博碩士論文 93225009 完整後設資料紀錄

DC 欄位 語言
DC.contributor統計研究所zh_TW
DC.creator鄒紹輝zh_TW
DC.creatorSHAO-HUI TSOUen_US
dc.date.accessioned2006-7-6T07:39:07Z
dc.date.available2006-7-6T07:39:07Z
dc.date.issued2006
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=93225009
dc.contributor.department統計研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract摘要 波動性的問題一直是多年以來各界所著墨的焦點,為了解何種波動性模型所算出的理論價格最貼近於市價,於是本研究利用不同之四種方法,來預測TXO未來一星期的波動度,代入到B-S 模型中得出TXO之理論價格,且利用三種價格誤差的指標,平均絕對誤差(mean absolute errors, MAE)、平均絕對誤差百分比(mean absolute percentage errors, MAPE)及均方誤 (root mean squared errors, RMSE),來比較理論價格與TXO市場價格的差異,並探討模型、參數及預測能力是否會隨著資料的變動而有所改變。最後再使用成對樣本T檢定,比較不同波動度模型下,所有預測之理論價格與市場價格的價格誤差之差異,是否會有相對顯著,希望藉此能找出一適合的模型,可較準確地預測出TXO的合理價格,以降低交易上的損失。zh_TW
dc.description.abstractAbstract The problem of the volatility has been the focus of research for many years. In order to understand the volatility model most suitable for real market data ,we utilize four different models to model the implied volatility for one week TXO future. Three different measurements are used to compare the performance of the models. They are : mean absolute errors (MAE), mean absolute percentage errors (MAPE) and root mean squared errors (RMSE). Real data were applied to study the usefulness of the models.en_US
DC.subject隱含波動性zh_TW
DC.subjectBlack-Scholes 模型zh_TW
DC.subjectGARCH模型zh_TW
DC.subjectBlack-Scholes Modelen_US
DC.subjectGARCH Modelen_US
DC.subjectImplied Volatilityen_US
DC.title隱含波動率之模型及預測:以台灣市場為例zh_TW
dc.language.isozh-TWzh-TW
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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