| dc.contributor.advisor | 曾正男 | zh_TW |
| dc.contributor.advisor | Tzeng, Jeng-Nan | en_US |
| dc.contributor.author (Authors) | 顧宗桓 | zh_TW |
| dc.contributor.author (Authors) | Ku, Tsung-Huan | en_US |
| dc.creator (作者) | 顧宗桓 | zh_TW |
| dc.creator (作者) | Ku, Tsung-Huan | en_US |
| dc.date (日期) | 2023 | en_US |
| dc.date.accessioned | 2-Aug-2023 13:02:13 (UTC+8) | - |
| dc.date.available | 2-Aug-2023 13:02:13 (UTC+8) | - |
| dc.date.issued (上傳時間) | 2-Aug-2023 13:02:13 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0108751004 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/146298 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 應用數學系 | zh_TW |
| dc.description (描述) | 108751004 | zh_TW |
| dc.description.abstract (摘要) | 本研究使用區間模糊數來建立模糊區間模型用以預測出財經資料最高價最低價之價格範圍，作為實際操盤使用。本論文以黃金期貨交易作為研究標的，在預測模型的建立上我們嘗試幾種不同的建立模組，得到預測未來的模糊區間，再用以操作當沖策略，並計算其收益。我們提供了新的模糊區間建立的R-r 方法，拓展模糊區間為一個三維的數值，以此三維數值進行預測，並結合適當的操作策略，提高收益的成效。本論文以1982年至2022年的黃金期貨為資料，經過多種模型測試，本研究預測模型直線MAX5日數據的結果呈現良好且穩定，操作策略成效優於傳統模糊統計的論文，因此，本研究推薦以直線MAX5日預測模型進行預測。 | zh_TW |
| dc.description.abstract (摘要) | This paper uses interval fuzzy number to establish a fuzzy interval forecasting model to forecast the price range of the highest price and lowest price of financial data for trading. This paper takes gold futures day trading as the research objective. In the establishment of the forecasting model, this paper tries several different models to obtain the next day’s forecasting fuzzy interval, and then combine the proposed operating strategy to calculate its profit. This paper provides a new fuzzy interval for establishing the R-r method which expands the fuzzy interval into a three-dimensional value, then use this three-dimensional value to forecast, and improve the effectiveness of profit through the proposed operating strategy. The gold futures data in this paper are selected from 1982 to 2022. In the variety of model testing, the MAX 5-day linear forecasting model data performed well, and its effectiveness is better than the traditional fuzzy statistical papers. Therefore, this paper recommends the MAX 5-day linear forecasting model. | en_US |
| dc.description.tableofcontents | 1.前言 12.研究方法 33.實證分析 74.結論 415.參考文獻 426.附錄 43 | zh_TW |
| dc.format.extent | 4602072 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0108751004 | en_US |
| dc.subject (關鍵詞) | 區間模糊數 | zh_TW |
| dc.subject (關鍵詞) | 當沖 | zh_TW |
| dc.subject (關鍵詞) | 操作策略 | zh_TW |
| dc.subject (關鍵詞) | 黃金期貨 | zh_TW |
| dc.subject (關鍵詞) | Interval fuzzy number | en_US |
| dc.subject (關鍵詞) | Day trading | en_US |
| dc.subject (關鍵詞) | Operating strategy | en_US |
| dc.subject (關鍵詞) | Gold futures | en_US |
| dc.title (題名) | 黃金期貨當沖的預測與操作策略 | zh_TW |
| dc.title (題名) | The Day Trading Forecasting and Operating Strategy of Gold Futures | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (參考文獻) | [1] Ji, Zhang, D., & Zhao, Y. (2020). Searching for safe-haven assets during the COVID-19 pandemic. International Review of Financial Analysis, 71, 101526–101526.[2] Narayan, Narayan, S., & Zheng, X. (2010). Gold and oil futures markets: Are markets efficient? Applied Energy, 87(10), 3299–3303.[3] Reboredo. (2013). Is gold a safe haven or a hedge for the US dollar? Implications for risk management. Journal of Banking & Finance, 37(8), 2665–2676.[4] Samuelson, P. A. (1965). Proof that properly anticipated prices fluctuate randomly. Industrial Management Review, 6(2), 41–49.[5] Malliaris, A. G. (1981). Martingale Methods in Financial Decision-Making. SIAM Review, 23(4), 434–443.[6] Hull. (2006). Options, futures, and other derivatives (6th ed.). Pearson, Prentice Hall.[7] 吳柏林、謝名娟（2011）網路教育問卷調查新技術與線上模糊統計分析建構，國家教育研究院[8] 吳柏林（2015）模糊統計導論：方法與應用(二版) ，五南出版社[9] 陳松男（2008）金融工程學: 金融商品創新選擇權理論，新陸書局 | zh_TW |
