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    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/118245
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/118245


    Title: 技術指標交叉策略之探究——以香港恆生指數期貨為例
    The Cross-Strategy of Technical Analysis: Evidence from Hong Kong Hang Seng Index Futures
    Authors: 蔡綿綿
    Cai, Mian-Mian
    Contributors: 廖四郎
    Liao, Szu-Lang
    蔡綿綿
    Cai, Mian-Mian
    Keywords: 技術指標
    交叉策略
    交易頻率
    買賣時間點
    Technical indicator
    Cross-strategy
    Trading frequency
    Time points of buying and selling
    Date: 2018
    Issue Date: 2018-07-03 17:27:22 (UTC+8)
    Abstract: 技術指標分析方法因其易於理解且操作簡單,在證券投資市場中扮演著重要角色。技術指標主要利用數據的波動來捕捉趨勢轉折點,但過多的短暫波動往往會誤導技術指標,釋放出錯誤的買賣信號,造成交易策略的損失。本文基於短暫性波動影響的考慮,探究改變交易頻率與買賣時間點,是否能夠減小波動的負面影響,使技術指標交叉策略獲得更好的報酬表現。
    本文以歷史悠久的恆生指數期貨為研究對象,在研究交易頻率時,採用常見的“黃金交叉”策略,即利用指標自身快慢線的交叉為買賣信號,對指數期貨的日資料、週資料、月資料進行實證研究,以觀察降低交易頻率,是否能夠減少短暫性波動的負面影響,幫助技術指標捕捉到精確的買賣訊號。從結果可以看到,記憶力長短不同的技術指標,最佳交易頻率也不相同。對於短記憶指標(KD、RSI)的黃金交叉策略,其在月資料的交易頻率下表現最好,對於長記憶期指標(MACD、DMI)的黃金交叉策略,其在週資料的交易頻率下表現最好。
    在研究買賣時間點的影響時,利用長、短記憶指標對波動敏感度不同的特點,構造“混合交叉”策略,即以短記憶指標的黃金交叉作為買點,長記憶指標的死亡交叉作為賣點,以避免短暫波動過早地釋放賣出訊號,喪失大波段漲幅。實證表明,在日交易頻率下,技術指標“混合交叉”策略表現均比單獨指標策略要好,說明用長短記憶指標改變買賣時間點,可以減少短暫波動的影響,提升報酬表現。
    The technical indicator plays an important role in the stock market because of its easy understanding and simple operation. Technical indicators mainly use the fluctuations of data to capture the turning points of trends, but many short-term fluctuations often mislead technical indicators, releasing the wrong trading signals and resulting in the loss of trading strategies. Therefore, this paper studies whether changing the trading frequency and the time points of buying and selling can reduce the negative effects of fluctuations, and enhance the performance of the cross-strategy of technical indicators.
    This paper takes the Hang Seng Index futures as the research object. When studying the trading frequency, it adopts the common “golden cross” strategy, which uses the intersection of the indicator’s own fast and slow lines as the buying and selling signals. Daily data, weekly data and monthly data are used for empirical research to observe whether lowering of trading frequency can reduce the negative impact of transient fluctuations and help the technical indicators capture accurate trading signals. From the results, we can see that the technical indicators with different lengths of memory have different optimal trading frequencies. For the golden cross strategy of short-memory indicators (KD, RSI), it performs best using monthly data. For the long-memory indicators (MACD, DMI), the gold cross strategy performs best using weekly data.
    When studying the time points of buying and selling, we construct a “mixed cross” strategy because the long-memory and short-memory indicators have different sensitivity to fluctuations. The golden cross of the short-memory indicator is used as a buying point and the death cross of the long-memory indicator is used as a selling point, to avoid releasing sell signal early because of the short-term fluctuations, and losing large-band gains. The empirical results show that the performance of the “mixed cross” strategy is better than that of the indicator’s respective cross strategy under the daily transaction frequency, which means that changing the time points of buying and selling by mixing the long and short memory indicators, can reduce the impact of transient fluctuations and improve the performance of the returns.
    Reference: 丁毅(2012)。MACD指標在A股市場中有效性檢驗。未出版之碩士論文,西南財經大學,金融學系,成都市。
    王兆軍(2001)。相對強弱指數的最佳參數組合。經濟數學,18(2),23-31。
    王勁松(2010)。股市常用技術分析方法的有效性實證研究。未出版之碩士論文,西南財經大學,統計學系,成都市。
    石赛男(2011)。股票技术分析中MACD指标的有效性检验。未出版之碩士論文,西南財經大學,金融學系,成都市。
    吳德生(2006)。技術分析對香港股市有效性之探討——以KD、MACD、MA、RSI為技術指標。未出版之碩士論文,國立臺北大學,企業管理學系,台北市。
    高梓森(1994)。臺灣股市技術分析之實證研究。未出版之碩士論文,國立臺北大學,財務金融學研究所,台北市。
    陸昱廷(2014)。我國股票市場技術分析交易策略實證研究。未出版之碩士論文,復旦大學,金融學系,上海市。
    鐘以恂(2013)。應用MACD及RSI為技術指標於台灣加權指數、日經225及香港恆生指數。未出版之碩士論文,國立政治大學,國際經營貿易研究所,台北市。
    Bessembinder, H., & Chan, K. (1995). The profitability of technical trading rules in Asian stock markets. Pacific-Basin Finance Journal, 3(2): 257-284.
    Brock, W., Lakonishok, J, & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5):1731-1764.
    Elliott, R. N. (2013). Nature's law: The secret of the universe, Los Angeles: Alanpuri Trading,.
    Fama, E. F. (1970). Efficient capital markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2):383-417.
    Fama, E. F. (1991). Efficient capital markets: II. The Journal of Finance, 46(5):1575-1618.
    Marshall, B. R., Cahan, R. H., & Cahan, J. M. (2008). Can commodity futures be profitably traded with quantitative market timing strategies? Journal of Banking and Finance, 32(9):1810–1819.
    Park, C. H., & Irwin, S. H. (2007). What do we know about the profitability of technical analysis? Journal of Economic Surveys, 21(4):786–826
    Robert, R. (1993). The Dow theory: an explanation of its development and an attempt to define its usefulness as an aid in speculation, Burlington VT: Fraser.
    Tharavanij, P., Siraprapasiri, V., & Rajchamaha, K. (2015). Performance of technical trading rules: evidence from Southeast Asian stock markets. SpringerPlus, 4(1):1-40
    William, P. H. (1960). The stock market barometer: a study of its forecast value based on Charles H. Dow's theory of the price movement. With an analysis of the market and its history since 1897, New York: R. Russell Associates
    Description: 碩士
    國立政治大學
    金融學系
    105352042
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G1053520421
    Data Type: thesis
    DOI: 10.6814/THE.NCCU.MB.002.2018.F06
    Appears in Collections:[金融學系] 學位論文

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