The Exchange Rate Sensitivities of Stock Returns in Japan: The Japanese Machinery Industry Cases

Transcription

1 The Exchange Rate Sensitivities of Stock Returns in Japan: The Japanese Machinery Industry Cases Chikashi TSUJI Abstract This paper investigates whether the exchange rates are priced in recent periods in the Japanese machinery industry. Our empirical examination firstly shows that recently, the sensitivities of exchange rates in the Japanese machinery industry increased. Further, our traditional regressions demonstrate that as to the Japanese machinery industry, in the recent periods, the exchange rate changes are priced in equity markets. Keywords: Asset pricing; Exchange rate sensitivity; Japanese machinery Industry. This paper was prepared for the annual report of the Data Bank Project of the University of Tsukuba. The author greatly appreciates the generous financial assistance of the Data Bank Project of the University of Tsukuba, which is led by Kazuo Kishimoto. The author also thanks the Japan Society for the Promotion of Science for their financial assistance. Correspondence: Chikashi TSUJI, Associate Professor, Department of Social Systems and Management, Graduate School of Systems and Information Engineering, University of Tsukuba. Address: Tennodai, Tsukuba, Ibaraki , Japan. 1

2 1. Introduction Exchange rate risks were often discussed in practical and academic contexts. Related important researches are, for example, those by Chow et al. (1997), Griffin and Stulz (2001), Phylaktis and Ravazzolo (2005), and Verdelhan (2010). Based on these studies, in this paper, we focus on the recent periods and the Japanese export industry because the Japanese yen much appreciated in recent periods and this affects the profitability of this industry. Hence more concretely, our objective in this paper is to empirically check whether the exchange rates are recently priced as to the Japanese machinery industry. The contribution in this paper is firstly that we find that recently, the sensitivities to the exchange rates of the Japanese machinery industry firms increased. In addition, our traditional regressions demonstrate that as to the Japanese machinery industry, in the recent periods, exchange rates are priced in stock markets. The organization of this paper is as follows. First, Section 2 documents our data set and research design, Section 3 shows our empirical evidence, Section 4 concludes the paper, and Section 5 notes for using our supplied data in Appendix. 2. Data and Research Design Our data (from QUICK Corp.) sample period starts January 1990 and ends July The notations of data are as follows: DEF: default spreads; TERM: term spreads; IP: the log percentage changes of seasonally adjusted industry productions; CPI: CPI percentage growth rates; MVOL: historical volatilities of market returns; ΔEX: changes of the exchange rates of the yen/us dollars. Further, we computed the sensitivities of stock returns of six companies in the Japanese machinery industry. These time-series values are exhibited in Panels A to F in Figure 1. (These time-series data are supplied in Appendix.) Regarding six companies names, Komatsu denotes Komatsu Ltd., Mitsubishi denotes Mitsubishi Heavy Industries Ltd, Kubota denotes Kubota Corp., SMC denotes SMC Corp., Daikin is Daikin Industries Ltd., and Hitachi denotes Hitachi Construction Machinery Co., Ltd. With regard to the research design, we first divide our full sample period into five periods as follows. The first period is from January 1990 to August 1994; the second period is from September 1994 to April 1999; the third period is from May 1999 to December 2003; the fourth period is from January 2004 to September 2008; the latest 2

3 period is from October 2008 to July Then we perform the following regressions for all companies and all sample periods. RET. (1) i, t i i 1DEFt i2term t i3ipt i4cpit i5mvolt i6 EX t i, t Where RET i,t denotes each company s return. Our focus here is the statistical significance of the coefficient of ΔEX, in particular, in recent sample periods. Figure 1. Stock Return Sensitivities to Exchange Rates: The Cases of the Japanese Machinery Industry Firms Panel A. Komatsu / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /07 Panel B. Mitsubishi / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /07 3

4 4 Panel C. Kubota Panel D. SMC Panel E. Daikin / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /07

5 Panel F. Hitachi / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /07 3. Empirical Results We display our empirical results from Tables 1 to 5. The results in Tables 1 to 5 are the evidence from regression (1). Again, our focus is on the statistical significance of the variable, ΔEX. Describing our empirical results, in Tables 1 to 3, little statistical significance of ΔEX is recognized. However, in Table 4, out of six companies, four companies show the statistical significant coefficients in regression (1) with positive sign. In addition, in Table 5, again four companies demonstrate the statistical significant positive coefficients in regression (1). Thus, these results mean that as to the Japanese machinery industry firms, in the recent periods of January 2004 to September 2008 and October 2008 to July 2012, exchange rates are statistically strongly priced in the Japanese equity markets. 5

6 Table 1. The Results of Regressions for Komatsu, Mitsubishi, Kubota, SMC, Daikin, and Hitachi: January 1990 to August 1994 Komatsu Mitsubishi Kubota SMC Daikin Hitachi Constant DEF TERM IP CPI 4.377** ** 6.0* 4.796** MVOL ΔEX 0.440* ** ** Adj. R Obs. Notes: Regarding companies names, Komatsu denotes Komatsu Ltd., Mitsubishi is Mitsubishi Heavy Industries Ltd, Kubota denotes Kubota Corp., SMC denotes SMC Corp., Daikin is Daikin Industries Ltd., and Hitachi denotes Hitachi Construction Machinery Co., Ltd. Further, Adj. R 2 denotes the values of adjusted R-squared values and Obs. means the number of samples in our time-series regressions. *** denotes the statistical significance at the 1% level, ** denotes the statistical significance at the 5% level, and * denotes the statistical significance at the 10% level, respectively. 6

7 Table 2. The Results of Regressions for Komatsu, Mitsubishi, Kubota, SMC, Daikin, and Hitachi: September 1994 to April 1999 Komatsu Mitsubishi Kubota SMC Daikin Hitachi Constant DEF * TERM * IP *** CPI MVOL ΔEX ** Adj. R Obs. Notes: Regarding companies names, Komatsu denotes Komatsu Ltd., Mitsubishi is Mitsubishi Heavy Industries Ltd, Kubota denotes Kubota Corp., SMC denotes SMC Corp., Daikin is Daikin Industries Ltd., and Hitachi denotes Hitachi Construction Machinery Co., Ltd. Further, Adj. R 2 denotes the values of adjusted R-squared values and Obs. means the number of samples in our time-series regressions. *** denotes the statistical significance at the 1% level, ** denotes the statistical significance at the 5% level, and * denotes the statistical significance at the 10% level, respectively. 7

8 Table 3. The Results of Regressions for Komatsu, Mitsubishi, Kubota, SMC, Daikin, and Hitachi: May 1999 to December 2003 Komatsu Mitsubishi Kubota SMC Daikin Hitachi Constant * DEF TERM IP CPI MVOL ΔEX 0.941* Adj. R Obs. Notes: Regarding companies names, Komatsu denotes Komatsu Ltd., Mitsubishi is Mitsubishi Heavy Industries Ltd, Kubota denotes Kubota Corp., SMC denotes SMC Corp., Daikin is Daikin Industries Ltd., and Hitachi denotes Hitachi Construction Machinery Co., Ltd. Further, Adj. R 2 denotes the values of adjusted R-squared values and Obs. means the number of samples in our time-series regressions. *** denotes the statistical significance at the 1% level, ** denotes the statistical significance at the 5% level, and * denotes the statistical significance at the 10% level, respectively. 8

9 Table 4. The Results of Regressions for Komatsu, Mitsubishi, Kubota, SMC, Daikin, and Hitachi: January 2004 to September 2008 Komatsu Mitsubishi Kubota SMC Daikin Hitachi Constant DEF TERM IP CPI 5.322* 6.483** *** 3.578* MVOL ΔEX 0.999** ** 0.693* ** Adj. R Obs Notes: Regarding companies names, Komatsu denotes Komatsu Ltd., Mitsubishi is Mitsubishi Heavy Industries Ltd, Kubota denotes Kubota Corp., SMC denotes SMC Corp., Daikin is Daikin Industries Ltd., and Hitachi denotes Hitachi Construction Machinery Co., Ltd. Further, Adj. R 2 denotes the values of adjusted R-squared values and Obs. means the number of samples in our time-series regressions. *** denotes the statistical significance at the 1% level, ** denotes the statistical significance at the 5% level, and * denotes the statistical significance at the 10% level, respectively. 9

10 Table 5. The Results of Regressions for Komatsu, Mitsubishi, Kubota, SMC, Daikin, and Hitachi: October 2008 to July 2012 Komatsu Mitsubishi Kubota SMC Daikin Hitachi Constant DEF * TERM IP ** 0.887*** CPI 4.306** * MVOL ΔEX 1.744*** *** 1.362** 3.166*** Adj. R Obs Notes: Regarding companies names, Komatsu denotes Komatsu Ltd., Mitsubishi is Mitsubishi Heavy Industries Ltd, Kubota denotes Kubota Corp., SMC denotes SMC Corp., Daikin is Daikin Industries Ltd., and Hitachi denotes Hitachi Construction Machinery Co., Ltd. Further, Adj. R 2 denotes the values of adjusted R-squared values and Obs. means the number of samples in our time-series regressions. *** denotes the statistical significance at the 1% level, ** denotes the statistical significance at the 5% level, and * denotes the statistical significance at the 10% level, respectively. 10

11 4. Conclusions This paper studied the exchange rate sensitivities of the machinery industry firms in Japan. Our contribution is that we find that in recent periods, as to the Japanese machinery industry firms, exchange rates are statistically strongly priced. Further, we consider that related future studies around the world and in similar contexts shall be valuable for deepening our knowledge of (in)efficient financial markets. 5. Notes for Using Data We limit the use of the attached data to academic research only. Any publications using these data must cite this paper. We are not responsible for any loss or damage following any use of these data for actual investments or deals. Views expressed in this paper are those of the author and do not necessarily reflect those of the Data Bank Project of the University of Tsukuba. References Bartov, E., Bodnar, G. M., Kaul, A. (1996) Exchange rate variability and the riskiness of US multinational firms: evidence from the breakdown of the Bretton Woods system. Journal of Financial Economics 42, Chow, E. H., Lee, W. Y., Solt, M. E. (1997) The exchange-rate risk exposure of asset returns. Journal of Business 70, Griffin, J., Stulz, R. (2001) International competition and exchange rate shocks: across-country industry analysis of stock returns. Review of Financial Studies 14, Phylaktis, K., Ravazzolo, F. (2005) Stock prices and exchange rate dynamics. Journal of International Money and Finance 24, Verdelhan, A. (2010) A Habit-Based Explanation of the Exchange Rate Risk Premium. Journal of Finance 65,

12 12 Appendix Estimated Sensitivities of Exchange Rates to Stock Returns of the Japanese Machinery Industry Firms Komatsu Mitsubishi Kubota SMC Daikin Hitachi 1990/ / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /

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