技術分析是否可以賺取超額報酬？ 以中國ETF為例

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题名:	技術分析是否可以賺取超額報酬？以中國ETF為例
作者:	曹兆渢;Tsao, Chao-Feng
贡献者:	高階主管企管碩士班
关键词:	技術分析;賺取;超額報酬;technical analysis;earning;excess returns
日期:	2023-11-30
上传时间:	2024-09-19 16:31:57 (UTC+8)
出版者:	國立中央大學
摘要:	本文為驗證技術分析在中國ETF市場中是否能夠獲得超額報酬。透過選取ETF標的與交易策略，整理出綜合的數據分析與對比。基於技術分析有效性的研究文獻，與闡述中國ETF市場的現況，更說明技術分析在投資決策中的應用特點。為實現研究目標，選用三種不同交易策略與六檔代表性ETF。透過收集交易數據及交易成本，並處理為交易訊號，藉以分析進出場後，最終交易結果的績效。在數據分析中，採用了期末報酬、區間最大報酬、最大回撤及交易次數等交叉比對方法，以研究技術分析與超額報酬之間的關聯性。結果顯示技術分析在中國ETF市場具有一定的相關性。例如數據反應受大盤環境或突發事件的影響，風險承受度和獲利幅度的相關聯動。本研究為投資大眾和市場交易人員提供了制定交易策略的幫助。未來的研究可以進一步探討技術分析在不同市場環境下的關聯性，並衍生含括其他因素對超額報酬的影響。為投資大眾和市場參與者提供有數據基礎的決策資訊。 ;This article examines whether technical analysis can achieve excess returns in China′s ETF market. By selecting ETF targets and trading strategies, a comprehensive data analysis and comparison is collated. Based on the research literature on the effec-tiveness of technical analysis, the current situation of ETF market in China is further illustrated to further illustrate the advantages and limitations of the application of tech-nical analysis in investment decision-making. To achieve our research objectives, we selected three different trading strategies and six representative ETFs. By collecting transaction data and processing it into transaction signals, we can analyze the perfor-mance of the final transaction result after entering and exiting the market. In the data analysis, cross-comparison methods such as end-of-period reward, interval maximum reward, maximum drawdown and number of transactions were used to study the corre-lation between technical analysis and excess reward. The results show that technical analysis has a certain correlation in the Chinese ETF market. For example, the data re-sponse is affected by the market environment or unexpected events, and the correlation between risk tolerance and profit margin. This study provides support to the investing public and market traders in developing trading strategies. Future research could further explore the correlation of technical analysis in different markets and derive the impact of other factors on excess returns. Provide data-based decision-making information for the investing public and market participants.
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