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  • 學位論文

期貨市場交叉避險策略分析-以銅商品交易為例

The Analysis of Cross Hedging Strategy in Futures Markets-A Case of Copper Futures

指導教授 : 胡為善
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摘要


摘 要 2003年一開始,LME銅價出現大幅上升行情,倫敦金屬交易所(LME)銅價自1,546美元/噸,於2月達到1,760美元/噸,漲幅14%。時序進入2003年4月初由於美英在伊拉克戰爭的進展順利,銅價逐漸上揚,隨著世界經濟的復甦,全球銅市場再度獲得上揚的動力,於12月末(LME)銅價已達2,321美元/噸漲幅已超過50%,創兩年來新高,且有挑戰更高價格的趨勢。 目前台灣的電子產業蓬勃發展,所需要使用的銅原料都必須仰賴進口,因而企業在面臨強大的競爭壓力之下,如何降低成本、增加收益就成為企業重要的課題之一。目前國內尚未有對於銅期貨避險之研究,本研究期待透過運用銅期貨及外匯期貨兩者間的避險策略,以提供給企業對於銅原料成本管理與外匯風險管理擬定避險策略之參考。 本研究分析銅進口企業在面臨價格的波動風險及匯率風險的問題,以銅期貨及外匯期貨訂定四種規避風險策略,利用GARCH 模型估算四種策略之最適避險比率,再以變異數估算出避險績效,實證結果顯示: 1、只以銅期貨進行規避價格風險時,避險績效高達99.53%,加入以新台幣對美元即期外匯後,其避險績效略下降0.01%,顯示廠商除進行穩定價格外亦應考慮匯率風險的存在。 2、考慮到匯率風險時,以新台幣對美元外匯期貨及以美元外匯期貨對日幣外匯期貨進行規避匯率風險時,避險績效均達99.52%以上,顯示廠商可運用外匯期貨進行規避匯率風險的存在。

並列摘要


Abstract Since the beginning of the year 2003, the copper price at the Metal Exchange of London (LME) has been sharply, risen from $1,546 / ton to $1,760/ ton, a which indicates 14% drastic increase in less than two months. In April of 2003, resulting from the victory of U.S. and Great Britain in Iraqi war, the copper prices rose up gradually. With the recovery of the international economy, the global copper market price rise up once again. By the end of December of 2003, the copper price at LME was up to $2,321 / ton, an increase exceeded 50%,which is a new peak since the December of 2001. Moreover there is a chance that the copper prices will go higher in the near futures. The electronic industry in Taiwan has been growing vigorously for the past decade. However all the raw materials for copper are imported from foreign countries. Under a stressful environment, the companies in Taiwan are facing against keen competition which forces the companies to lower their operating cost and increasingly profits which becomes one of the enterprise's immediate goods. Since there has been few studies concerning the hedging stratagems to copper futures in Taiwan. This study utilizes the hedging methods to request the Copper Futures Exchange and Currencies Forward Exchange to provide the enterprises reference on the appropriation of raw coppers and risk management of the foreign currency. The main objectives of this study are analyzing the enterprises which imported copper under the risk of price fluctuation and the exchange rate flotation by using the copper futures and foreign exchange to stipulate four different hedging tactics, This work applies the GARCH model to estimate the probability of the best hedging strategies by employing various parameters to calculate four hedging ratios. The empirical results are as follows: 1. When this investigation prices hedging ratio with the copper futures only, the hedging ratio calculated by GARCH model is above 99.53%. When the spot foreign exchange rate between the New Taiwan Dollar and U.S. Dollar is included, then the hedging ratio was reduced by 0.01%. This result showed that the manufacturer should consider both the price stabilization and the hedging of foreign exchange rate. 2. In order to eventing from the risk of foreign exchange rate with New Taiwan Dollars to the U.S. Dollar and with U.S. Dollars to Japanese Yens, this study uses both currencies futures along with the copper futures, the hedging ratio of GARCH model were improved. This result indicated that the manufacturer should use both the currency futures and copper futures to evade from the risk of exchange rate and the price fluctuation risk of coppers.

參考文獻


吳佩珊 市場效率性與避險本研究以門檻雙變量GARCH為實證模型分析亞洲地區國家即期,淡江大學財務金融學系研究所博士論文,民國91年。
Brown, S. L. (1985), “A Reformulation of the Portfolio Model of Hedging,”American Agricultural Economics, Vol. 67, 508-512。
Bollerslev, T. (1986), “Generalized Autoregressive Conditional Heteroscedasticity,”Journal of Econometrics, Vol. 31, 307-327。
Braga, F. S., Martin , L. J. and Meilke, K. D. (1989) , “Cross Hedging the Italian Lira/US Dollar Exchange Rate with Deutsch Mark Futures,”Journal of Futures Markets,Vol.9, No.2; 87-99。
Bollerslev, T. (1990), “ Modelling the Coherence in Short-run Nominal Exchange Rates: Multivariate Generalized ARCH Approach,” Review of Economics and Statistics ,Vol. 72, 498-505。

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