New Evidence of Technical Trading Profitability
We developed profitable foreign exchange forecasts by applying a special adaptive form of the Strongly Typed Genetic Programming (STGP)-based learning algorithm to five-minute high frequency data of six of the most traded currency pairs. We examined the out-of-sample performance of these intraday technical trading models based on STGP and optimised linear forecasting. We found evidence of economically and statistically significant out-of-sample excess returns, after taking into account appropriate transaction costs.
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Volume (Year): 33 (2013)
Issue (Month): 4 ()
Pages: 2493-2503
| Handle: | RePEc:ebl:ecbull:eb-13-00465 |
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- Neely, C. J. & Weller, P. A., 2003.
"Intraday technical trading in the foreign exchange market,"
Journal of International Money and Finance,
Elsevier, vol. 22(2), pages 223-237, April.
- Paul Weller & Christopher Neely, 1999. "Intraday Technical Trading in the Foreign Exchange Market," Working Papers wp99-02, Warwick Business School, Finance Group.
- Christopher J. Neely & Paul A. Weller, 2001. "Intraday technical trading in the foreign exchange market," Working Papers 1999-016, Federal Reserve Bank of St. Louis.
- Atanasova, Christina V. & Hudson, Robert S., 2010. "Technical trading rules and calendar anomalies -- Are they the same phenomena?," Economics Letters, Elsevier, vol. 106(2), pages 128-130, February.
- Marcucci Juri, 2005. "Forecasting Stock Market Volatility with Regime-Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-55, December.
- Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, 02.
- Hendershott, Terrence & Jones, Charles M. & Menkveld, Albert J., 2008. "Does algorithmic trading improve liquidity?," CFS Working Paper Series 2008/41, Center for Financial Studies (CFS).
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