Cross-market hedge

To our knowledge, the correlation between markets in Asia is proved by several studies. Solnik (1996) studies the correlation between Asia stock markets and between

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Asia bond markets to indicate that international correlation increase in the periods of high market volatility and strongly affected by national factors. Studying for crisis, Masih and Masih (1997) present the fact that the correlation of the international markets revealed obviously after the crash of the New York Stock Exchange in 1987, the financial crisis in Mexico in 1994 and the Asian Financial Storm from 1997 to 1998. Baig and Goldfajn (1999) also show the significant correlation among Asia stock, currency, and bond markets.

Chiang, Jeon and Li (2007) investigate the stock market contagion in eight Asian countries and the US as well. The results show significant contagion effects that the correlations for any pairs of countries increase after Asian crisis. According to the results, the gain from international diversification by holding a portfolio consisting of diverse stocks from these contagion countries declines since these stock markets are commonly exposed to systematic risk. Also, this study suggests that both investors and international rating agents play significant roles in shaping the structure of dynamic correlations in the Asia markets.

Moreover, in recent studies, the cross-market credit correlation is studied for construction of portfolios and international investment. The literatures suggest that the credit correlation exists under certain situations and has some characteristics. For example, firms in the same industry (region) often have higher default correlations

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than those in different industries (regions). Zhou (2001) develops a model to calculate default correlation and joint default probability of two firms to calculate the probability of a two-dimensional stochastic process passing a boundary. The model theoretically implies that the high credit quality implies a low default correlation which is consistent with the well-known empirical feature regarding the relation

between default correlation and credit ratings. Also, the default correlation and the asset level correlation are positive related. That’s why firms in the same industry

(region) often have higher default correlations than those in different industries (regions). Also, because the time of peak default correlation depends on the credit quality of the underlying firms which is time-varying, the default correlation is dynamic. Loffler (2003) estimates default correlation based on the joint distribution of assets values and shows similar results.

The Latin American and Asian countries credit correlation is worth focusing on because those emerging countries are more risky than developed countries. Cowan and Cowan (2004) suggest that it is more worthwhile to focus on the lower grade portfolios which are sensitive to changes in default correlations. Furthermore, the magnitude of default correlation increases as the internally assigned risk grade declines. They study the credit correlation of subprime lenders under loan portfolio, because this kind of portfolio carries greater risk of default and therefore compensates

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lenders with higher credit spread.

To figure out factors related to credit quality, Weigel and Gemmill (2006) have extracted the distance-to-default implied by bond prices, for Argentina, Brazil, Mexico and Venezuela, to investigate the impact of global, regional and country-specific factors on creditworthiness. Overall, the results show that global and regional factors are far more important than country-specific factors in determining changes in creditworthiness for these four emerging-market countries. It also considers the S&P 500 volatility as a proxy for global market uncertainty. The results indicate that it is positive and significant for credit quality, which is consistent with the modeling of credit spreads. It indicates that the dependence of emerging markets on industrial countries increase because of globalization.

Actually, the cross-market hedge is also related to the uncertainty. Chordia, Sarkar and Subrahmanyam (2001) explore both trading volume and spreads in the stock and bond markets respectively from June 1991 to December 1998 to find the evidence consistent with linkage between dynamic cross-market hedging and uncertainty. They ponder over the Asian crisis in 1997 and the Russian default crisis in 1998, and the results suggest that greater market uncertainty during the crisis periods leads to an dramatical changes in correlation between stock and bond spread and volume relevant to normal times, and linkages between stock and bond market liquidity are

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significantly stronger in the crisis periods. Thus, the uncertainty of financial market is a critical factor while we consider market correlation.

Connolly, Stivers and Sun (2005) study whether stock-government bond return relation in nine European countries from 1992 to 2002 varies due to the influence of stock market uncertainty which is measured by equity implied volatility. The stock

market uncertainty is measured by the implied volatility from equity index options, specifically the Chicago Board Options Exchange’s Volatility Index (VIX). The

results indicate bond returns tend to be high during days when implied volatility increases. They also find a negative relation between the uncertainty measures and the future correlation of stock and bond returns that the correlation of daily stock and bond returns swing from significantly positive in low uncertainty periods to significantly negative in high uncertainty periods in most countries. This study presents additional evidence supporting these stock market uncertainty effects may stem from cross-market rebalancing. When considering cross-market pricing influences, variation in stock market uncertainty (as measured by stock volatility) is likely to be more important than variation in bond market volatility.

According to the articles mentioned above, the contagion is significant for financial markets and regions as well as the credit correlation. Because equity implied volatility can be determinant of credit spreads as well as the measurement of influence of

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market uncertainty which has an impact on cross-market hedge, it is taken as an exogenous variable while we explain the variation of credit correlations. The US stock market volatility is adapted because of dependence of emerging markets on industrial countries increasing due to globalization. Therefore, our study of credit contagion of Asia countries will take credit spread of sovereign debts as the measurement of credit quality and VIX as the uncertainty of world financial markets.

However, the credit spread analysis is lack of time-varying. Our study applies an appropriate model to improve estimation.