「區間漲跌幅投資策略」的探討：以台灣股市為例; “the specific range for buy and sell strategy” in Taiwan stock market

NCUIR > School of Management at National Central University > Graduate Institute of Finance > Electronic Thesis & Dissertation > Item 987654321/12218

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/12218

Title:	「區間漲跌幅投資策略」的探討：以台灣股市為例;“the specific range for buy and sell strategy” in Taiwan stock market
Authors:	許雅琳;Ya-lin Hsu
Contributors:	財務金融研究所
Keywords:	投資策略;台股;trading model;program trading strategy
Date:	2007-09-26
Issue Date:	2009-09-22 14:42:38 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	本研究以「區間漲跌幅投資策略」之機械化操作在台灣股票市場進行模擬操作，試圖運用這樣的一個操作模型，克服一般投資人在交易時的心理偏誤，能獲得合理的投資報酬率。實證結果所得，十六組的參數組合中以「-5%買進：+5%賣出」策略的可行性最高。然而，本研究實際操作所達成的6.38%之投資報酬率，若以絕對報酬而非相對報酬的績效來作衡量，這樣的結果無法滿足多數的投資人需求，且操作策略容易被其他投資工具所取代。故以區間漲跌幅的機械化操作模型運用於台灣股市進行投資並沒有成功。事實上，每一種操作模型都有其特性及適合的市場，要如何設計出能夠獲利的交易策略，仍有賴於人為的對市場的看法。此種機械化操作模型的方式，最終目的只在於確實地執行交易策略。由於本操作模型的架構只是一個程式交易策略的前段雛型，本研究最終目的，是未來此操作策略若可以在核心操作邏輯、買賣點的設定、交易規則、選股方法等方面進行改善，期許未來能修正成可行的策略以運用於股票市場。 This research adopts the mechanized operation carrying on the simulation trading by “the specific range for buy and sell strategy” in Taiwan stock market. It attempts to construct such a trading model, to overcome the general investor's psycho-behavioral deviation during trading, and to obtain the reasonable investment return. Amount 16 group of parameter combinations, the final test result of “-5% buys；+5% sells” strategy has the highest feasibility. However, 6.38% investment return achieved by, this research actual operation , can not satisfy most investors if by the measure of absolute return, but the relative return; particularly when the trading strategy is easily replaced by other investment tools. Therefore, we did not adopt “the specific range for buy and sell strategy” successfully. In fact, each kind of model reveals characteristics, and it only works in the appropriate market. For designing a profitable trading strategy, it still depends on the mankind’s view on the market. The final goal of such mechanized trading model is to exactly execute the trading strategy. As the structure of this trading model is only a simple forepart of a program trading strategy, the ultimate purpose of this research is improving on core trading logic, timing of buy and sell, trading rules, stock selections, and so on. We hope that the model can be reconstructed a feasible strategy to work in the stock market in the near future.
Appears in Collections:	[Graduate Institute of Finance] Electronic Thesis & Dissertation

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