Do short-term international capital movements play a role in exchange rate and stock price transmission mechanism in China?

Xin, Li; Su, Chi‐Wei; Chang, Hsu‐Ling; Ma, Ji

doi:10.1016/j.iref.2018.02.010

Cited by 9 publications

(10 citation statements)

References 33 publications

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“…Thus, this study has the same results for Egyptian T-bills against inflation as many Previous studies; but it has different results for Egyptian common stocks performance under inflation with results at Italy (Bagliano & Beltratti, 1997); Pakistan (Akmal, 2007) USA (Ang et al, 2012) & in addition, this study has a same different when Comparative returns between Egyptian T-bills & Egyptian stock with results at Ghana (Antwi et al, 2012); In addition & for Egyptian common stocks, this study pointed to the impact of exchange rate Floating on short-run international capital movements (SICM), which is consistent with the study results of (Li, Chang, & Ma, 2018), finally, the study found a preference for investing in Egyptian Treasury bills relative to Egyptian common stocks in the long term, which is Indirect consistent with (Bessembinder, 2017).…”

Section: Study Conclusionsupporting

confidence: 85%

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Performance of Stock and Treasury Bills Under Inflation and Floating: Evidence from Egypt

Wagdi

Tarek²,

Edres³

2018

SSRN Journal

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Section: Study Conclusionsupporting

confidence: 85%

“…Li, X., Su, C. W., Chang, H. L., & Ma, J. (2018) Through Literature review, the study finds the following:…”

Section: -2015 Chinamentioning

confidence: 99%

Performance of Stock and Treasury Bills Under Inflation and Floating: Evidence from Egypt

Wagdi

Tarek²,

Edres³

2018

SSRN Journal

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“…Hence the quantitative easing policy, especially in the U.S., had a significant influence on IRD and SCF. Besides, according to previous studies, exchange rate (Hacker, Karlsson, & Mansson, 2014), stock price (Li et al, 2018) and capital control (Cheung et al, 2016) are also considered as factors that influence changes in IRD and SCF. In our paper, the cointegration test (Johansen, 1988;Johansen & Juselius, 2009) given in the Appendix is employed to assess the long-run relationship among these factors.…”

Section: Datamentioning

confidence: 99%

“…Since 2013, China has faced short-term capital outflows again, which is mainly attributed to U.S. economic recovery, quitting quantitative policies, and falling domestic asset prices. The fluctuation of China's SCF has become an unneglectable factor that affects its economic development and stability, which would bring higher requirements and serious challenges to macroeconomic policies (Li, Su, Chang, & Ma, 2018). To keep economic stability, reduce negative influences from SCF, and continue the momentum of rapid development, the People's Bank of China (PBOC), Chinese central bank, has implemented a series of monetary policies, including interest rate adjustment.…”

Section: Introductionmentioning

confidence: 99%

Time-varying character for short-term capital flow from the interest rate aspect in China

Wang

Tao

2019

Economic Research-Ekonomska Istraživanja

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This study investigates the causal link between short-term capital flow and interest rate differential with the bootstrap Granger fullsample causality and sub-sample rolling-window methods. The empirical results indicate that there is a unidirectional link from interest rate differential to short-term capital flow. However, when considering structural breaks in the above series, the full-sample causality test cannot be relied on. Hence, the time-varying rollingwindow method is employed to examine the dynamic causal nexus. Being influenced by the U.S. monetary, world economic situation, Chinese intervention policies and other factors, interest rate differential has influences on short-term capital flow in some periods, but the reverse effect does not exist. Therefore, it is important for authorities to focus on specific backgrounds (e.g., economic situation, monetary policies) and further utilise interest rate and capital control to alleviate negative effects from violent fluctuation of short-term capital flow on the Chinese economy.

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“…The relationship between stock prices and macroeconomic dynamics has been studied extensively (Al‐Awadhi, Al‐Saifi, Al‐Awadhi, & Alhamadi, 2020; Ali, Alam, & Rizvi, 2020; Dhingra, Gandhi, & Bulsara, 2016; Ichev & BakerMarinc, 2018; Jain & Biswal, 2016; Katechos, 2011; Li, Su, Chang, & Ma, 2018; Lin & Fu, 2016; Mallick & Mishra, 2019; Mishra, 2004; Mishra, Rath, & Dash, 2020; Vyas, 2014; Vyas & Mishra, 2016; Vyas, Prasad, & Mishra, 2011; Wong, 2017). From these studies, the impact of pandemics (see Al‐Awadhi et al, 2020; Ali et al, 2020; Ichev & BakerMarinc, 2018) gold and crude oil prices (see Jain & Biswal, 2016) demand for money, short term interest rate, net foreign equity flows, and the exchange rate (See Dhingra et al, 2016; Mishra, 2004; Vyas, 2014; Vyas et al, 2011; Vyas & Mishra, 2016) are shown to influence India's stock market.…”

Section: Introductionmentioning

confidence: 99%

Forecasting stock prices of five major commercial banks in India and stress testing: A multivariate approach

Mallick

Mishra

Vyas

2020

Journal of Public Affairs

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This study explains a novel glide path to model the stock prices of five major commercial banks in India. The purpose of this work is concerned with identifying the macroeconomic drivers of stock prices of five core banks listed in NIFTY50 index, namely, SBI, HDFC, ICICI, INDUSIND and KOTAK MAHINDRA, and to test their stability during periods of fiscal tension. The study utilized a Principal Component Analysis (PCA) of the respective stock prices and has proceeded with the multivariate method to make the required predictions. The choice of statistical technique primarily consists of decomposing the respective stock prices of the five banks using PCA and then selecting one optimal Principal Component (PC1). A multivariate regression model is employed to predict the optimal PC of such stock prices in which PC1 is the dependent variable and NIFTY50 and INR‐USD is the independent variables. Ultimately, the optimal PC is returned to the stock prices of the corresponding levels. The model is set up to be performed comfortably and the hardiness of the model is supported from various selection criteria; particular, the model assumption testing, goodness of fit, sample stressed period (using Rolling Average method on Indian VIX: 2008:Q1 to 2009:Q2) testing and out of sample performance. In addition to this, the estimated results are consistent with Monte‐Carlo simulation results. The envisioned model satisfies the model objective, while sufficiently capturing the historical dynamics of the stock prices as reflected by various performance indicators (RMSE, MAPE, RMSE over standard deviation) presented in this paper.

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Do short-term international capital movements play a role in exchange rate and stock price transmission mechanism in China?

Cited by 9 publications

References 33 publications

Performance of Stock and Treasury Bills Under Inflation and Floating: Evidence from Egypt

Performance of Stock and Treasury Bills Under Inflation and Floating: Evidence from Egypt

Time-varying character for short-term capital flow from the interest rate aspect in China

Forecasting stock prices of five major commercial banks in India and stress testing: A multivariate approach

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