several hypotheses about spillovers in means and variances, as well as GARCH-in-mean effects, from global and regional markets to local markets. The results suggest that spillovers from regional and global markets are present in the vast majority of EMEs. However, the nature of cross-market linkages varies across countries and regions. While spillovers in mean returns dominate in emerging Asia and Latin America, spillovers in variance appear to play a key role in emerging Europe. There is also some evidence of cross-market GARCH-in-mean effects. The relative importance of regional and global spillovers varies too, with global spillovers dominating in Asia, and regional spillovers in Latin America and the Middle East. The paper is organised as follows. Section 2 describes the econometric model. Section 3 provides details on the data set and outlines the hypotheses tested. Section 4 discusses the results; and Section 5 offers some concluding remarks.

The main objective of this study was to examine regional and global spillovers in emerging stock markets using a uniform model for a large set of EMEs to facilitate cross-country comparisons. A tri-variate VAR-GARCH(1,1)-in-mean model was chosen to capture a broad range of possible spillover channels in means and variances. We carried out a series of Wald tests involving restrictions on various spillover parameters to analyse the importance of different transmission channels. Starting with a benchmark case that rules out any spillovers from regional or global stock markets to local emerging markets, we found that such spillovers are present in the vast majority of EMEs. The benchmark restrictions are rejected for all but a few countries in our sample. However, the nature of cross-market linkages varies across countries and regions. While spillovers in mean returns dominate in emerging Asia and Latin America, spillovers in variance appear to play a key role in emerging Europe. The relative importance of regional and global spillovers varies too, with global spillovers dominating in Asia, and regional spillovers in Latin America and the Middle East. We find evidence of cross-market GARCH-in-mean effects for half of the EMEs considered in Asia, Europe, the Middle East and North Africa. This is a particularly interesting finding, suggesting that stock market returns are affected by their volatility (risk). In other words, they are responsive to stock market turbulence, implying that international financial investors should be concerned with the linkage between returns and volatility in EMEs markets when forming their expectations and consequently their investment strategies. Our results offer a first stab at a comprehensive comparative analysis of cross-market linkages in emerging stock markets. Further research is no doubt needed. An important question is whether transmission channels and the relative importance of regional and global spillovers have changed over time, in particular in the run-up to, and course of, the present crisis.