توضیح روابط بین المللی سهام با نوسانات شاخص بهای مصرف کننده و نوسانات بازار
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|19332||2009||10 صفحه PDF||سفارش دهید||7187 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Banking & Finance, Volume 33, Issue 11, November 2009, Pages 2026–2035
This paper investigates the dynamic correlations among six international stock market indices and their relationship to inflation fluctuation and market volatility. The current research uses a newly developed time series model, the Double Smooth Transition Conditional Correlation with Conditional Auto Regressive Range (DSTCC-CARR) model. Findings reveal that international stock correlations are significantly time-varying and the evolution among them is related to cyclical fluctuations of inflation rates and stock volatility. The higher/lower correlations emerge between countries when both countries experience a contractionary/expansionary phase or higher/lower volatilities.
International stock market correlations have attracted more attention with the integration and globalization of financial markets. A wealth of qualitative literatures devoted to the intriguing connection between financial markets and economic fundamentals provide sufficient evidences that co-movement of business-cycle fluctuations impact international financial market correlations. However, the controversy continues. Debates on whether economic fundamentals such as business cycle indicators significantly affect international financial correlations, surfaced in the early 1990s, and have not yet reached a consistent agreement. Erb et al. (1994) found that correlations between two equity markets vary according to both countries’ economic cycles that economic fundamentals significantly affect stock market correlations. They show that among the G-7 countries, the highest correlations appear when both countries stand in the contractionary phase and lowest correlations appear when both countries are in the expansionary phase. Correlations vary between these two extreme states when they are out of phases. Dumas et al. (2003) highlighted the statistical evidence that output correlations and stock market correlations are positively related. Forbes and Chinn (2004) showed that direct trade is the predominant factor of the world’s largest markets that affect financial markets. Yang et al. (2009) investigated dynamic interdependence between international stock and bond markets affected by real economy (represented as the business cycle, the inflation environment and monetary policy stance). Furthermore, they supplied evidence that higher stock-bond correlation coincides with higher short rates and higher inflation rates. On the contrary, other literatures maintain skeptic upon such association between real economic linkages and financial-market linkages. King et al. (1994) suggested that co-variances between international stock markets are difficult to interpret by observable economic variables, and can reverse by unobservable variables. Ammer and Mei (1996) discovered that contemporaneous co-movement in macroeconomic variables influence co-variances between international stock markets. However, they ignore this relationship because the real linkages are much stronger in the long-run than a short-run perspective. Kizys and Pierdzioch (2006) supported Ammer and Mei, showing that the linkage between monthly conditional international equity correlations and co-movement of business-cycle fluctuations is not significant enough. Recent researches have also focused on the linkages between international stock correlations and market volatility. Longin and Solnik (2001) found that correlation increased in bear markets, but not in bull markets and international integration tightens the financial linkage progressively. Connolly et al. (2007) offered plentiful evidence that international stock linkages are likely higher/lower when the level of implied volatility (as a measure of stock uncertainty) stays higher and its variation is larger. Aydemir (2008) indicated that the higher the risk aversion periods, the higher the tendency for market correlations and high market volatility to emerge at the same time. Besides, Ferreira and Gama (2007) showed that sovereign debt ratings news tends to increase the international stock market correlations. Another literature focuses on the factors explaining the stock-bond correlations. For example, see Kim et al., 2006, Li and Zou, 2008 and Panchenko and Wu, 2009. Motivated by earlier conflicting reports, this research restudies the relationship between economic fundamentals as well as global stock volatility and international stock market interdependence. The current work employs a range-based multivariate volatility model by Chou and Cai (2009). The smooth transition in conditional correlation is controlled by some exogenous variables. The model maintains a parsimonious structure while allowing flexibility in specifying the dynamic evolutions of conditional correlations. This paper is organized as follows. Section 2 introduces the model including model specifications, dynamics and tests. Section 3 discusses the data set used for the empirical research. Section 4 provides empirical results. Section 5 concludes this paper.
نتیجه گیری انگلیسی
This paper investigates the relationship between real and financial linkages. We use average CPI rates and VIX as transition variables in our model. Empirical results prove the DSTCC-CARR model to be effective. CCC models are rejected in favor of STCCCARR and DSTCC-CARR formulations. The tests also indicate that the DSTCC-CARR model with both transition variables to outperform the STCC-CARR model with either of the two variables alone. By analyzing the estimated results, this study collects ample evidence on varying correlations among different inflation cycle phases. Our results are consistent with those of Erb et al. (1994) that highest correlations appear when both countries are in the contractionary phase and lowest correlations emerge when both countries are in the expansionary phase. Correlations are also violent during periods with different volatilities, coinciding with Connolly et al. (2007). Future research could employ other indicators of economic fundamentals such as output and interest rates in our model. Other extensions like considering a richer specification with both countries’ inflation rates as transition variables would also be useful.