- 學位論文
股市多層次技術分析知識平台之實作
Multi-Level Technical Analysis Knowledge System Platform for Stock Market
摘要
投資股票為大多數投資者不可或缺的重要工具，如何找出投資股市中提升績效的通用知識是相當有意義且重要的研究。本研究設計出多層次過濾機制的知識平台，每個層次皆能讓使用者自行選擇不同類型的技術知識設定，再使用最終層的買賣策略知識。該知識平台能讓使用者能快速地透過技術指標及買賣策略的知識組合找出最佳的參數。並以此平台來驗證過去學者在技術指標使用上的投資績效是否在不同的時空背景下是否有效。 本研究驗證中發現，黃紹輔的三重過濾系統在趨勢向下的期間一上表現較好，期間二則是以張清良的KD隨機指標參數較好，總期間則是以張清良的KD隨機指標參數績效最高。為了進一步研究出更有效的技術指標參數，我們透過此平台找出績效更佳的參數設定藉此找出最佳組合。
並列摘要
Investing in stocks is an indispensable and vital way for most investors. Therefore, ways to find out the secrecy of improving the performance of such investment is absolutely important. This study implements a multi-level filtering mechanism knowledge platform for investing in stocks. Each level allows users to choose an appropriate technical knowledge setting, then use the trading strategies in the final level. The knowledge platform allows users to find quickly the combination of knowledge settings, trading strategies, and the effects. As a study, we verify the knowledge settings among several researches by using the system. As a result, we found that Huang Shao Fu’s triple filtration system in a downward trend get better performance. In the upcoming trend, the knowledge settings provided by Zhang Qing Liang by using KD Stochastic parameters is better. Finally, we tuned the KD Stochastic parameters and find a best combination for investment in the period.