Trades Return Based on Candlestick Charts in Tehran Stock Exchange

Document Type : Research Paper

Authors

1 Assistant Prof., Department of Finance, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.

2 M.Sc. Student, Department of Finance Engineering, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.

Abstract

Objective: Investors are always trying to predict stock prices in order to earn returns proportional to risk. One way to predict price is using candlestick charting which is common among analysts mainly due to its simplicity. So in this research we examine its profitability in different conditions.
Methods: For this purpose, daily stock price data of companies listed in Tehran Stock Exchange during 15 years from October 2003 to October 2018is used to calculate returns and winning rates of investment based on thirteen different candlestick charts in two horizon times of one day and ten days in different conditions of uptrends and downtrends for different turnover values.
Results: The research findings show that regardless of the trend or trading turnover, the sell candlestick, when holding for one day, and the buy candlestick, when holding for ten days, have the highest returns (more than transaction costs). By examining candlesticks in uptrends and downtrends their performance will improve. Buy candlestick in uptrends for companies with medium turnover value has the best return when holding for ten days if we consider the trading turnover value. The results of the research can also be considered as a recommendation for adopting a short-term outlook in the bearish periods.
Conclusion: Based on the findings, investors can use the mentioned patterns to gain returns in the Tehran Stock Exchange based on their preferred time horizon, as well as ascending and descending conditions among the companies with different trading turnover value.

Keywords


Afsharirad, E., Alavi, S.E., Sinaei, H. (2018). Developing an Intelligent Model to Predict Stock Trend Using the Technical Analysis. Financial Research Journal, 20(2), 249-264.
 (in Persian)
Asima, M., Ali Abbaszadeh Asl, A. (2019). Developing a Hybrid Model to Estimate Expected Return Based on Genetic Algorithm. Financial Research Journal, 21(1), 101-120. 
(in Persian)
Bashir Khodaparasti, R., Jahangardi, K., Boroomandzadeh, H., Saba, M. (2019). Comparison of the Efficiency of Technical Analysis Indicators in in the capital market periods of the boom and depression in the active Manufacturing companies at the Tehran Stock Exchange. Financial Knowledge of Securities Analysis, 12(42), 147-161. (in Persian)
Blume, L., Easley, D., & O'hara, M. (1994). Market statistics and technical analysis: The role of volume. The Journal of Finance49(1), 153-181.
Boobalan, C. (2014). Technical analysis in select stocks of Indian companies. International Journal of Business and Administration Research Review2(4), 26-36.
Chen, S., Bao, S., & Zhou, Y. (2016). The predictive power of Japanese candlestick charting in Chinese stock market. Physica A: Statistical Mechanics and its Applications457, 148-165.
Eslami Bidgoli, GH. R., Nabizade, A. (2011). Examination of Weekend Effect and Caparison of Individual and Legal Investor's Behavior During 1381-85 in Tehran Stock Exchange. Financial Research Journal, 11(28), 21-34. (in Persian)
Fathi, S., Parvizi, N. (2016). Profitability of Technical Analysis: Combining Oscillators with Moving Average Rules. Financial Engineering and Securities Management, 7(28), 41-53. (in Persian)
Frankel, J. A., & Froot, K. (1990). Chartists, fundamentalists, and trading in the foreign exchange market. NBER Working Paper, (R1512).
Gholamian, E., davoodi, S. (2018). Predicting the Direction of Stock Market Prices Using Random Forest. Financial Engineering and Securities Management, 9(35), 301-322. 
(in Persian)
Khanjarpanah, H., Dourvash, D., Shavvalpour, S., Jabbarzadeh, A. (2018). The Application of Technical Analysis in Stock Price Forecasting: Non-linear Probability Models and Artificial Neural Networks. Financial Management Strategy, 6(3), 59-79. (in Persian)
Kimiagari, M., Tizhari, M. (2006). A Model for Testing and Improving Stock Market Efficiency. Financial Research Journal, 8(22). (in Persian)
Ko, K.C., Lin, S.J., Su, H.J., Chang, H.H. (2014). Value investing and technical analysis in Taiwan stock market. Pacific-Basin Finance Journal, 26, 14-36.
Logan, T. (2008). Getting Started in Candlestick Charting. John Wiley & Sons, New Jersey.
Lu, T. H. (2014). The profitability of candlestick charting in the Taiwan stock market. Pacific-Basin Finance Journal26, 65-78.
Masry, M. (2017). The Impact of Technical Analysis on Stock Returns in an Emerging Capital Markets (ECM¡¯s) Country: Theoretical and Empirical Study. International Journal of Economics and Finance, Canadian Center of Science and Education, 9(3), 91-107.
Mirzaei, H., Khodamipour, A., Pourheidari, O. (2016). Applying Multi objective Genetic Algorithms in Portfolio Optimization by Technical Indicators. Financial Engineering and Securities Management, 7(29), 67-84. (in Persian)
Mohamadi, A. (2017). A complete reference to technical analysis in capital markets. Tehran: Mehraban Book. (in Persian)
Murphy, J. J. (1999). Technical Analusis of the Financial Markets. New York: John Wiley & Sons.
Nasrolahi, KH., Saghafi Killvangh, R., Samadi, S., Vaez Barzani, M. (2013). An Appraisal of the Merit of Candlestick Technical Trading Strategies in Tehran Stock Exchange. Journal of Financial Accounting Research, 59-72. (in Persian)
Nikusokhan, M. (2018). An Improved Hybrid Model with Automated Lag Selection to Forecast Stock Market. Financial Research Journal, 20(3), 389-408. (in Persian)
Nison, S. (1991). Japanese candlestick charting techniques: a contemporary guide to the ancient investment techniques of the Far East. Penguin.
Park, C. H., & Irwin, S. H. (2007). What do we know about the profitability of technical analysis? Journal of Economic Surveys21(4), 786-826.
Poorzamani, Z., Rezvaniaghdam, M. (2015). Compare efficiency technical strategies containing exponential moving average and relative strength index with buy and hold method. Journal of Investment Knowledge, 4(16), 27-44. (in Persian)
Rastegar, M., Ashuri, F. (2018). Optimization of technical indicators’ parameters for intraday data using optics – inspired optimization (OIO): a case study of Tehran stock exchange. Financial Engineering and Securities Management, 9(35), 153-178. (in Persian)
Rastegar, M., Dastpak, M. (2018). Developing a High-Frequency Trading system with Dynamic Portfolio Management using Reinforcement Learning in Iran Stock Market. Financial Research Journal, 20(1), 1-16. (in Persian)
Rezaeian, A., Fadaei Nejad, M. E., Joshan, E. (2016). The effect of behavioral financial factors on the value of transactions in different stock market conditions. Quantitative Researches in Management, 7(3), 27-37. (in Persian)
Rezvani Aghdam, M., Pourzamani, Z. (2017). Compare the Efficiency of Technical Analysis Strategies with Buy and Hold Rule for the Stock Purchase in Bullish and Bearish periods. Financial Knowledge of Securities Analysis, 10(33), 17-31. (in Persian)
Saleh Ardestani, A. (2016). Comparative Study of Eeffectiveness of Technical Analysis Indicators with Type of Trend with Accidental Oscillator in Securities Analysis Pharmaceutical Companies. Journal of healthcare management, 6(4), 41-47. (in Persian)
Stankovic, J., Markovic, I., Stojanovic, M. (2015). Investment Strategy Optimization Using Technical Analysis and Predictive Modeling in Emerging Markets. Procedia Economics and Finance, 19, 51-62.
Tehrani, R., Modarres, A., Tahriri, A. (2010). Evaluation of the Effect of using Technical Analysis Indexes on the Returns of Investors. Journal of Economic Research, 45(3). 
(in Persian)
Treynor, J. L., & Ferguson, R. (1985). In defense of technical analysis. The Journal of Finance40(3), 757-773.
Vakili, S., Emadi, S., Ebrahimi, S. (2019). Automatic Portfolio Rebalancing System Design Using Volatility Prediction Models and Technical Analysis Combination. Financial Management Strategy, 7(1), 145-164. (in Persian)