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The Effect of Exchange Rate Volatility on Stock Return in Taiwan Around Abenomics

Chien-Chung, Nieh and Hsun-Fang, Cho
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Chien-Chung, Nieh: Professor, Department of Banking and Finance, Tamkang University, Taiwan
Hsun-Fang, Cho: Ph.D. Student, Department of Banking and Finance, Tamkang University, Taiwan

Asian Economic and Financial Review, 2017, vol. 7, issue 4, 368-380

Abstract: The purpose of this study is to investigate the relationship between stock returns, exchange rates and financial ratios in the automotive and integrated circuit industries in Taiwan around the introduction of Abenomics. We employ panel data from 34 listed companies on the Taiwan Security Exchange over the period 2011-2014. The Panel Smooth Transition Regression (PSTR) model is utilized to estimate the threshold of exchange rates and its effect on stock returns. The main finding of this paper shows that there exists an efficient hedge regime. When the Abenomics applied a policy of quantitative easing to instigate a sharp depreciation of the yen, the effects of the policies absolutely bring out benefit and competitive advantage of Japanese export industries. The depreciation of the exchange rate against other currencies would affect a country?s international competitive advantage or exports. If Taiwan exchange rate does not follow the depreciation of the yen and the levels of the exchange rate volatility in the automotive and integrated circuits industries in Taiwan are over 2.30% and 2.72% appreciation, respectively, the both industries will generate exchange losses and further influence the profit of the companies. Therefore, the main contribution of this paper is to provide a means for CEOs of companies in the two industries to exercise hedge options and evade the risk of exchange rate for their firms when the appreciation of currency are over 2.3% and 2.72% for automotive and integrated circuits industries, respectively.

Keywords: Panel smooth transition regression model; Exchange rate; Abenomics; Financial ratios; Stock returns; Automotive and integrated circuits industries. (search for similar items in EconPapers)
Date: 2017
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