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學術發表 --- (2002 NTU 財務金融國際研討會 ) (( 國立台灣大學財務金融系 )) Regime-Switching Analysis for the Impacts of the Exchange Rate Uncertainty on the Taiwan’s Corporate Values Chien-Chung Nieh 聶建中 淡江大學財務金融系副教授

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Regime-Switching Analysis for the Impacts of the Exchange Rate Uncertainty on the Taiwan’s Corporate Values zKey Words: Exchange rate uncertainty, Corporate values, GARCH, Markov switching model zI. Introduction zII. Data zIII. GARCH modeling for ERU zIV. The OLS and the CUSUM zV. Markov Switching zVI. Concluding remark zAppendix: theoretical model zBased on the controversies between more opportunities to achieve the corporate goals when exchange rates fluctuate and the harmful experiences of the large movements of exchange rates, this paper attempts to investigate the impacts of the ERU on the CVs for the industries concerned in Taiwan. A regime- switching regression is applied. To allow for variance to be drawn from different states, this paper extends the first-moment switching model to a second-moment one.

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Contribution zExtends the first-moment switching model to a second-moment one. zA theoretical model which shows the relationship between the ERU and the CVs is derived. zA two-state first-order MS model is appropriate to describe the relationship between the ERU and the CVs.

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動機 zThree drastic changes in the NTD against the USD since z(1)The regime of managed floating exchange rates was adopted by the government of Taiwan in February of (2) After the "Plaza Accord", the NTD followed the Japanese yen to appreciate within six months from June to November, (3) The drastic depreciation a few months after the Asian financial crisis happened in July 1997.

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文獻回顧 zNegative relationship between the ERU and the exporting flows: Arize (1995), Chowdhury (1993), Hassan (1998), Smith (1999), Arize, Osang and Slottje (2000), and Nieh (2002) zNegative relationship between the ERU and the trading volume: Gupta (1980), Rana (1981), Coes (1981), Cushman (1983), Akhtar and Hilton (1984), Kenen and Rodrik (1986), Chowdhury (1993), Arize (1997), Broll, Wong and Zilcha (1999), and Arize, Osang and Slottje (2000). zPositive relationship between the ERU and the trading volume:Gotur (1985), De Grauwe (1988), Per"ee and Steinherr (1989), Franke (1991), Viaene and Vries (1992), and Broll and Eckwert (1999)

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文獻回顧 ( Markov-switching (MS) ) zHamilton (1988): two-state first-order Markov-switching (MS) model was first citedand. (The probability switching mechanism by Goldfelt and Quandts (1973) for the heteroscedasticity.) zShen (1994) tests the hypothesis the efficiency of the Taiwan- US forward exchange market zHo (2000a) and Ho (2000b) tests the hypothesis for the international capital mobility and the Phillips curve trade-off. zHuang (2000) employ the same technique to examine the Sharpe-Lintner CAPM. zEngel and Hamilton (1990), Garcia and Perron (1993), Engle (1994), Kim and Yoo (1995), and Schaller and van Norden (1997): The applications of the MS mechanism.

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各產業經濟變數之代號 z 化學 (Y1) ；電子 (Y2) ；食品 (Y3) ；玻璃 (Y4) ； 機電 (Y5) ；造紙 (Y6) ；塑膠 (Y7) ；橡膠 (Y8) ； 鋼鐵 (Y9) ；紡織 (Y10) ； z 出口比例在 50% 以上之產業 (Y11) ； 出口比例在 30% 以下之產業 (Y12) ； 出口比例在 30%~50% 之產業 (Y13) ； z 匯率不確定性 ( 匯率波動 ) ： RX z 樣本頻率 ：月資料， 資料期間：七十七年一月至八十九年二月

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理論與實證 z 理論模 型：.Cobb -Douglas 型函數 z 推導得匯率之不確定性與 企業盈餘之關係式： zGARCH effect zThe OLS zCUSUM and CUSUM of squares zMarkov Switching

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GARCH modeling zA GARCH(1,1) modeling zh t, the hetroscedastic variance, implies the EXU( 2 ) in this paper. 。 zPozo(1992), Arize(1995) and Arize(1997)

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GARCH effect

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The OLS

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The goodness-of-fit type tests Brown, Durbin, and Evans (1975) zCUSUM (cumulative sum of residuals) and CUSUM of squares tests:

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Markov switching (Stuctural break) zthe OLS model zthe MS setting

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Estimation

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Specification tests

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Conclusion zOLS approach find that the ERU has the significantly positive impacts on the values among the industries of chemistry, electron, plastic and rubber, but has the negative impacts on that of food industry. zThe structural unstable phenomena from the CUSUM and CUSUM of squares tests reduce the explaining power of the ERU affecting the CVs when the OLS regression is applied. zUsing GARCH(1, 1) modeling to extract the value of exchange rate volatility is appropriate.

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Conclusion zTwo different regimes of a strong-impact and a weak- impact are identified by the values of impact coefficients. zthe influence level of the ERU on the CVs is dominated by the weak impact regime: industries of chemistry, food, electricity, plastic, and rubber. zthe influence level of the ERU on the CVs is dominated by the strong impact regime: industries of electron, glass, and steel. zthe effects of the ERU on the CVs are all dominated by the strong impact regime for all three export ratio. zthe industries of paper and textile show that the impact level is undetermined.

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Conclusion zThe Wald statistics for the null of equality are mixed. zIt is hard to conclude that data are drawn from two different states since the null of no strong-weak impact switching can only be rejected for three industry categories of electron, glass, and plastic. This implies that if the MS model is appropriate, the ERU may not be the major factor but other factors, which could switch the CVs of Taiwan’s industries. zThe data of eight industries are shown to fit a two-state model when the volatility is stimulated.

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Conclusion zTesting for the transition probability, only six out of thirteen industries are rejected at 5% significance level. However, when based on the 10% level, we are able to reject the null of "no regime change," and then conclude that a two- state first-order MS model is appropriate for the "goodness of fit" analysis.

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