A Dynamic Analysis of Exchange Rate Exposure: The impact of China's Renminbi

Abstract

This study examines the impacts of unexpected exchange rate movements of Chinese renminbi (CNY/USD) on stock returns of Standard & Poor's 500 corporations. To gain better insight into the long‐standing exposure puzzle concerning the divergence between theoretical and empirical investigation and the critical issue regarding the determinants of exposure, the time variation and asymmetry property associated with foreign exchange exposure are further taking into account. We also broaden the scope of analysis to investigate unexpected risk exposure at 10 economic sectors in compliance with Global Industry Classification Standard. Unlike those from the static analysis or dynamic ones with the ordinary least squares model, the empirical findings provide additional concrete evidence that unexpected exchange rate exposure varies substantially across time and market circumstances when using the quantile regression with a rolling method. Furthermore, our dynamic analysis not only supports the existence of industrial effects across different economic sectors, but also provides strong evidence that financial factors, such as size, debt ratio and book to market ratio, have a significant impact on exposure.

Why did some firms perform better in the global financial crisis?

“…Due to the astonishing expansion and fast growth of China's stock markets, the management of large funds and international institutions have recognised the profit-making opportunities and are weighting more of their investment portfolios in these stock markets (Chen, Lee, Lee, & Huang, 2016b;Lee, Chen, & Hsieh, 2013;Lao & Singh, 2011). Nevertheless, recent developments since the onset of the global financial crisis also show that China is not autonomous (Fidrmuc & Korhonen, 2010).…”

Quantile regression-based seasonal adjustment

“…(Pascual, 2003) recommended the use of rolling regression with a fixed window instead of using recursive regression as this maintains the test power fixed. The implementation of the rolling quantile regression approach has been applied in previous studies which mainly focuses on finance (Guler et al (2017); (Aretz and Arisoy, 2016); (Cenesizoglu and Timmermann, 2007); (Bonaccolto, 2016); (Xu and Childs, 2013); (Cho et al, 2015); (Chen et al, 2016)). Here we implement the quantile regression-based seasonal adjustment approach in the framework of the rolling analysis.…”

Exchange rate fluctuations and interest rate policy

“…When the RMB is undervalued through market intervention by China, the expectation of future appreciation makes it more attractive to hold and makes U.S. dollars less desirable. However, that distortion was restored to normal (Chen, Lee, Lee, & Huang, 2016; Chen, Zeng, & Lee, 2018; Kang, Ratti, & Vespignani, 2016) after the RMB was decoupled from the U.S. dollar in 2005.…”

“…Under the floating exchange rate system, if the domestic interest rate is higher than the foreign interest rate, then a large amount of international speculative capital will theoretically flow in, and the currency will face appreciation pressure. The greater the market power of speculators is, the more the forward exchange rate deviates from the interest rate parity equilibrium exchange rate (Chen et al, 2016; Gu & Mcnelis, 2013; Jing & Zhao, 2017). Guo et al (2009) find the influx of international speculative capital causes fluctuations in the demand for RMB in the international capital market, and a large amount of foreign exchange funds leads to domestic excess liquidity, which results in the rise of domestic interest rates and fluctuating interest rate spreads between China and the United States.…”