標題: | 應用技術指標與市場輪廓理論於臺指期貨轉折點之行為發現 Applying Technical Indicators and Market Profile to Discover the Turning Point Behavior of Taiwan Index Futures Market |
作者: | 謝正一 Hsieh, Cheng-I 陳安斌 Chen, An-Pin 管理學院資訊管理學程 |
關鍵字: | 技術指標;市場輪廓;基因演算法;臺灣指數期貨;Technical Indicators;Market Profile;Genetic Algorithms;Taiwan Index Futures |
公開日期: | 2013 |
摘要: | 本研究為以技術指標RSI背離為基礎、交易量物理動能為輔,同時基因演算法於非線性運算空間搜查找尋最佳 RSI指標參數與計算獲利與停損點,針對台灣加權指數期貨市場的趨勢行為,進行分析與轉折點找尋與預測,並於盤勢來回時,進行反方向的轉折點操作進行投資,並根據結果擬定交易策略,交易策略中加入懲罰機制與市場輪廓理論的擺動因子作為參考,操作模擬與績效評估,資料顯示本研究中的策略於五年四個月的時間區間內,訓練期間四年,測試時間一年四個月中台指期的準確率介於 42.86%~59.62%,其中以實驗4最為突出;在考慮交易成本後之年化報酬率介於 17.13%~172.14%其中實驗組3為 172.14%,實驗組4則為129.3%;在平均每次交易獲利介於-118.49~1657.69,實驗組3為 808.17元在實驗組4為 1657.69元,可見利用技術指標RSI背離性及搭配市場輪廓理論,藉由基因演算法進行參數學習找尋轉折點,有卓越的顯著表現,進行台指期趨勢的預測可獲得良好的效果。以提供投資人作為未來投資方法與策略的依據。 This study is to deviate from technical indicators RSI, based on the amount of physical momentum trading, giving the same genetic algorithm for nonlinear operator space search to find the best RSI indicator parameters and calculate profit and stop-loss point for Taiwan's Weighted Index Futures Market trends in behavior analysis and a Turning Point in finding and forecasting, and back forth when plate potential, be a Turning Point in the opposite direction to invest in operations and develop trading strategies based on the results, the swing factor is added trading strategies and market mechanisms outline the theory of punishment as a reference, operation simulation and performance evaluation, information strategy in this study within five months of the time interval during training for four years, four months in the year test period ranged accuracy TAIEX between 59.62% and 42.86% , of which the most prominent experiment 4, after considering transaction costs between the annualized rate of 17.13% and 172.14% in the experimental group 3 was 172.14%, compared to 129.3% in the experimental group 4; between the average profit per transaction between 1657.69 NT and 118.49 NT experimental group 3 was 808.17 NT in the experimental group 4 was 1657.69 NT. Showing that the use of technical indicators RSI with the market deviated from the outline of the theory of genetic algorithm parameters by learning to find a Turning Point, there is significantly superior performance, conduct TAIEX trend forecasts obtained good results. To provide investors with investment approach as the basis for future strategies. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT070163407 http://hdl.handle.net/11536/74967 |
Appears in Collections: | Thesis |