Exchange rate and Chinese financial market: Variance decomposition under vector autoregression approach

Shweta Ahalawat and Archana Patro ()

Cogent Economics & Finance, 2019, vol. 7, issue 1, 1628512

Abstract: The foremost objective of the manuscript is to predict dynamic behaviour of economic and financial time series i.e. exchange rate and price of stock market in China and also to determine if there is a interrelation between the two. Monthly time series data of 10 years have been taken, from January 2009 to December 2018 (post-financial crisis of 2008). The unit root test, variance decomposition under vector autoregressive (VAR) approach, impulse response function and Granger causality under VAR environment have been smeared to infer the long and short-run statistical dynamics. The outcomes of vector autoregression approach depict that the two variables have positive impact and are statistically significant in the short run. There is no long-run association and causal relation between the exchange rate and Chinese financial market.

Date: 2019
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DOI: 10.1080/23322039.2019.1628512

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