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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/19966完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李賢源(Shyan-Yuan Lee) | |
| dc.contributor.author | Wei-Siang Huang | en |
| dc.contributor.author | 黃煒翔 | zh_TW |
| dc.date.accessioned | 2021-06-08T02:38:11Z | - |
| dc.date.copyright | 2020-12-25 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-11-17 | |
| dc.identifier.citation | 1.Avramov D., G. Kaplanski, A. Subrahmanyam (2018). The Predictability of Equity Returns from Past Returns: A New Moving Average-Based Perspective. SSRN, 3111334 2.Bessembinder H., K. Chan (1995). The Profitability of Technical Trading Rules in the Asian Stock Markets. Pacific-Basin Finance Journal, 3, 257-284 3.Brock W., J. Lakonishok, B. LeBaron (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47, 1731-1764 4.Corrado C., S. Lee (1992). Filter Rule Tests of the Economic Significance of Serial Dependencies in Daily Stock Return. Journal of Financial Research, 15(4), 369-387 5.De Man J. (2014). Profitability of Technical Trading Strategies “Double Crossover Moving Average Strategy and Contrarian Bollinger Bands Strategy”. Unpublished Master’s Thesis. Tilburg University, Netherland. 6.Fama E., M. Blume (1966). Filter Rules and Stock-Market Reading. Journal of Business, 39(1), 226-241 7.Fama E. (1970). Efficient Capital Markets: A Review of Theory and Works. Journal of Finance, 25(2), 381-417 8.Gehrig T., L. Menkhoff (2006), Extended Evidence on the Use of Technical Analysis in Foreign Exchange International Journal of Finance and Economics, International Journal of Economics, 11, 327-338 9.Gencay R. (1998). Optimization of Technical Trading Strategies and the Profitability in Security Markets. Economics Letters, 59, 249-254 10.Gencay R. (1999). Linear, Non-Linear and Essential Foreign Exchange Rate Prediction with Simple Technical Trading Rules. Journal of International Economics, 47, 91-107 11.George T., C. Huang (2004). The 52-Week High and Momentum Investing. Journal of Finance, 59, 2145-2176 12.Hansen L., R. Hodrick (1980). Forward Exchange Rates as Optimal Predictors of Future Spot Rates: An Econometric Analysis. Journal of Political Economy, 88(5), 829-853 13.Hudson R., M. Dempsey, K. Keasey (1996). A Note on the Weak Form Efficiency of Capital Markets: The Application of Simple Technical Trading Rules to UK Stock Prices – 1935 to 1994. Journal of Banking Finance, 20, 1121-1132 14.LeBaron B. (1999). Technical Trading Rule Profitability and Foreign Exchange Intervention. Journal of International Economics, 49, 125-143 15.Levich R., L. Thomas (1993). The Significance of Technical Trading Rule Profits in the Foreign Exchange Market: A Bootstrap Approach. Journal of International Money and Finance, 12, 451-474 16.Levy R. (1967). Relative Strength as a Criterion for Investment Selection. Journal of Finance, 22, 595-610 17.Lim S., S. Yanyali, J. Savidge (2016). Do Ichimoku Cloud Charts Work and Do They Work Better in Japan? SSRN, 2628581 18.Marshall B. R., R. H. Cahan, J. Cahan (2008). Technical Analysis Around the World: Does it Ever Add Value? SSRN, 1181367 19.Neely C. J. (1997). Technical Analysis in the Foreign Exchange Market: A Layman's Guide. Review-Federal Reserve Bank of St. Louis, 1-15 20.Neely C. J., P. A. Weller, R. Dittmar (1997). Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach. Journal of Financial and Quantitative Analysis, 32, 405-426 21.Park S. (2010). The Moving Average Ratio and Momentum. Financial Review, 45, 415-447 22.林坤良,2007,外匯市場技術分析之研究,國立台灣大學國際企業研究所,碩士論文 23.陳有忠,2007,技術指標應用於外匯交易之研究-以英磅、日圓及台幣為例, 國立台灣科技大學企業管理系碩士在職專班,碩士論文 24.張天禹,2015,技術分析應用於外匯交易之研究,東吳大學財務工程與精算數學系,碩士論文 25.張堯,2018,多國指數的擇時與避險策略-以長短期均線比值為依據,國立台灣大學財務金融學研究所,碩士論文 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/19966 | - |
| dc.description.abstract | 運用交易策略在資本市場上取得最大化的超額報酬,一直都是學界和業界所追求的理想目標,希望能找出各種市場裡對於未來走勢有相當程度預測力的指標因子,並藉此擬定合宜的交易策略從中獲利。大體而言市場分析思維可區分為基本面與技術面兩類,前者係透過研究總體經濟、公司財報、新聞消息等公開資訊,衡量一項標的之真實價值,辨識出相對被市價高估或低估之標的;後者則是經由量化方式分析歷史價格數據,推斷未來之潛在趨勢,並以技術指標提示適當的進出時機點。儘管實務上應用廣泛,技術指標的有效性仍然備受爭論。而在外匯市場是否也一樣存在有效的技術面交易策略,則是本研究欲探討之重點。 本研究以美元、歐元、英鎊、澳幣、日圓、人民幣、台幣7種幣別所組成共21對匯兌組合作為研究標的,根據一目均衡指標(Ichimoku Indicators)為進出場信號,當價格線上穿雲帶做多,下穿雲帶做空,一旦轉換線和基準線交叉即平倉。並且利用MultiCharts軟體模擬歷史回測,研究該策略的績效統計數據,驗證其相較於對照組(雙均線策略),能在外匯市場獲得超額報酬和降低回撤風險。 | zh_TW |
| dc.description.abstract | Applying trading strategies to retrieve maximum excess return on capital markets has been an ideal goal to pursue in both academy and industry, which hopes to find out some factors with predictability of future trends in all sorts of markets and to profit from planning suitable trading strategies according to these factors. Generally speaking, Market analysis mindset can be divided into two categories: fundamental and technical. The former refers to research on macro economy, corporate financial reporting, news and other public information, in order to evaluate an underlying’s authentic value, and distinguish those which are relatively overvalued or undervalued by market prices. The latter refers to analyze historical price data with quantitative approach to deduct future potential trend, and using technical indicators to signal appropriate timing to enter or exit the market. Despite their widely application in practice, technical indicators are still being argued in their effectiveness. Furthermore, whether technical trading strategies with same effectiveness exist in foreign exchange market, is being the main focus in our research. In this paper, we will use USD, EUR, GBP, AUD, JPY, CNY, TWD to compose 21 foreign exchange pairs as subjects. Based on Ichimoku Indicators as entry or exit signal, long the underlying when price curve surpasses “the cloud”, while short when price curve falls over “the cloud”, and exit either position once the conversion line crosses with the standard line. Besides, by running historical backtesting with simulation software MultiCharts, we can gather the performance statistics and verify if Ichimoku gain excess return and decrease drawdown risk, relative to the benchmark (Double Moving Average Strategy). | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T02:38:11Z (GMT). No. of bitstreams: 1 U0001-1211202017562300.pdf: 2010948 bytes, checksum: 4a417b4f4498334230bab248b4d7f554 (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | 誌謝詞 I 中文摘要 II ABSTRACT III 目錄 IV 表目錄 V 圖目錄 VI 第一章 緒論 1 第二章 文獻回顧與策略建構 4 第一節 文獻回顧 4 第二節 策略建構 6 第三章 研究方法及樣本資料 12 第一節 樣本資料來源 12 第二節 資料處理 12 第三節 回測方法 13 第四章 回測數據分析 16 第一節 淨利報酬分析 16 第二節 績效回撤分析 18 第三節 交易頻率分析 20 第五章 結論 22 參考資料 24 | |
| dc.language.iso | zh-TW | |
| dc.title | 一目均衡指標於資本市場之應用-以外匯市場為依據 | zh_TW |
| dc.title | Application of Ichimoku Indicators on Capital Markets – Based on Foreign Exchange Markets | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 109-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 李宗培(Tsung-Pei Lee),姜堯民(Yao-Min Chiang) | |
| dc.subject.keyword | 技術分析,外匯市場,一目均衡指標,擇時,雙均線策略,歷史回測, | zh_TW |
| dc.subject.keyword | Technical Analysis,Foreign Exchange Market,Ichimoku Indicator,Timing Selection,Double Moving Average Strategy,Historical Backtesting, | en |
| dc.relation.page | 26 | |
| dc.identifier.doi | 10.6342/NTU202004334 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2020-11-17 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
| 顯示於系所單位: | 財務金融學系 | |
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