We provide evidence that the use of technical trading rules provides traders the opportunity to generate profits from actively buying and selling individual stocks across Asian markets. We test the trading performance of three widely used technical trading strategies, the Arithmetic Moving Average, the Relative Strength Index, and the Stochastic Oscillator, as well as variations to each trading strategy. We compare the results of these trading rules to a long-term buy-and-hold strategy across 4822 stocks traded in 39 Asian countries. Our results, when applying a simple behavior intervention filter of only selling a position when a trade is profitable, show that these technical trading rules, on average, were able to outperform the buy-and-hold strategy for 66% of the stocks listed in our sample. Additionally, given any of the listed Asian stocks, we found that, on average, a trader could apply any technical trading strategy and have a greater than 50–50 chance of outperforming the buy-and hold strategy for that stock for 63% of all stocks.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price excludes VAT (USA)
Tax calculation will be finalised during checkout.
Throughout our methodology, we assume that traders can only act upon a change in signal. This avoids over-accumulating or over-borrowing on long or short positions. Similar restrictions hold for the Relative Strength Index and the Stochastic Oscillator techniques.
We also compare results from this mechanical approach by incorporating a simple behavioral filter to our trading rules, to provide human intervention before closing a trading position. We discuss below.
The price ranges for some stocks may not trigger any “buy” signal from a trading rule to begin trading. So, not all 31 trading rules can be counted. While possible for any trading rule, it is more common for those trading rules with stricter filters on less volatile stocks.
Arnold, C. (1994). Reading between the (chart) lines. Futures, the Magazine of Commodities and Options, 23, 36–38
Ben-Zion, U., Klein, P., Shachmurove, Y., & Yagil, J. (2003). Efficiency differences between the S&P 100 and the Tel-Aviv 25 indices: A moving average comparison. International Journal of Business, 8, 267–284
Bessembinder, H., & Chan, K. (1995). The profitability of technical trading rules in the Asian stock markets. Pacific Basin Finance Journal, 3, 257–284
Bessembinder, H., & Chan, K. (1998). Market efficiency and the returns to technical analysis. Financial Management, 27, 5–17
Brock, W. A., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. Journal of Finance, 47, 1731–1764
Colby, R. W. (2003). The encyclopedia of technical market indicators. (2nd ed.). McGraw-Hill
Elder, A. (1987). Using stochastics to catch early trends and reversals. Futures, the Magazine of Commodities and Options, 16, 68–72
Etzkhorn, M. (1995). Getting an indication. Futures, the Magazine of Commodities and Options, 24, 38–39
Fama, E. (1965). The behavior of stock market prices. Journal of Business, 38, 34–105
Gencay, R. (1996). Non-linear predictions of security returns with moving average rules. Journal of Forecasting, 15, 165–174
Kahn, Michael (2019). How investors can prosper with technical analysis. Kiplinger’s Personal Finance. https://www.kiplinger.com/article/investing/t052-c008-s001-how-investors-can-prosper-with-technical-analysis.html
Khand, S., Anand, V., & Qureshi, M. N. (2020). The predictability and profitability of simple moving averages and trading range breakout rules in the Pakistan stock market. Review of Pacific Basin Financial Markets and Policies. https://doi.org/10.1142/S0219091520500010
Kwon, K., & Kish, R. J. (2002). Technical trading strategies and return predictability: NYSE. Applied Financial Economics, 12, 639–653
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(1), 144–170
Mitchell, C. (2020). Trend trading: the four most common indicators. https://www.investopedia.com/articles/active-trading/041814/four-most-commonlyused-indicators-trend-trading.asp
Nor, S. M., & Wickremasinghe, G. (2014). The profitability of MACD and RSI trading rules in the Australian stock market. Investment Management and Financial Innovation, 11(4), 194–199
Papathanasiou, S., & Samitas, A. (2010). Profits from technical trading rules: The case of Cyprus stock exchange. Journal of Money, Investment and Banking, 13, 35–43
Poterba, J. M., & Summers, L. (1988). Mean reversion in stock prices: Evidence and implications. Journal of Financial Economics, 22, 27–59
Ratner, M., & Leal, R. P. C. (1999). Tests of technical trading strategies in the emerging equity markets of Latin America and Asia. Journal of Banking and Finance, 23(12), 1887–1905
Seiler, M. J. (2001). Optimizing technical trading strategies: Making the ludicrous lucrative. American Business Review, 19, 20–25
Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. Journal of Finance, 40(3), 777–790
Stein, J. (1989). What divergence indicates about real price value. Futures, the Magazine of Commodities and Options, 18, 32–34
Tharavanij, P., Siraprapasiri, V., & Rajchamaha, K. (2015). Performance of technical trading rules: evidence from Southeast Asian stock markets. Springerplus. https://doi.org/10.1186/s40064-015-1334-7
Wilder, J.W. (1978) New concepts in technical trading systems. Trend Research
Wong, W., Manzur, M., & Chew, B. (2003). How rewarding is technical analysis? Evidence from Singapore stock market. Applied Financial Economics, 13, 543–551
Yoon, F. (2021). A ‘Mind-Boggling’ Individual Investor Boom Stirs Up Markets in Asia. Wall Street Journal. March 4, 2021 https://www.wsj.com/articles/a-mind-boggling-individual-investor-boom-stirs-up-markets-in-asia-11614853804. Accessed April 10, 2021
Yu, H., Nartea, G. V., Gan, C., & Yao, L. J. (2013). Predictive ability and profitability of simple technical trading rules: Recent evidence from Southeast Asian stock markets. International Review of Economics and Finance, 25, 356–371
Yu, T., and Chen, S-H (2004). Using genetic programming with lambda abstraction to find technical trading rules. Computing in Economics and Finance. Society for Computational Economics, https://EconPapers.repec.org/RePEc:sce:scecf4:200
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Coe, T.S., Laosethakul, K. Applying Technical Trading Rules to Beat Long-Term Investing: Evidence from Asian Markets. Asia-Pac Financ Markets 28, 587–611 (2021). https://doi.org/10.1007/s10690-021-09337-5