Dissertation/ Thesis
The Research of Applying Data Mining on Option Pricing - The Case of CME Gold Options
| العنوان: | The Research of Applying Data Mining on Option Pricing - The Case of CME Gold Options |
|---|---|
| Alternate Title: | 資料採礦於選擇權評價模型之應用 - 以美國CME黃金期貨選擇權為例 |
| المؤلفون: | Ying-Shan, Liu, 劉盈珊 |
| Thesis Advisors: | Yao-Hung, Chang, Tai-Ning, Yang, 張耀鴻, 楊泰寧 |
| سنة النشر: | 2013 |
| المجموعة: | National Digital Library of Theses and Dissertations in Taiwan |
| الوصف: | 101 After the subprime financial crisis, gold market continues to heating up and the price is climbing. However, the gold market has turned downward in 2013 with a rapid price decline, and the outlook is divergent. Options payoff could be expected in both bull and bear market. Its nonlinear pricing characteristic could apply back-propagation neural network (BPNN) to identify a suitable price level. Nowadays data mining technology is widely used in various fields. Data mining tools have been innovation, and most of them have included neural network function. In this study, I use WEKA, a widely-used academic data mining tool, to conduct evaluation studies by BPNN. The data uses U.S. CME gold future call options daily settlement price with the period from January 1983 to March 2011. Empirical results show that, in addition to BS model (Black-Scholes Option Pricing Model) basic variables, the additional variable inputs of current and previous open-interest volume from options and the underlying commodity could improve the model accuracy. In an up-down oscillation market, including sorely CME option implied volatility might not be necessary to improve the model accuracy. |
| Original Identifier: | 101PCCU1396020 |
| نوع الوثيقة: | 學位論文 ; thesis |
| وصف الملف: | 74 |
| الاتاحة: | http://ndltd.ncl.edu.tw/handle/70188686533743789880 |
| رقم الانضمام: | edsndl.TW.101PCCU1396020 |
| قاعدة البيانات: | Networked Digital Library of Theses & Dissertations |
| الوصف غير متاح. |