The contribution of the study is threefold. First, the paper proposes a new empirically testable definition for a safe haven and a hedge from the viewpoint of extreme and regular dependences measured by a modern statistical tool of copulas. Second, this paper investigates the extreme and regular dependences between the Chinese and the G7 stock markets, using a mixture copula specification, and the results reveal that the Chinese stock market has been not only a hedge but also a safe haven for the G7 stock markets all these years. Finally, this study suggests that the Chinese stock market is the target market for global stock fund managers and international investors, who are seeking a hedge or a safe haven for their portfolios, under turbulence.
Continuing economic reforms and opening-up of China in recent years have stimulated the development of the Chinese financial markets (Chan, Fung, & Thapa, 2007). Meanwhile, the Chinese stock market has grown to one of the most important markets in the world and become integrated over time with foreign stock markets (Laurence et al., 1997 and Xu, 2000). However, the Chinese stock market still appears immune to foreign shocks (Rösch & Schmidbauer, 2008). The low degree of international dependence of the Chinese stock market leads to one interesting question: is the Chinese stock market a good candidate of safe haven or hedge? A safe haven is defined by Kaul and Sapp (2006) as “an ideal venue to park money during periods of uncertainty”, and Baur and Lucey (2009) add that a safe haven is an asset that investors prefer holding when uncertainty increases. In other words, a safe-haven stock market should provide safety against crises and prevent itself from large shocks from another market. Therefore, such a market gives investors larger chance of survival under extreme turbulence. Hence, this study defines a safe haven as a market that is less dependent with the other market and generates low probability of joint crash, given the other collapses. That probability is known as extreme dependence or conditional probability of contagion, defined by Costinot, Roncalli, and Teiletche (2000). If the Chinese stock market is a safe haven, we expect low and insignificant extreme dependence between the Chinese and the other stock markets.
Moreover, a hedge, a related concept to a safe haven, defined as that a market does not co-move with another on average ( Baur & Lucey, 2009), is also investigated. The study interprets the term “co-movement on average” as “regular dependence”, defined as the dependence between markets in regular market condition. In the study, regular dependence is measured by correlation coefficients, which is the expectation of standardized co-movement. If the Chinese stock market serves as a hedge, it should have low and insignificant regular dependence.
From the definitions of a safe haven and a hedge, a market which is a hedge does not necessarily imply a safe haven, and vice versa. To investigate whether the Chinese stock market serves as a safe haven or a hedge (or both), the study estimates extreme and regular dependences simultaneously from a mixture copula composed of a Clayton copula and a Normal copula, where the former captures the pattern that markets collapse together and the latter contains correlation coefficient for measuring regular dependence and exhibits no extreme dependence.
The contribution of the study is threefold. First, the paper proposes a new empirically testable definition for a safe haven and a hedge from the viewpoint of extreme and regular dependences measured by a modern statistical tool of copulas. Second, since the Chinese stock market is one of the largest emerging markets in the world, though imperfect, incomplete and highly regulated by government (Chan et al., 2007), the results provide interesting insights regarding the role of the Chinese stock market in the world. Third, a safe haven is especially essential to asset allocation of global stock funds, which hold large position of stocks from markets all over the world. This study sheds lights for stock fund managers and global investors on seeking safe-haven markets under turbulence. The structure of the paper is as follows. Section 2 discusses the specification of the mixture copula and the estimation for extreme and regular dependence; Section 3 presents data description and empirical results; finally Section 4 discusses and concludes.
This paper provides a new empirically testable definition for a safe haven and a hedge using extreme and regular dependences. We investigate the Chinese and the G7 stock markets using a mixture copula specification and test whether a market is a hedge or a safe haven (or both) in two sub-sample periods. The results show strong extreme and regular dependences between the G7 markets, implying high interaction under turbulence and regular market condition. Moreover, Japanese stock market is a safe haven for Canada, France and the U.S. in Period 1 and for Germany and the U.S. in Period 2. Italian stock market serves as a hedge for Japan and a safe haven for the U.S. in Period 1. Interestingly, the Chinese stock market is evidenced as a safe haven and a hedge for the G7 stock markets in both periods. Since seeking a hedge or safe-haven market is essential to asset allocation of global stock funds and international investors, the results suggest that the Chinese stock market is a good candidate of a hedge in regular market condition and a safe haven under turbulence in global stock markets.
