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臺灣股票市場技術指標之研究─不同頻率資料績效比較

The Study on the Technical Indicator of Taiwan Stock Market-Using Different Data Frequencies

摘要


本研究針對日、週、月及日內頻率台灣加權股價指數資料,在考量交易成本下,利用不同長、短週期的移動平均線(Moving Average, MA)與隨機指標(Stochastic Oscillator, KD)配置,其包含短線操作(5日、5週)、季報效應(60日、13週、3月)、半年報效應(120日、26週、6月)和年報效應(240日、52週、12月),探討台股市場獲利績效表現。實證結果顯示,以移動平均線作為買賣交易策略時,不論於日、週及月頻資料,均以季線型移動平均線發出的買賣訊號獲得較高的投資報酬率。本研究進一步以MA及KD組成雙指標組合,投資報酬則相對為佳,其中又以60日MA與9日KD組合績效在所有技術分析指標中獲利績效最佳。同時考量市場歷年重大事件造成之多、空時期,60日MA與9日KD組合績效不論在多頭或空頭均可獲得穩健的獲利結果。最後,針對日內資料再作驗證,仍以60根分時MA與9根分時KD雙指標操作績效最佳,再次印證本文雙指標投資績效的優越性。總合本文結果,印證技術指標可獲超額報酬,運用雙指標判斷可獲得較佳績效,說明投資者可參考不同技術指標之頻率組合而獲得績效較佳之買賣時點。

並列摘要


In this paper, we employ daily, weekly, monthly and intra-day data of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) with application of the Moving Average Line (MA) and Stochastic Oscillator (KD) to analyze differences in investment performances under particular technical indicator. The transaction costs are taken into consideration in our research and the following Moving Average Lines are applied: 5 days (5 weeks)-MA, 60 days(13 weeks, 3 months)-MA, 120 days(26 weeks, 6 months)-MA, 240 days(52 weeks, 12 months)-MA. These MA Lines represent the short-term trading, quarterly report effect, semi-annual report effect, and annual report effect respectively. The results show that while using MA as short-term trading strategy, the quarterly characterized indicators cause better total and average returns for each data frequency. By combining both MA and KD as dual-indicators, we observe that the indicators composed of quarterly MA and KD with daily frequency obtain the highest return. Moreover, the result indicates that both quarterly MA and the dual-indicators perform well when taking bullish and bearish market conditions into account. We also find that the dual-indicators with intra-day frequency have the best market returns. Comparing with low-frequency data, the indicators with high frequency do achieve better annual return. In conclusion, we examine that trading strategies for getting excess returns can be implemented by using technical indicators; and superior investment performances are realizable when adopting dual-indicators as referrals. Our findings confirm that analysis on both technical indicators and data frequencies suggests investors in searching for better trading timing.

參考文獻


Dickey D.A., and Fuller, W.A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49, 1057-1072.
Edwards, R.D., Magee, J., and Bassetti, W.H.C. (2001). Technical Analysis of Stock Trend, 8th ed., New York:St Lucie Press, Chapter 17.1, 303-310.
Eng, W.F. (1988). The Technical Analysis of Stock, Options and Futures: Advanced Trading Systems and Technioues. Chicago: Probus Publishing.
Engle, R.F., and Granger, C.W.J. (1987). Co-Integration and Error Correction: Representation, Estimation and Testing. Econometrica, 55, 1-87.
Fama, E.F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance, 25, 383-417.

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謝佩瑾(2016)。期貨投資組合交易策略應用之研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2016.00688
張恪清(2015)。全球期貨投資組合交易策略分析〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2015.00839
陳昱安(2015)。巨量資料探討及分析-以台灣50 ETF 為例〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2015.00346
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