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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/76437


    Title: 以技術指標建構市場指標投資台灣股票市場
    The Optimal Asset Allocation in Taiwan Stock Market: Using Technical Analysis as Market Indicator
    Authors: 賴欣沅
    Lai, Hsin Yuan
    Contributors: 黃泓智
    賴欣沅
    Lai, Hsin Yuan
    Keywords: 技術指標
    綜合信號指標
    資產配置
    Regular Vine Copula
    Technical Indicator
    Combined Signal Approach
    Asset Allocation
    Regular Vine Copula
    Date: 2015
    Issue Date: 2015-07-13 11:09:49 (UTC+8)
    Abstract: 許多新興風險隨著金融市場的變化而產生,以致於發生許多大型金融災害造成許多金融產業蒙受鉅額損失。而於金融市場尋求利潤已是金融產業重要的一環,有鑑於此,本論文提出ㄧ套完整的資產配置流程,利用技術指標建構綜合信號指標作為市場指標再選擇投資資產並估計、模擬、最適化投資權重並投資,以達到規避大型金融事件風險並獲取超額利潤。本論文亦嘗試不同股票評分指標、股票資產模型、結構模型、投資組合大小等組合,以找出最適合台灣股票支股票評分指標、資產模型以及投資組合大小。
    本論文發現綜合信號指標作為市場指標可有效判讀金融事件的發生與結束時間,經由此指標判斷可獲得相當的超額利潤。本論文亦發現當投資組合為5支股票、資產模型為GJR GARCH(1,1)模型、相關結構型態為多元高斯Copula時可獲得超額利潤。
    Reference:  Aas, K., Czado, C., Frigessi, A., & Bakken, H. (2009). Pair-copula constructions of multiple dependence. Insurance: Mathematics and Economics, 44(2), 182-198.
     Bertrand, P., & Prigent, J.-l. (2011). Omega performance measure and portfolio insurance. Journal of Banking & Finance, 35(7), 1811-1823.
     Chavarnakul, T., & Enke, D. (2008). Intelligent technical analysis based equivolume charting for stock trading using neural networks. Expert Systems with Applications, 34(2), 1004-1017.
     Esfahanipour, A., & Mousavi, S. (2011). A genetic programming model to generate risk-adjusted technical trading rules in stock markets. Expert Systems with Applications, 38(7), 8438-8445.
     Friesen, G. C., Weller, P. A., & Dunham, L. M. (2009). Price trends and patterns in technical analysis: A theoretical and empirical examination. Journal of Banking & Finance, 33(6), 1089-1100.
     Hitaj, A., Corazza, M., & Pizzi, C. (2014). Portfolio allocation using Omega function: An empirical analysis Mathematical and Statistical Methods for Actuarial Sciences and Finance.
     Ingersoll, J., Spiegel, M., Goetzmann, W., & Welch, I. (2007). Portfolio Performance Manipulation and Manipulation-proof Performance Measures. The Review of Financial Studies, 20(5), 1503-1546.
     Lam, M. (2004). Neural network techniques for financial performance prediction: integrating fundamental and technical analysis. Decision Support Systems, 37(4), 567-581.
     Leigh, W., Purvis, R., & Ragusa, J. M. (2002). Forecasting the NYSE composite index with technical analysis, pattern recognizer, neural network, and genetic algorithm: a case study in romantic decision support. Decision Support Systems, 32(4), 361-377.
     Lento, C. (2008). A Combined Signal Approach to Technical Analysis on the S&P 500. Rochester: Social Science Research Network.
     Lento, C. (2009). Combined signal approach: evidence from the Asian–Pacific equity markets. Applied Economics Letters, 16(7), 749-753.
     Levich, R. M., & Thomas Iii, L. R. (1993). The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach. Journal of International Money and Finance, 12(5), 451-474.
     Mohanram, P. (2005). Separating Winners from Losers among LowBook-to-Market Stocks using Financial Statement Analysis. Review of Accounting Studies, 10(2-3), 133-170.
     Neely, C. J., & Weller, P. A. (1999). Technical trading rules in the European Monetary System. Journal of International Money and Finance, 18(3), 429-458.
     Neely, C. J., & Weller, P. A. (2003). Intraday technical trading in the foreign exchange market. Journal of International Money and Finance, 22(2), 223-237.
     Potvin, J.-Y., Soriano, P., & Vallée, M. (2004). Generating trading rules on the stock markets with genetic programming. Computers & Operations Research, 31(7), 1033-1047.
     Rossello, D. (2015). Ranking of investment funds: Acceptability versus robustness. European Journal of Operational Research, 245(3), 828-836. Wang, J.-L., & Chan, S.-H. (2007). Stock market trading rule discovery using pattern recognition and technical analysis. Expert Systems with Applications, 33(2), 304-315.
     Zakamouline, V., & Koekebakker, S. (2009). Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance. Journal of Banking & Finance, 33(7), 1242-1254.
     Lento, Camillo, Tests of Technical Trading Rules in the Asian-Pacific Equity Markets: A Bootstrap Approach. Academy of Financial and Accounting Studies Journal, Vol. 11, No. 2, 2007.
    Description: 碩士
    國立政治大學
    風險管理與保險研究所
    102358021
    103
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0102358021
    Data Type: thesis
    Appears in Collections:[風險管理與保險學系] 學位論文

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