The study on the optimal hedge ratio using wavelet analysis
碩士 === 樹德科技大學 === 金融與風險管理系碩士班 === 99 === This paper argues that the noise contained in the original series influence the hedging effectiveness, especially in the long term. First of all, the noise is removed by using wavelet analysis. Secondly, the hedge ratios are estimated by OLS and GARCH with or...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2011
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| Online Access: | http://ndltd.ncl.edu.tw/handle/70928232414601744227 |
| Summary: | 碩士 === 樹德科技大學 === 金融與風險管理系碩士班 === 99 === This paper argues that the noise contained in the original series influence the hedging effectiveness, especially in the long term. First of all, the noise is removed by using wavelet analysis. Secondly, the hedge ratios are estimated by OLS and GARCH with original series and de-noise signal, respectively. Finally, this paper compares the original series and de-noise signal of the hedging effectiveness. The best hedging effectiveness is using OLS model estimations by de-noise signal under four weekly. Furthermore, the most significant improvement on hedging effectiveness is using the BGARCH model with de-noise signal.
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