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    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/50849
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/50849


    Title: 條件機率交易模型 - 台灣股票市場之實證研究
    Conditional probability trading model - empirical research for the stock market of Taiwan.
    Authors: 李培均
    Lee, Pei Chun
    Contributors: 李桐豪
    Lee, Tong Hao
    李培均
    Lee, Pei Chun
    Keywords: 包寧傑帶狀
    動態偏態
    回歸均數
    Bollinger bands
    dynanic skewness
    mean reversion
    Date: 2010
    Issue Date: 2011-09-29 16:50:37 (UTC+8)
    Abstract: 該篇文章中提出一個新的交易方式:條件機率交易模型conditional probability trading model。
    這個模型應用了三個主要的基本假設:
    (1)總體經濟因子和股價指數間有相關性。因此可以透過總經指標來衡量股市應有的合理價位。
    (2)股價具有回歸均數的特質。亦即股價一旦過度偏離基本價值,理論上會傾向回復到基本價值之上。
    (3)股價指數相對於基本價值線的距離,將會影響偏態係數的大小。

    根據以上三個性質,試圖建構出一個能夠捕捉股價指數變動的模型,並用以進行交易模擬,觀察其是否能獲取正報酬。
    The trading strategy, conditional probability trading model(CPTM), is presented in this article. We’ve tried to develop a new trading strategy which is built up by the combination of the properties which includes 1)the relationship between macroeconomic factors and stock market. 2) mean reversion and 3) conditional skewness. The conclusion implies that we may successfully find out a method to combine fundamental and technical analysis, if this method is proved effective. The former hypothesis is assumed that the different level of stock market index may stand for a specific condition of macroeconomic environment. Meanwhile, a better fundamental economic condition could reasonably create a higher stock market index, vice versa. By observing the fundamental value, we can figure out the market ,currently, is over-priced or under-priced. Next, we construct a trading model which is graphed like Bollinger bands. According to specific rules, it provides buying or selling signals. In some special situations, it can also forecast the turning points of the stock market precisely. 3) Skewness also plays a very important role in CPTM, because one of the hypothesis assumes that overpriced /underpriced stock market probably accompanies with left-skewed / right-skewed distribution of daily stock return. The hypothesis of dynamically adjusted skewness implies the concept that over-priced/under-priced stock market has higher propensity to decline/rise. To judge the trading timing is the core value in this model.
    Reference: Andreas Humpe and Peter Macmillan(2005),Can macroeconomic variables explain long term stock market movements?: A comparison of the US and Japan.
    Bai, J., and S. Ng. (2005). Test for skewness, kurtosis and normality for time series data.Journal of Business & Economic Statistics 23, 49–60.
    Belaire-Franch, J., and A. Peir´o. (2003). Conditional and unconditional asymmetry in U.S. macroeconomic time series. Studies in Nonlinear Dynamics & Econometrics 7, issue 1, article 4.
    Benjamin Graham (1934), Security Analysis.
    Balvers, Ronald J., Thomas F. Cosimano, and Bill McDonald, 1990,
    Predicting stock returns in an efficient market, Journal of Finance 45,
    1109-1128.
    Br¨ann¨as K., Nordman N. (2003b). Conditional skewness modelling for stock returns. Applied Economics Letters, 10, 725–728.
    Chan, Louis K. C., Narasimhan Jegadeesh, and Josef Lakonishok, 1996, Momentum strategies, Journal of Finance 51, 1681-1713.
    Campbell R. Harvey and Akhtar Siddique(2000), Conditional Skewness in Assets Pricing Tests., The Journal of Finance VOL. LV, NO. 3 • JUNE 2000
    Campbell R. Harvey and Akhtar Siddique(1999), Autoregressive conditional Skewness, The Journal of Financial and Quantitative Analysis, Vol. 34, No. 4 (Dec., 1999), pp.465-487
    Campbell R. Harvey, Akhtar Siddique(1999), Autoregressive Conditional Skewness,
    Campbell, J. Y., and L. Hentschel. (1992). No news is good news: an asymmetric model of changing volatility in stock returns. Journal of Financial Economics 31, 281–318.
    Cecchetti, Stephen, Pok-Sang Lam, and Nelson Mark, 1990, Mean reversion in equilibrium asset prices, American Economic Review 80, 398-418.
    Chen, J., H. Hong, and J. C. Stein. (2001). Forecasting crashes: trading volume, past returns and conditional skewness in stock prices. Journal of Financial Economics 61,345–381.
    Chopra, Navin, Josef Lakonishok, and Jay R. Ritter, 1992, Measuring abnormal performance: Do stocks overreact?, Journal of Financial Economics 31, 235-268.
    Conrad, Jennifer, and Gautam Kaul(1993), Long-term market overreaction or biases in computed returns?, Journal of Finance 48, 39-64.
    DeBondt, Werner, and Richard Thaler(1985), Does the stock market overreact?, Journal of Finance 40, 793-805.
    Fama, Eugene(1981), Stock returns , real activity, inflation and money, American Economic Review: 71:545-65
    Fama, E. F. & Schwert, G. W. (1977). Asset returns and inflation., Journal of Financial Economics, 5, 115-146.
    Fama, Eugene, and Kenneth French, 1988a, Permanent and temporary components of stock prices, Journal of Political Economy 96, 246-273.
    Flannery, M. J. & Protopapadakis, A. A. (2002). Macroeconomic factors do influence aggregate stock returns., The Review of Financial Studies, 15, 3, 751-782.
    Hueng, C. J., and J. B. McDonald. (2005). Forecasting asymmetries in aggregate stock market returns: evidence from conditional skewness. Journal of Empirical Finance 12,666–685.
    Jarque, Carlos M., and Anil K. Bera, 1980, Efficient tests for normality, heteroskedasticity and serial independence of regression residuals, Economics Letters 6, 255-259.
    Jegadeesh, Narasimhan, and Sheridan Titman, 1993, Returns to buying winners and selling losers: Implications for stock market efficiency, Journal of Finance 48, 65-91.
    Mark J. Flannery and Aris A. Protopapadakis (2002),Macroeconomic Factors Do Influence Aggregate Stock Returns.
    Mansor H. Ibrahim and Wan Sulaiman Wan Yusoff(2001), Macroeconomic Variables, Exchange Rate and stock price: a Malaysian perspective. IIUM Journal of Economics and Management.
    Nicolas Darvas(2007), How I made 2,000,000 in the stock market, Lightning source Inc., ISBN: 9562914534
    Serkan Yilmaz Kandir(2008), Economic Variables, Firm Characteristics and Stock Returns: Evidence from Turkey , International Research Journal of Finance and Economics.
    S. Chancharat, A. Valadkhani, C. Harvie(2007), The Influence of International Stock Markets and Macroeconomic Variables on the Thai Stock Market.
    John Bollinger(2002), Bollinger on Bollinger Bands,McGraw-Hill Companies, Inc. ISBN: 978-0-07-137368-5
    Kim, Myung Jig, Charles R. Nelson, and Richard Startz, 1991, Mean reversion in stock prices? A reappraisal of the empirical evidence, Review of Economic Studies 58, 515-528.
    Robert D. Gay(2008), Effect Of Macroeconomic Variables On Stock Market Returns For Four Emerging Economies: Brazil, Russia, India, And China, International Business & Economics Research Journal – March 2008 Volume 7, Number 3
    Ronald Balvers, Yangru Wu and Erik Gilliland(2000), Mean Reversion across National Stock Markets and parametric contrarian Investment Strategies , The Journal of Finance, Vol. 55, No. 2 (Apr., 2000), pp. 745-772
    Nai-Fu Chen, Richard Roll, Stephan A. Ross(1986), Economic forces and the stock market, The Journal of Business, Vol. 59, No. 3 (Jul., 1986), pp. 383-403
    Oliver Douglas Williams(2006), Empirical Optimization of Bollinger Bands for Profitability
    Chinese Essays中文論文
    吳慶忠(2005),金融與總體經濟變數對股票報酬之影響—Linear
    英文部分和STARX模型之比較分析,中原大學國際貿易學系
    Kai-Li Wang王凱立,Jai-Hui Lin林嘉慧(), A new parameter approach to modeling generalized autoregressive conditional density model at higher order moments.條件高階動差於財務金融市場之應用
    Description: 碩士
    國立政治大學
    金融研究所
    98352017
    99
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0098352017
    Data Type: thesis
    Appears in Collections:[金融學系] 學位論文

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