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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/69370完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 呂育道(Yuh-Dauh Lyuu) | |
| dc.contributor.author | Yi-Ke Huang | en |
| dc.contributor.author | 黃奕軻 | zh_TW |
| dc.date.accessioned | 2021-06-17T03:13:59Z | - |
| dc.date.available | 2018-07-19 | |
| dc.date.copyright | 2018-07-19 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-07-11 | |
| dc.identifier.citation | Borovykh, A., Bohte, S., & Oosterlee, C. W. (2018). Conditional time series forecasting with convolutional neural networks. Retrieved June 15, 2018, from https://arxiv.org/abs/1703.04691v4
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/69370 | - |
| dc.description.abstract | 股市指數通常由多家上市公司的股票組合而成。然而其價格決定於複雜的交易過程，並且資產間時常具有非線性的相依性。因此為了預測指數未來的短期走勢，我們考慮以卷積神經網路處理非線性多維時間序列。我們將模型用於預測指數的上漲或下跌，並實證模型的預測性。市場高頻資料 (每5秒) 包含了 2015 年至 2017 年日內的臺灣加權指數與個股價格。實驗結果顯示，模型使用在日內交易預測能得到良好的準確率與績效。 | zh_TW |
| dc.description.abstract | A stock index consists of a board selection of stocks. Stylized facts show non-linear correlations exist between stock prices. Therefore, predicting the direction of an index involves modeling and analyzing sophisticated multi-dimensional time series. We employ the convolutional neural network to forecast the intra-day price movement of the Taiwan Stock Exchange Weighted Index (TAIEX). Furthermore, we verify the prediction performance of our model on the high-frequency data (5 sec) of the TAIEX and its constituent share prices from 2015 to 2017. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T03:13:59Z (GMT). No. of bitstreams: 1 ntu-107-R05922111-1.pdf: 1501490 bytes, checksum: 3e7bf2bfc8927179f72569b62ef8f791 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 致謝 i
中文摘要 iii 英文摘要 v 圖目錄 vii 表目錄 ix 第一章 研究介紹與文獻回顧 1 第二章 預測模型 5 第一節 卷積神經網路 5 第二節 估計方法 8 第三章 實證研究 11 第一節 資料來源以及特性 11 第二節 趨勢預測 12 第三節 模型預測結果 15 第四章 結論 21 參考文獻 23 | |
| dc.language.iso | zh-TW | |
| dc.title | 上市個股預測台灣加權指數高頻趨勢 | zh_TW |
| dc.title | Prediction of Short-Term Trends of TAIEX via Its High-Frequency Constituent Share Prices | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 金國興(Guo-Xing JIN),張經略(Jing-Lue Zhang),鄧惠文(Hui-Wen Deng),蔡芸琤(Yun-Cheng Cai) | |
| dc.subject.keyword | 台灣證券市場,日內資料,資料探勘,神經網絡,股票預測, | zh_TW |
| dc.subject.keyword | Taiwan Stock Market,Intraday trading,Data mining,Neural network,Stock prediction, | en |
| dc.relation.page | 25 | |
| dc.identifier.doi | 10.6342/NTU201801430 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-07-11 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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|---|---|---|---|
| ntu-107-1.pdf 目前未授權公開取用 | 1.47 MB | Adobe PDF |
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