論文摘要翻譯:技術分析評論

論文摘要翻譯:技術分析評論

技術分析常因其在科學和統計驗證方面的不足而受到研究人員的批評。技術分析人士對此的回應往往是,這種方法是一種務實的方法,但其主要興趣在於,與現有理論相比,什麽方法能夠奏效。然而,事實仍然是,技術研究的各種方法都具有較高的主觀性,研究人員經常聲稱,技術分析從業者所使用的價格和指標的模式更多地是站在視角和旁觀者的角度。然而,自過去十年以來,實踐者們繼續生動地描述技術分析實用程序以及它是多麽的有名。最值得註意的是,現在大多數主流報紙的觀點是,根據技術分析方法和一些公司經紀業務,發布股票建議。此外,在過去十年中,對技術分析盈利能力的研究在數量和統計意義方面都有所增加。Park等人(2007)在他們提交的研究論文綜述中試圖通過基於技術的分析來分析潛在的利潤產生。他們發現,現代世界的研究將這種技術方法描述為,在幾個推測的市場中,分析始終有助於產生盈利回報。

然而,技術分析似乎是最有價值的方法自動化與個人電腦,因為股票的價格是現成的。此外,由於技術分析中有許多指標涉及不確定性,在解釋純分析性方法方面存在問題。這似乎是一個適合人工智能和通過機器學習的領域。雖然這項研究將限於技術分析方法,但從今後工作的角度來看,其他股票分析技術也是必不可少的。

論文摘要翻譯:技術分析評論

Often technical analysis is criticized by researchers for its inadequacy towards validation scientifically and statistically. Technical analysts, in response often argued that this method is a pragmatic approach but has its major interest in what is able to work in comparison to present theory. The fact still remains however that various methods in technical research have higher subjectivity and researchers claim often that patterns for price and indicators utilized by technical analysis practitioners is more in the perspective and beholder’s eye. However, vividly, practitioners continue portraying the technical analysis utility and how famous it is ever since the past decade. Most notably this is seen through the perspective that most main newspapers now are posting advice from stocks depending upon technical method as analysis and some firm brokerage. Research over technical analysis profitability, furthermore, has increased in terms of volume and statistical significance during the last decade itself. Park et al (2007), in a research paper review submitted by them tried to analyse the profits potential generation through technical based analysis. They searched that studies in the modern world depict that technical method as analysis consistently helps in generating profitability returns in several markets speculated.
Technical analysis however seems to be the most valuable approach for automating with a PC as prices of stock are available readily. As many indicators, furthermore, within technical analysis involve uncertainty and they have problem in interpreting pure methods of analytical nature. This seems like a domain which is properly suited for AI (Artificial intelligence) and learning through machinery. Although, the study will be limited to technical analysis methods, other techniques for stock analysis are also essential from the future work perspective.

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