Can an automated trading algorithm based on a graphical analysis present a good result?
DOI:
https://doi.org/10.22567/rep.v9i1.594Keywords:
Automated Trading. Technical Analysis. Fibonacci. Parabolic SAR.Abstract
Investments based on technical analysis have been used more frequently to examine the strategic performance of automated negotiations through an investment algorithm, in particular using parabolic SAR indicators and Fibonacci. This work used the scenario evaluation to later compare their results in relation to the buy and hold strategy. Scenarios differ from the use of risk factors, timeframes and price levels. Backrests were carried out for a period from January 20015 to April 2017 to compare the strategies. As a result, it was noticed that the use of technical analysis through automated trading can result in profits higher than buy and hold. However, such a form of trading presents a high level of volatility.
References
ABARBANELL, J. S. Do analyst’s earnings forecasts incoporate information in prior stock price changes?. Journal of Accounting and Economics, v.14, n. 2, p. 147-165, 1991.
BACEN - Banco Central do Brasil. Disponível em: < http:www.bcb.gov.br >. Acesso em 11/11/2017.
BHATTACHARYA, S.; KUMAR, K.. A computational exploration of the efficacy of Fibonacci Sequences in technical analysis and trading. Annals of Economics and Finance, v. 7, n. 1, p. 185, 2006.
BROWN, S. J.; GOETZMANN, W. N.; KUMAR, A. The Dow theory: William Peter Hamilton's track record reconsidered. The Journal of Finance, v. 53, n. 4, p. 1311-1333, 1998.
BRUNI, A. L.; FAMÁ, R. Eficiência, previsibilidade dos preços e anomalias em mercados de capitais: teoria e evidências. Caderno de Pesquisas em Administração, v. 1, n. 7, p. 71-85, 1998.
FAMA, E. F. The behavior of stock-market prices. The Journal of Business, v.38, n.1, p. 34-105, 1965.
FAMA, E. F. Efficient capital markets: A review of theory and empirical work. The Journal of Finance, v. 25, n. 2, p. 383-417, 1970.
FRANKEL, R.; LEE, C. M. Accounting valuation, Market expectation and cross-sectional stock returns. Journal of Accounting and Economics, v.25, n.3, p. 283-319, 1998.
GAUCAN, V. How to use Fibonacci retracement to predict forex market. Journal of Knowledge Management, Economics and Information Technology, v.1, n. 2, 2011.
LEE, S. J.; AHN, J. J., OH, K. J.; KIM, T. Y. Using rough set to support investment strategies of real-time trading in futures market. Applied Intelligence, v. 32, n. 3, p. 364-377, 2010.
LEVICH, R. M.; THOMAS III, L. R. The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach. Journal of international Money and Finance, v. 12, n. 5, p. 451-474, 1993.
LO, A. W. Efficient markets hypothesis. In: BLUME, L.; DURLAUF, S. The New Palgrave: A Dictionary of Economics, ed. 2. New York: Palgrave McMillan, 2007.
NAN, X.; SUN, X. Automatic stock market forecasting system based on extended language template model. Journal of Information & Computational Science, v. 8, n. 1, p. 112-118, 2011.
NEELY, C. J.; WELLER, P. A. Technical trading rules in the European monetary system. Journal of International Money and Finance, v. 18, n. 3, p. 429-458, 1999.
NEELY, C.; WELLER, P.; DITTMAR, R. Is technical analysis in the foreign exchange market profitable? A genetic programming approach. Journal of Financial and Quantitative Analysis, v. 32, n. 04, p. 405-426, 1997.
OHLSON, James A. A synthesis of security valuation theory and the role of dividends, cash flows, and earnings. Contemporary accounting research, v. 6, n. 2, p. 648-676, 1990.
OSLER, C. L. Currency orders and Exchange rate dynamics: an explanation for the predictive success of technical analysis. The Journal of Finance, v. 58, n. 5, p.1791-1820, 2003.
PIOTROSKI, Joseph D. Value investing: The use of historical financial statement information to separate winners from losers. Journal of Accounting Research, v. 38. pp. 1-41, 2000.
ROBERTS, Harry V. Stock?Market “Patterns” And Financial Analysis: Methodological Suggestions. The Journal of Finance, v. 14, n. 1, p. 1-10, 1959.
SAMUELSON, Paul A. Proof That Properly Anticipated Prices Fluctuate Randomly. Industrial Management Review, v. 6, p. 41-49, 1965.
SHERSTOV, A. A.; STONE, P. Three automated stock-trading agents: A comparative study. In: International Workshop on Agent-Mediated Electronic Commerce. Springer Berlin Heidelberg, 2004. p. 173-187.
TEIXEIRA, L. A.; OLIVEIRA, A. L. I. A method for automatic stock trading combining technical analysis and nearest neighbor classification. Expert Systems With Applications, v. 37, n. 10, p. 6885-6890, 2010.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 Revista Eniac Pesquisa

This work is licensed under a Creative Commons Attribution 4.0 International License.




