دانلود مقاله ISI انگلیسی شماره 17746
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کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
17746 2013 19 صفحه PDF سفارش دهید محاسبه نشده
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عنوان انگلیسی
Can US economic variables predict the Chinese stock market?
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Pacific-Basin Finance Journal, Volume 22, April 2013, Pages 69–87

کلمات کلیدی
- بازار بورس چینی - پیش بینی برگشت - سرمایه گذاری بین المللی
پیش نمایش مقاله
پیش نمایش مقاله آیا متغیرهای اقتصادی ایالات متحده می توانند بازار بورس چینی را پیش بینی کنند؟

چکیده انگلیسی

In the last few decades, we observed a significant increase in global economic activities and these activities may have an impact on both China's economy and stock market. Given the potential impact, we empirically examine whether US economic variables are leading indicators of the Chinese stock market. Prior to China joining the World Trade Organization (WTO) in the end of 2001, we find no statistical relationship between US economic variables and the Chinese stock market returns. However, we find US economic variables have statistically significant predictive power for periods after China's admission into the WTO. In addition, we show that the combination of US and China economic variables is more superior in terms of forecasting ability than either single country economic variables. These findings are of economic importance from an investment perspective.

مقدمه انگلیسی

There is an ongoing debate as to whether there is a decoupling between economic activities in emerging markets with those in mature markets. Studies supporting the notion that markets are integrated are many. For example, Gultekin et al. (1989), Bekaert and Harvey, 1995 and Bekaert et al., 2010, and Bracker et al. (1999) find that the stock markets contemporaneously co-move among economically integrated countries. In addition, Carrieri et al. (2007) find evidence suggesting that, notwithstanding the substantial differences and time variations in integration, none of the emerging markets are completely segmented from the global market. However, Chinese stock market seems to be different. In particular, Huang et al. (2000) find no co-integration and casual relationship between Chinese and American stock markets. It is important to note that their sample period is from October 1992 to June 1997, which happens to coincide with the period before China joined the World Trade Organization (WTO). In a recent study, Johansson (2009) documents evidence suggesting that China is showing an increasing level of integration with several major financial markets during the last decade. Incidentally, this study's sample includes the period after China's admission into the WTO. It may not be surprising that joining the WTO may be a turning point for the Chinese economy. For example, studies have shown that the importance of the global economy on the Chinese economy has increased significantly after joining the WTO in December 2001. (e.g., Canova and Dellas, 1993, Sachs and Warner, 1995, Frankel and Romer, 1999 and Rumbaugh and Blancher, 2004). In addition, a close relationship exists between economic activity and stock prices (e.g., Schwert (1990) and Roll (1992) for the US economy, and Canova and De Nicolo (1995) for European economies). Hence, it is plausible that the Chinese stock market may be affected by global economic activities through a transmission mechanism from the Global to the Chinese economy, and then from the Chinese economy to the Chinese stock market.1 Since the US is the world's largest economy and is China's largest trading partner, it is reasonable to use US economic variables as a proxy for global economic activity.2 In this paper, we investigate whether US economic variables, such as the dividend–price ratio, earnings–price ratio, as well as the term and default spreads can predict Chinese stock market behavior. We also explore whether US economic variables can provide additional information beyond that contained in Chinese economic variables in predicting the Chinese stock market. Investigating the forecasting ability of US economic variables for the Chinese stock market is relevant for a number of reasons. First, it establishes the proper information set or benchmark for investors focusing on the Chinese stock market. For instance, if US economic variables can predict and provide additional forecasting information for the Chinese stock market beyond that contained in Chinese economic variables, investors should incorporate US economic variables into their information set to enhance the accuracy of their return forecasts. The enhancement of the return forecasts may be economically important from an investment perspective, and will therefore affect the benchmark used for measuring investment performance. Second, analyzing the forecasting ability of US economic variables for the Chinese stock market could have important implications for the cross-sectional returns of the Chinese stock market. As shown by Ferson and Harvey (1999) for the US stock market, among others, economic variables that predict stock returns provide significant explanatory power for the cross-sectional stock returns. Hence, incorporating US economic variable may lead to better asset pricing modelling as well as better cost of capital measuring (e.g., Fama and French, 1997). Third, an investigation of the forecasting ability of US economic variables for the Chinese stock market improves our understanding of the return predictability across countries. Since the extant voluminous literature on return predictability focuses almost exclusively on the US stock market, the present paper provides additional evidence across countries by examining the forecasting ability of the US economic variables for the Chinese stock market. In this paper, we conduct the following analyses on the forecasting ability of the US economic variables for the Chinese stock market. First, we analyze the in-sample forecasting ability of the US economic variables for the Chinese stock market for the aggregate market portfolio and for a large number of component portfolios. Second, we employ an out-of-sample analysis, focusing on comparing the forecasting performance of the enhanced forecasts utilizing the US economic variables as additional predictors relative to the benchmark forecasts based on historical average and the benchmark forecasts based on the China economic variables alone, respectively. Third, we examine the economic importance of incorporating the US economic variables as additional predictors from an investment perspective. Our analysis on the forecasting ability of the US economic variables for the Chinese stock market uncovers a number of interesting empirical facts. In-sample results reveal that although in the time period before China joined WTO, the US economic variables are unable to predict the Chinese stock market. These variables show significant predictive ability after China joined WTO. Following Rapach et al. (2011), we also analyze the predictability of the US variables on the Chinese stock markets not only for the Chinese aggregate market portfolio but also for thirteen Chinese industry portfolios. Our results document a similar pattern – significant increase in the predicting power after China joined WTO – except for one industry, AGRIC (Agriculture, Forestry, and Fishing). Our results seem to suggest that China's admission into the WTO may have an effect on the integration of China economy with the world economy. The increase in integration between the two economies may have contributed to one of our key findings, that is, the US economic variables gain significant predicting power on the Chinese stock market after China joined WTO. Furthermore, we show that the US economic variables can be used in conjunction with the China economic variables to improve return forecasts. In other words, the US economic variables provide useful forecasting information beyond that contained in the China economic variables. In addition, our out-of-sample results further reveal extensive predictability in real time for both the aggregate market portfolio and the thirteen industry portfolios. Finally, in terms of Sharpe ratio and utility gains, including the US economic variables as additional predictors relative to the benchmark forecasts turns out to be economically significant from an investment perspective. This study complements the growing body of knowledge on the Chinese economy and market. For example, Lee and Rui (2000) document some evidence of predictability of China's stock market based on data ending in 1997 for only the market portfolio. Phylaktis and Ravazzolo (2002) find that economic integration provides a channel for financial integration, which explains the high degree of financial integration even in the presence of foreign exchange control for a group of Pacific-Basin countries by analyzing the covariance of excess returns on national stock markets over the period from 1980 to 1998. Wang and Cheng (2004) study the cross sectional predicting power of turnover in the Chinese stock market. Wang and Firth (2004) provide evidence that there is unidirectional contemporaneous, but not one-period lagged, return spillover from developed markets to China market using daily price data from 1994 to 2001. Tian (2007) finds weak co-integration and casual relationship between China and US at the post Asian financial crisis period. Wang and Di Iorio (2007) show that there is an increasing integration between China's A-share market and Hong Kong's stock market, but that there is no evidence that the Chinese A-share market is becoming more integrated with the world market. Masson et al. (2008) review the China's financial liberalization progress since its accession to the WTO. Jiang et al. (2011) investigate the predictability of Chinese market and component portfolios based on China economic variables. Chen et al. (2010) examine stock return predictability in China at the firm level. Hence, this paper's results documenting return predictability using US economic variables as leading indicators adds to the understanding of the Chinese economy and stock market, especially after the admission into the WTO. The remainder of the paper is organized as follows. Section 2 illustrates the statistical methodology. Data is described in Section 3, while Section 4 reports the empirical results. Section 5 concludes.

نتیجه گیری انگلیسی

The relative importance of the world economy for China has increased significantly over the last few decades, especially after China officially entered the WTO in December 2001. Joining the WTO meant more international trade for Chinese exporters. As a result of this move, it is not surprising to see increased integration between the Chinese and Global economy. Another effect of joining the WTO is the establishment of a freer and open financial market.18 Hence, it is plausible that China joining the WTO may result in the Chinese stock market may be significantly affected by the world economy and/or the US economy. In this paper, we examine whether the US economic variables are leading indicators of the Chinese stock market, especially after 2001. Our results show that US economic variables are indeed good leading indicators for the Chinese stock market after China joined the WTO. Prior to that, the predictive ability of these variables are statistically insignificant. One explanation for our findings is the increased integration of the Chinese economy to the world economy after China joined the WTO in 2001. In addition, we show that the US economic variables can be used in conjunction with the China economic variables to enhance return forecasts for the Chinese stock market. Finally, our out-of-sample results indicate extensive predictive power of the US economic variables in real time, which turns out to be economically important from an investment perspective as indicated by significant utility and Sharpe ratio gains. Our findings suggest that conventional predictive regression models for Chinese stock market ignore important information in US (global) economic variables, and investors interested in investing in the Chinese stock market should pay attention to both US and China economic variables. Our results also have potentially important implications for asset pricing models for the Chinese stock market as well as cost of capital calculation. Acknowledgments We are grateful to Charles Cao (the editor), two anonymous referees, Hendrik Bessembinder, Yin-Wong Cheung, Chiraphol New Chiyachantana, Dong He, Wei Huang, Tuuli Koivu, Peter Phillips, David E. Rapach, Laura Solanko, Qian Sun, Kun Wang (2011 AFBC discussant), Yexiao Xu, Jun Yu, Yongding Yu, Bohui Zhang (2011 CICF discussant), Chu Zhang, Xuechun Zhang, Guofu Zhou, Hengfu Zou and session and seminar participants at 2011 China International Conference in Finance, 2011 Australasian Finance and Banking Conference, HU-HUE-SKBI Tripartite Conference, Bank of Finland Workshop on China's Financial Market and Internationalization of RMB, International Conference for the Economic and Financial Challenges and Issues in the Asia-Pacific Countries at Southwestern University of Finance and Economics, and Singapore Management University. Tu acknowledges financial support for this project from Sing Lun Fellowship.

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