台灣股票市場交易風氣興盛，對於公開資訊的解讀向來有各種說法，使投資人難以判斷有效的資訊進而做出錯誤的決策。因此，本研究根據基本分析與技術分析的概念，試圖歸納出有系統的交易策略，讓投資人可以更有依據地去決定進出場時機點，減少不必要的投資損失。
　　一般市場所用的投資工具不外乎為基本分析和技術分析兩種，雖然兩種分析方法的立場不同，但並非為完全互斥。因此，本研究結合兩種分析方法，提出兩種交易策略。第一種策略針對Pruitt and White(1988)所提出的CRISMA交易策略作修正，考慮到四條不同長短的移動平均線具有不同的遞延性，再配合相對強弱指標與雙重移動平均線構成新的技術分析指標交易策略；第二種策略則基於趨勢的概念，找出股市的平均循環期間而形成的股市循環波段斜率策略。
　　本文研究期間自西元2002年至2011年止，樣本為台灣證券交易所上市之公司，主要探討此兩種交易策略，是否具有異常報酬。在考慮基本面與交易成本的情況下，實證結果發現，本研究所提出的兩種策略的確具有異常報酬，且基本分析能大幅減少交易成本以及損失的發生，有助於一般投資人減少不必要的風險。投資人應考慮到自身的風險承受程度設立出場的條件且嚴格執行，並以理性的態度去判斷市場的所有資訊，吸收更多的財務知識，找到最適合自己的投資策略，才能獲得穩定的投資績效。

In Taiwan, the stock market is filled with noise information and is prosperous in stock trading. Therefore, it is difficult for investors to make accurate and efficient trading decisions. In the current study, we try to form some trading strategies which are based on fundamental and technical analysis and hope that such strategies can provide investors a systematic stock investing decisions.
This study retrieves relevant information from financial statement which is later used by fundamental analysis and technical analysis. These methods are not mutual exclusive. The first strategy named technical analysis indicator strategy which revises CRISMA trading rules uses several indices, including four moving averages, relative strength index, and double moving average of volume. Second, based on the concept of trend, we find the average cycle period of the stock market and induce the second strategy named cycle strategy.
Our sample period ranges from 2002 to 2011, including all the listed firms. The goal of this paper is to examine whether the two strategies can get excess return. In our empirical finding, with the fundamental analysis and transaction cost, both strategies have excess return. It proves our strategies are useful. Also, fundamental analysis decreases many transaction cost and losses and actually reduces the risk and increase the possibility of earning profit overall. As a result, our strategies can get excess returns. Investors should set different cash-out points according to their risk tolerance and execute it strictly. Also, they should learn more relevant knowledge, make judge on all the information of the market in a rational manner, and find the most suitable investment strategy to generate stable returns.

李春旺，1988。股價行為與規模效應－台灣股票市場實證研究，國立政治大學企業管理研究所博士論文。
林天中，1997。台灣股票市場三因子：系統風險、公司規模及淨值市價比實證研 究，國立清華大學經濟研究所碩士論文。
林錦慧譯，2002。艾略特波浪理論－市場行為的關鍵，初版，眾文出版。原著Prechter, Robert Rougelot, & Frost, A. J. 2001. Elliott Wave Principle: Key to Market Behavior, John Wiley & Sons Inc.
周建新和陳振遠，2002。濾嘴法操作績效與台灣期貨市場效率性之研究，中華管理評論，第5卷，第4期，第104-119頁。
胡玉雪，1994。益本比、淨值市價比及公司規模對股票報酬之影響－相似無關迴 歸法之應用，國立台灣大學商學研究所碩士論文。
郭世豪，2006。結合財報資訊之二元信號投資模型－以台灣股票市場為例，國立 台灣科技大學企業管理學系碩士論文。
陳建良，1994。我國股票市場異常現象之實證研究。國立交通大學管理科學研究所碩士論文。
陳賢達，2008。技術分析在股票市場產生超額報酬可能性之實證探討-以寶來台灣50 ETF為例，國立台灣科技大學管理MBA碩士論文。
黃旭峰，2004。以技術分析法則與公司特性選股之投資績效，國立東海大學管理碩士學程在職進修專班碩士論文。
黃嘉斌譯，2000。金融市場技術分析，初版，寰宇出版。原著Murphy, John J. 1999. Technical Analysis of the Financial Markets, Prentice-Hall.
趙永昱，2002。技術分析交易法則在股市擇時之實證研究，國立中山大學財務金融研究所碩士論文。
鄭宜典，2007。基本分析與技術分析之投資績效比較，國立中興大學會計學研究 所碩士論文。
蔡尚儒，2000。台灣店頭市場技術分析的實證研究，國立中正大學財務金融研究所碩士論文。
蔡詩珉，2004。技術分析法則與公司特性之關聯性，中興大學財務金融研究所碩士論文。
寰宇財務顧問公司譯，1998。史瓦格期貨技術分析，初版，寰宇出版。原著Jack D. Schwager 1996. Schwager on Futures Technical Analysis.
謝宏鑫，2009。考量投資標的基本面、技術面分析並運用遺傳基因演算法決定最佳投資組合，國立台北大學企業管理學系碩士論文。
謝政遠，2004。以移動平均線、相對強弱指標與成交量檢驗台灣股票市場的效率 性，逢甲大學財務金融學系碩士班碩士論文。
謝劍平，2006。財務管理－新觀念與本土化，四版，智勝文化。
鍾惠民、吳壽山、周賓凰、范懷文，2002。財金計量，雙葉書局。
Abarbanell, J. S., & Bushee, B. J. (1997). Fundamental Analysis, Future Earnings, and Stock Prices. Journal of Accounting Research, 35(1), 1-24.
Ahmed, P., Beck, K., & Goldreyer, E. (2000). Can Moving Average Technical Trading Strategies Help in Volatile and Declining Markets? A Study of Some Emerging Asian Markets. Managerial Finance, 26, 49-62.
Alexander, Sidney S. (1961). Price Movements in Speculative Markets: Trends or Random Walks. Industrial Management Review, II, 7-26.
Antoniou, A., & Holmes P. (1995). Futures Trading, Information and Spot Price Volatility: Evidence for the FTSE-100 Stock Index Futures Contract Using GARCH. Journal of Banking and Finance, 19, 117-129.
Banz, Rolf W. (1981). The relationship between return and market value of common stocks. Journal of Financial Economics, 9(1), 3-18.
Barber, B. M., & Lyon, J. D. (1997). Detecting Long-run Abnormal Stock Returns: The Empirical Power and Specification of Test Statistics. Journal of Financial Economics,43, 341-372.
Basu, S. (1983). The Relationship between Earnings Yield, Market value and the Return for NYSE Stocks: Further Evidence. Journal of Financial Economics, 12(1), 129-156.
Bhardwaj, R. K., & Brooks, L. D. (1993). Dual Betas from Bull and Bear Markets: Reversal of the Size Effect. Journal of Financial Research, 16(4), 269-283.
Black, F., & Scholes, M. (1974). The Effects of Dividend Yield and Dividend Policy on Common Stock Prices and Returns. Journal of Financial Economics, 1(1), 1-22.
Blume, L., Easley, D., & O’Hara M. (1994). Market Statistics and Technical Analysis: The Role of Volume. Journal of Finance, 49(1), 153-181.
Brock, W., Lakonishok, J., & Lebaron, B. (1992). Simple Technical Trading 　　Rules and the Stochastic Properties of Stock Returns. Journal of Finance, 47, 1731-1764.
Bessembinder, H., & Chan, K. (1995). The Profitability of Technical Trading Rules in the Asia Stock Markets. Pacific-Basin Financial Journal, 3, 257-284.
Boehmer, E., Musumeci, J., & Poulsen, A. (1991). Event Study Methodology Under Conditions of Event Induced Variance, Journal of Financial Economics, 30, 253-272.
Cai, B. M., C. X. Cai, & Keasey, K. (2007). Influence of cultural factors on price clustering and price resistance in China's stock markets. Accounting and Finance, 47, 623-641.
Cohen, J. B., Zinbarg, E. D., & Zeikel A. (1973).Investment Analysis and Portfolio Management, Revised Edition.
Coutts, J. A., & Cheung, K. C. (2000). Trading Rules and Stock Returns: Some Preliminary Short Run Evidence from The Hang Seng 1985-1997. Applied Financial Economics, 10, 579-586.
Cowan, A. R. (1992). Nonparametric Event Study Tests. Review of Quantitative Finance and Accounting, 2(4), 343-58.
Cullen, L., & Christopher, T. (2002). Governance Disclosures and Firm Characteristics of Listed Australian Mining Company. International Journal of Business Studies, 10(1), 37-58.
Fabozzi, F. J., & Francis, J. C. (1977). Stability Tests for Alphas and Betas Over Bull and Bear Market Conditions. Journal of Finance, 32(4), 1093-1099.
Fabozzi, F. J., & Francis, J. C. (1979). Mutual Fund Systematic Risk for Bull and Bear Markets: An Empirical Examination. Journal of Finance, 34(5), 1243-1250.
Fama, E. F.,& Blume M. E. (1966). Filter Rules and Stock Market Trading. Journal of Business, 226-241.
Fama, Eugene F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance, 25(2), 383-417.
Fama, E. F., & French, K.R. (1992). The Cross-Section of Expected Stock Returns. Journal of Finance, 47(2), 427-465.
Fang, Y., Xu, D. (2002). The Predictability of Asset Returns: An Approach Combining Technical Analysis and Time Series Forecasts. International Journal of forecasting, 19, 369-385.
Gervais, S., Kaniel, R., & Mingelgrin, D. H. (2001). The High Volume Return Premium. Journal of Finance, 56(3), 877-919.
Goldberg, M. A., & Vora, A. (1981). The Inconsistency of the Relationship between Security and Market Returns. Journal of Economics and Business, 33, 97-107.
Goodacre, A., Bosher, J., Dove, A. (1999). Testing the CRISMA Trading System: Evidence from the UK Market. Applied Financial Economics, 9(5), 455-468.
Hall, P. (1992). On the Removal of Skewness by Transformation. Journal of the Royal Statistical Society. Series B (Methodological), 54(1), 221-228.
Hudson, R., Dempsey, M., & Keasey, K. (1996). A Note on The Weak Form Efficiency of Capital Markets The Application of Simple Technical Trading Rules to UK Stock Prices-1935 to 1994. Journal of Banking and Finance, 20, 1121-1132.
Jegadeesh, N.,& Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Market Efficiency. Journal of Finance, 48, 65-91.
Keim, Donald B. (1983). Size Related Anomalies and Stock Return Seasonality: Further Empirical Evidence. Journal of Financial Economics, 12(1), 13-32.
Kim, M. K., & Ismail, B. E. (1998). An Accounting Analysis of the Risk-Return Relationship in Bull and Bear Market. Review of Financial Economics, 7, 172-182.
Kim, M. K., & Zumwalt, J. K. (1979). An Analysis of Risk in Bull and Bear Markets. Journal of Finance and Quantitative analysis, 14(5), 1015-1025.
Kothari, S. P., Shanken, J., & Sloan, R. G. (1995). Another Look at the Cross-Section of Expected Stock Returns. Journal of Finance, 50(1), 185-224.
Lai, M. M., & Lau, S. H. (2006). The Profitability of the Simple Moving Averages and Trading Range Breakout in the Asian Stock Markets, Journal of Asian Economics, 17, 144-170.
Lakonishok, J., Shleifer, A., & Vishny, R. W. (1994). Contrarian investment, Extrapolation, and Risk. Journal of Finance, 49, 1541-1578.
Lindahl-steven, M. (1980). Redefining Bull and Bear Markets. Financial Analyst Journal,36, 76-77.
Marshall, B. R., Cahan, J. M., & Cahan, R. H. (2006). Is the CRISMA technical trading system profitable? Global Finance Journal, 17, 271–281.
Moosa, I., & Li, L. (2011). Technical and Fundamental Trading in the Chinese Stock Market: Evidence Based on Time-Series and Panel Data. Emerging Markets Finance and Trade, 47(1), 23-31.
Oberlechner, T. (2001). Importance of Technical and Fundamental Analysis in the European Foreign Exchange Market. International Journal of Finance and Economics, 6, 81-93.
Ou, J. A., & Penman, S. H. (1989). Financial Statement Analysis and the Prediction of Stock Returns. Journal of Accounting and Economics, 11, 295-329.
Piotroski, Joseph D. (2000). Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. Journal of Accounting Research, 38, 1-41.
Pruitt, S. W., & White, R. E. (1988). The CRISMA Trading System: Who Says Technical Analysis Cannot Beat the Market? Journal of Portfolio Management, 14, 55-58.
Pruitt, S. W., & White, R. E. (1989). The CRISMA Trading System: The Next Five Years. Journal of Portfolio Management, 14, 55-58.
Ratner, M., & Leal, R. (1999). Tests of Technical Trading Strategies in the Emerging Equity Markets of Latin America and Asia. Journal of Banking and Finance, 23, 1887-1905.
Roll, R., & Ross, S. A. (1980). An Empirical Investigation of the Arbitrage Pricing Theory. Journal of Finance, 35(5), 1073-1103.
Shleifer, A. (2000). Inefficient markets: An introduction to behavioral finance. Oxford, New York: Oxford University Press.
Sweeney, Richard J. (1988). Some New Filter Rule Tests: Methods and Results. Journal of Financial Quantitative Analysis, 23(3), 285-300.
Tain, G. G., Wan, G. H., & Guo, M. (2002). Market Efficiency and the Returns to Simple Technical Trading Rules: New Evidence from U.S. Equity Market and Chinese Equity Markets. Asia-Pacific Financial Markets, 9, 241-258.