Price and Volatility Transmission across Borders

Abstract

Over the past forty years, financial markets throughout the world have steadily become more open to foreign investors. With open markets, asset prices are determined globally. A vast literature on portfolio choice and asset pricing has evolved to study the importance of global factors as well as local factors as determinants of portfolio choice and of expected returns on risky assets. There is growing evidence that risk premia are increasingly determined globally. An important outcome of this force of globalization is increased comovement in asset prices across markets. This survey study examines the literature on the dynamics of comovements in asset prices and volatility across markets around the world. The literature began in the 1970s in conjunction with early theoretical developments on international asset pricing models, but it blossomed in the late 1980s and early 1990s with the availability of comprehensive international stock market databases and the development of econometric methodology to model these dynamics.

International Equity Correlations, Integration and Contagion

“…A thorough survey of the literature regarding the transmission of prices and volatility between international markets is explored in Gagnon and Karolyi (2006). We briefly review the relevant literature here.…”

“…According to more recent work by Gagnon and Karolyi (2006), these low correlations encouraged institutional investors to allocate increasing amounts of capital into foreign equity markets. Between 1977 and 2008, gross U.S. purchases of foreign stocks have grown from about $200 million to more than $450 billion.…”

Community Analysis of Global Financial Markets

“…Moreover, many studies have analyzed relationships between stock and foreign exchange markets, given the significant increase in global capital flows in the last two decades [24][25][26][27][28][29][30][31][32][33][34][35][36]. Other studies have focused on global stock market return predictability offering diverse findings across different regions and time periods [37][38][39][40][41][42][43][44][45][46][47].…”

An Examination of Price Discovery and Volatility Spillovers of Crude Oil in Globally Linked Commodity Markets

“…These spillovers are usually attributed to the cross-market hedging and changes in commonly available information, which may simultaneously impact the expectations of various participants across markets (Engle, Ito and Lin, 1990). More specifically, volatility spillover examines information assimilation in two different ways: firstly, in terms of own-volatility spillovers under lagged innovations (information) and lagged volatility spillover effects, as it highlights whether lagged information and lagged volatility of an asset traded on an exchange impacts current volatility or not, if this is the case, it is called clustering effects under ARCH framework and volatility persistence under GARCH framework, it has strong implications for market participants as it highlights the assimilation of information other than the information contained in the price (Hong, 2001;Gagnon and Karolyi, 2006;Nekhili and Naeem, 2009). Secondly, cross-volatility spillovers measure spillover of past information and lagged volatility of an asset/market on other asset/market (Gagnon and Karolyi, 2006).…”

“…More specifically, volatility spillover examines information assimilation in two different ways: firstly, in terms of own-volatility spillovers under lagged innovations (information) and lagged volatility spillover effects, as it highlights whether lagged information and lagged volatility of an asset traded on an exchange impacts current volatility or not, if this is the case, it is called clustering effects under ARCH framework and volatility persistence under GARCH framework, it has strong implications for market participants as it highlights the assimilation of information other than the information contained in the price (Hong, 2001;Gagnon and Karolyi, 2006;Nekhili and Naeem, 2009). Secondly, cross-volatility spillovers measure spillover of past information and lagged volatility of an asset/market on other asset/market (Gagnon and Karolyi, 2006). It has also practical implications more importantly than the first one as it helps in characterizing the commodity market as dominant or satellite trading platform (see, Karmakar, 2009;Mahalik, Acharya and Babu, 2010;Du, Yu and Hayes, 2011;Liu and An, 2011;Arouria, Jouini, and Khuong, 2012, among others).…”