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Exploring Carry Trade and Exchange Rate toward Sustainable Financial Resources: An application of the Artificial Intelligence UKF Method

1
SHU-UTS SILC Business School, Shanghai University, Shanghai 201899, China
2
School of Business, Dalian University of Technology, Dalian 124221, China
3
Institute of Innovation and Circular Economy, Asia University, Taichung 41354, Taiwan
4
Department of Medical Research, China Medical University, Taichung 40402, Taiwan
*
Authors to whom correspondence should be addressed.
Sustainability 2019, 11(12), 3240; https://doi.org/10.3390/su11123240
Received: 17 March 2019 / Revised: 5 June 2019 / Accepted: 8 June 2019 / Published: 12 June 2019
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Abstract

This paper constructs a heterogeneous agent model for the foreign exchange market that is based on the law of supply and demand and includes carry trade, central bank intervention, and macroeconomic fundamentals. With the artificial intelligence method of the unscented Kalman filter, this paper investigates carry traders’ expectation formation and risk aversion and the impact of their activities on the movement of the Chinese yuan exchange rate and on the efficiency of central bank intervention. The findings demonstrate that carry traders’ activities are partially responsible for fluctuations in the Chinese yuan exchange rate; carry traders behave with obvious risk aversion; their activities tend to weaken the ability of the central bank to intervene in China’s foreign exchange market; and the volatility of the Chinese yuan exchange rate and the weight of carry traders are negatively related. Based on these empirical results, specific suggestions for exploring sustainable financial resources are provided. View Full-Text
Keywords: Chinese yuan exchange rate; carry trade; unscented Kalman filter Chinese yuan exchange rate; carry trade; unscented Kalman filter
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Zhang, Q.; Wu, K.-J.; Tseng, M.-L. Exploring Carry Trade and Exchange Rate toward Sustainable Financial Resources: An application of the Artificial Intelligence UKF Method. Sustainability 2019, 11, 3240.

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