技術指標與股價漲跌幅非線性關係之獲利能力之探討__臺灣人文及社會科學引文索引資料庫

:::

詳目顯示

第 1 筆 / 總合 1 筆

/1頁

來源文獻資料
摘要
外文摘要
引文資料

題名：	技術指標與股價漲跌幅非線性關係之獲利能力之探討
書刊名：	臺灣管理學刊
作者：	林金賢／李淑惠
作者(外文)：	Lin, Chin-shien／Lee, Shu-hui
出版日期：	2006
卷期：	6:1
頁次：	頁129-156
主題關鍵詞：	效率市場；類神經模糊；馬克維茲投資組合；Efficient market；Neuro fuzzy；CRISMA；Markowitz portfolio
原始連結：	連回原系統網址
相關次數：	被引用次數:期刊(4) 博士論文(1) 專書(0) 專書論文(0) 排除自我引用:4 共同引用:0 點閱:114

股票之均衡價格決定於股票之供需力道，而供需力道之改變將造成均衡價格之改變。然而由於投資者獲取資訊之成本與速度不同，造成市場上資訊之不對稱，因而產生了套利機會。本研究認為如果能夠經由適當之工具將技術指標與股價漲跌幅間較諸經驗法則更加複雜之關係粹取出來，由於此較為複雜的交易規則將使資訊不對稱之情況更加明顯，使得有能力挖掘此關係者可發掘更多的套利機會，進而產生更多的超額報酬。過去的研究大部分針對技術指標本身之獲利性作探討，本研究則針對CRISMA技術指標與股價漲跌幅間之關係利用類神經模糊技術作進一步之探索，以臺灣摩根成份股作為驗證對象。實證結果顯示，CRISMA交易系統在臺灣股市仍然可以獲取超額報酬，對股票市場資訊充分流通之假設提出一大質疑；而利用類神經模糊粹取出之交易規則較諸原來的交易規則可以產生更多的超額報酬，似乎意味著較複雜之關係確可帶來更多的超額報酬。除此，利用粹取出之交易規則所產生之訊號來建構之投資組合，除了平均報酬率與Sharpe ratio顯著的優於指數法所建構之被動投資組合（passive portfolio）外，在六種不同之投資組合建構方法中具有最高的Sharpe ratio，而且也較諸同期間九十九支開放式股票型基金淨值報酬最優之前十名有較高之Sharpe ratio。對較複雜的交易系統將使得資訊不對稱之情況更加明顯而使得該交易系統可以產生較多超額報酬之假說，本研究之實證結果提供一有利之證據。

以文找文

The equilibrium stock price is determined by the interaction of supply and demand. A change of demand or supply will change the equilibrium price. However, the arbitrage opportunity happens during the price change when the information asymmetry exists due to the difference of cost and speed among the investors to acquire the information in the market. This research aims to exploit the nonlinear relationship between the technical indexes and stock price change by using neuron fuzzy to obtain excess returns. The empirical results show that the CRISMA trading system can still obtain excess return in Taiwan stock market, which questions the rapid price adjustment hypothesis. Besides, the rate of return from the neuron fuzzy system is better than that of the original CRISMA trading system, which implies that a more complicated trading system could get more excess return due to the information asymmetry. The portfolio constructed by neuron fuzzy has the highest Sharpe ratio among the six strategies in addition to beating the passive portfolio constructed by the index method. When compared with the top 10 funds with the best return within the same period, neuron fuzzy still ahs the highest Sharpe ratio. This research provides an empirical evidence to support the hypothesis that the more complicated the trading system is the harder the information pass among the investors in the market, and therefore, the more the excess return is.

以文找文

期刊論文
1.	Pruitt, S. W.、White, R. E.(1988)。The CRISMA trading system: who says technical analysis can not beat the market?。Journal of Portfolio Management，14(3)，55-58。
2.	Buckley, J. J.、Hayashi, Y.(1994)。Fuzzy Neural Networks: A Survey。Fuzzy Sets and Systems，66(1)，1-13。
3.	Chiang, W. C.、Urban, T. L.、Baldridge, G.(1996)。A neural network approach to mutual fund net asset value forecasting。Omega Int. J. Mgmt. Sci.，24(2)，205-215。
4.	Fama, Eugene F.、Blume, Marshall E.(1966)。Filter Rules and Stock Market Trading Profits。The Journal of Business，39(1 Part 2)，226-241。
5.	Fama, Eugene F.、French, K. R.(1998)。Market Efficiency, Long-Term Returns, and Behavioral Finance。Journal of Financial Economics，49(3)，283-306。
6.	Conrad, Jennifer、Kaul, Gautam(1998)。An Anatomy of Trading Strategies。The Review of Financial Studies，11(3)，489-519。
7.	Tam, Kar Yan、Kiang, Melody Y.(1992)。Managerial Applications of Neural Networks: The Case of Bank Failure Predictions。Management Science，38(7)，926-947。
8.	Brock, William、Lakonishok, Josef、LeBaron, Blake(1992)。Simple Technical Trading Rules and the Stochastic Properties of Stock Returns。The Journal of Finance，47(5)，1731-1764。
9.	Fama, E. F.(1965)。The behavior of stock market prices。Journal of Business，38(1)，34-105。
10.	Sharpe, William F.(1966)。Mutual fund performance。Journal of Business，39(1)，119-138。
11.	Bessembinder, Hendrik、Chan, Kalok(1995)。The Profitability of Technical Trading Rules in the Asian Stock Markets。Pacific-Basin Finance Journal，3(2/3)，257-284。
12.	Rouwenhorst, K. Geert(1998)。International Momentum Strategies。The Journal of Finance，53(1)，267-284。
13.	Zadeh, Lotfi Asker(1965)。Fuzzy sets。Information and Control，8(3)，338-353。
14.	Fama, Eugene F.(1970)。Efficient Capital Markets: A Review of Theory and Empirical Work。The Journal of Finance，25(2)，383-417。
15.	Brown, Stephen J.、Warner, Jerold B.(1985)。Using Daily Stock Returns: The Case of Event Studies。Journal of Financial Economics，14(1)，3-31。
16.	Bolloju, N.,(1996)。Formulation of qualitative models using fuzzy logic。Decision Support Systems，vol. 17，275-298。
17.	Chirinko, R. S., Guill, G. D., and Hebert, P.,(1991)。Developing a systematic approach to credit risk management。Journal of Retail Banking，13( 3)，29-37。
18.	Elder, A.,(1987)。Using stochastics to catch early trends and reversals。Futures，16(6)，68-72。
19.	Fama, E. F.,(1991)。Efficient Capital Makets II。Journal of Finance，vol. 46，1575-1618。
20.	Fernandez-Rodriguez, F., Gonzalez-Mattel, C., and Sosvilla-Rivero, S.,(2000)。On the profitability of technical trading rules based on artificial neural networks: Evidence from the Madrid stock market。Economics Letters，vol. 69，89-94。
21.	Foster, B., Collopy, F., and Ungar, L.,(1992)。Neural network forecasting of short, noisy time series。Computers and Chemical Engineering，16, Vol. 12，293-297。
22.	Gencay, R.,(1998)。The predictability of security returns with simple technical trading rules。Journal of Empirical Finance，vol. 5，347-359。
23.	Gorman R. P., and Sejnowski, T. J.,(1988)。Analysis of hidden units in a layered network trained to classify sonar targets。Neural Networks，1(1)，76-90。
24.	Hudson, R., Dempsey, M., and Keasey, K.,(1996)。A note on the weak form efficiency ofcapital markets: The application of simple technical trading rules to UK stock price --- 1935 to 1994。Journal of Banking & Finance，vol. 20，1121-1132。
25.	Jacobs, B., and Levy, K.,(1989)。The complexity of the stock market。The Journal of Portfolio Management，vol. 16。
26.	Jensen, M. C.(1967)。Random Walks: Reality or Myth--Comment。Financial Analysts Journal，23，77-85。
27.	Kaneko, T.,(1996)。Building a financial diagnosis system based on fuzzy logic production system。Computers in Industrial Engineering，vol. 31, 3/4，743-746。
28.	Levy, R. A.,(1966)。Conceptual Foundations of Technical Analysis。Financial Analysts Journal，vol. 22，83。
29.	Mckim, R. A.,(1993)。Neural network applications to cost engineering。Cost Engineering，vol. 35，31-35。
30.	Michitaka, K.,(1991)。Applications of fuzzy logic/neural network to securities trading decision support system。1991 IEEE International Conference on Systems, Man, and Cybernetics. `Decision Aiding for Complex Systems，Oct，1913-1919。
31.	Parisi, F., and Vasquez, A.,(2000)。Simple technical trading rules of stock returns: evidence from 1987 to 1998 in Chile。Emerging Markets Review，vol. 1，152-164。
32.	Pruitt, S. W., and White, R. E.,(1989)。Exchange-traded options and CRISMA trading。The Journal of Portfolio Management，15 (4)，55-56。
33.	Pruitt, S. W., Maurice, T. K. S., and White, R. E.,(1992)。The CRISMA Trading System: The Next Five Years。The Journal of Portfolio Management，18(3)，22-25。
34.	Ranaweera, D. K., Hubele, N. F., and Karady, G. G,(1996)。Fuzzy logic for short term load forecasting。Electrical Power & Energy Systems，vol. 18, 4，215-222。
35.	Shaout, A., and Al-Shammari, M.,(1998)。Fuzzy logic modeling for performance appraisal systems: A framework for empirical evaluation。Expert systems with Applications，vol. 14，323-328。
36.	Stoeva, S. P.,(1992)。A weight-learning algonthm for fuzzy production systems with weighting coefficients。Fuzzy Sets and Systems，vol. 48，87-97。
37.	Sweeny R.J.(1986)。Beating The Foreign Exchange Market。Journal of Finance，vol. 41，163-182。
38.	Zimmerman, H.-J. and Thole, U.,(1978)。On the suitability of minimum and product operators for the intersection of fuzzy sets。Fuzzy Sets and Systems，vol. 2，173-186。

會議論文
1.	Kimoto, T., Asakawa, K., Yoda, M., and Takeoka, M.,(1990)。Stock Market Prediction System with Modular Neural Networksvol. 1，1-6。

研究報告
1.	Cottrell, G. W., Munro, P., and Zipser, D.,(1987)。Image compression by back propagation: An example of extensional programming。San Diego. CA.。
2.	Lapedes and Farber,(1987)。Nonlinear signal processing using neural networks: Prediction and system modeling。

學位論文
1.	Werbos, P.(1974)。Beyond regression: New tools for prediction and analysis in the behavioral sciences(博士論文)。University of Harvard。

圖書
1.	Markowitz, Harry M.(1959)。Portfolio Selection: Efficient Diversification of Investment。New York：Wiley。
2.	Inform Software Corporation(1993)。Fuzzy Tech 3.0 Explorer Edition Manual and Reference Book。Evanston. IL.：Inform Software Corporation。
3.	Granville, J.,(1963)。Granville’s new key to stock market profits。Englewook Cliff, NJ：Prentioe Hall。
4.	Kosko, B. J.(1992)。Neural Networks and Fuzzy Systems: A Dynamic Systems Approach to Machine Intelligence。Englewood Cliffs, New Jersey：Prentice-Hill。
5.	Edwards, R. D., and Magee, J.,(1966)。Technical Analysis of Stock Trends, 5th edition。Boston, MA。
6.	Frost, A. J., and Prechter, R. R.,(1978)。Elliott Waave Principle, Key to Stock Market Profits。Chappaqua, NY。
7.	Lin, C-T, and Lee, G.,(1996)。Neural fuzzy system, a neuro-fuzzy synergism to intelligent systems。Englewood Cliffs, N.J.。
8.	McClelland, J., and Rumeihart, D.,(1986)。Parallel Distributed Processing。Cambridge, MA。
9.	Murphy, J. J.,(1986)。Technical Analysis of the Futures Markets。New York Institutue of Finance。
10.	Nauck, D., and Kruse, R.,(1996)。Designing neuro-fuzzy systems through backpropagatio。Fuzzy Modelling: Paradigms and Practice。Boston。
11.	Nauck, D., and Kruse, R.,(1996)。Neuro-Fuzzy Systems Research and Applications outside of Japan。Fuzzy-Neural Networks, Soft Computing series。Tokyo。
12.	Patel, C.,(1980)。Technical Trading Systems for Commodities and Stocks, Trading Systems Research。California。
13.	Pedrycz, W., and Card, H. C.,(1992)。Linguistic Interpretation of Self-Organizing Maps。IEEE Int. Conf. On Fuzzy Systems。San Diego, CA.。
14.	Von Altrock. C.,(1997)。Fuzzy Logic and NeuroFuzzy Application in Business and Finance。Upper Saddle River, N.J。
15.	Williams, L.,(1973)。How I Made One Million Dollars in the Commodity Market Last Year。Conceptual Management。Monterey, CA。

推文
推薦
引用網址
引用嵌入語法
轉寄

top

:::

相關期刊
相關論文
相關專書
相關著作
熱門點閱

1.	智慧資本衡量指標之研究：以無線射頻辨識系統廠商為例
2.	臺灣股票市場技術指標之研究--不同頻率資料績效比較
3.	影響大盤與衍生性金融商品成交量因素之探討與分析
4.	融資、融券餘額、外資買賣超對臺灣股價影響--分量迴歸之應用

1.	修正隨機優勢理論—以台灣股票市場進行實證

無相關書籍

無相關著作

無相關點閱

QR Code

臺灣人文及社會科學引文索引資料庫系統

詳目顯示

臺灣人文及社會科學引文索引資料庫