| dc.contributor | 金融學系 | zh_Tw |
| dc.creator (作者) | 林士貴 | zh_TW |
| dc.date (日期) | 2015 | en_US |
| dc.date.accessioned | 26-Dec-2017 17:45:23 (UTC+8) | - |
| dc.date.available | 26-Dec-2017 17:45:23 (UTC+8) | - |
| dc.date.issued (上傳時間) | 26-Dec-2017 17:45:23 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/115430 | - |
| dc.description.abstract (摘要) | 本計畫針對 CME 在美國 18 個城市所發行之 CDD/HDD 衍生性商品進行模型配適、評價公式與評價績效。在模型配適部分，提出 S-MR-S-SA-GARCH 模型來刻畫溫度指數之走勢，透過粒子群最適化演算法進行參數估計，並利用 AIC、BIC、概似比檢定等方法判斷此模型之配適度優於其他模型。評價之部分，提出一組溫度期貨評價公式之封閉解，僅存在一層積分因此透過 Laguerre-Gauss-Quadrature 積分法即可有效率地計算溫度期貨價格。然而，溫度期貨選擇權可視為以一系列歐式買權或賣權總和所組成之複合選擇權，此商品不存在封閉解因此本研究利用蒙地卡羅模擬之方式進行評價。評價績效方面，研究期間內 S-MR-S-SA-GARCH 模型具有較好之評價績效，即理論價格與市場價格誤差較小，因此可作為未來市場參與者之評估溫度衍生性商品價格之工具。 | zh_TW |
| dc.description.abstract (摘要) | This study focuses on the CDD/HDD derivatives issued by CME for 18 cities in the U.S. There are three parts in this study: the model estimation, the pricing formula, and the pricing performance. For the part of model estimation, we support the S-MR-S-SA-GARCH model to depict the path of daily temperature index (DAT), and employ the particle swarm optimization algorithms to estimate the model parameters. Comparing to the AICs, BICs, and likelihood ratio tests cross five models, the S-MR-S-SA-GARCH model improves the goodness-of-fit for the DAT. For the part of pricing formula, we develop a closed form for the CDD/HDD futures with only one integral. The Laguerre-Gauss quadrature integration can approximate the price of futures efficiently. However, the CDD/HDD futures options can be seen as the sum of a series of European call/put options, and we use the Monte-Carlo simulation to price futures options owing to no closed form solution. For the part of pricing performance, over the study period, the S-MR-S-SA-GARCH model has the better performance than other models. That is, the pricing error which is compute by the difference between the model price and the market price is smaller than other four models. Thus, the pricing formula under the S-MR-S-SA-GARCH model can provide a methodology/tool for the market participants. | en_US |
| dc.format.extent | 838140 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | 執行起迄：2015/08/01~2017/07/31 | zh_TW |
| dc.relation (關聯) | 104-2410-H-004-021-MY2 | zh_TW |
| dc.subject (關鍵詞) | 日均溫;CDD/HDD衍生性商品;均數復歸;一般化自我迴歸條件變異模型;季節性不對稱非預期效果;特徵函數評價法;粒子群演算法 | zh_TW |
| dc.subject (關鍵詞) | Daily average temperature index; CDD/HDD derivatives; Mean reversion; GARCH model; Asymmetric unexpected effect with seasonality; Zharacteristic function pricing method; Particle swarm optimization | en_US |
| dc.title (題名) | 在季節性、不對稱性及極端氣候下隨機波動度之氣候衍生性商品定價與避險：GARCH 與 SV 模型之應用 | _TW |
| dc.type (資料類型) | report | |
