We use genetic programming techniques to identify optimal technical trading rules. We find strong evidence of economically significant out-of-sample excess returns to the rules for each of six exchange rates ($/DM, $/Yen, $/SF, $/£, DM/Yen, SF/£), over the period 1981–95. Some of the rules have a structure similar to those used by technical analysts. Betas calculated for the returns according to various benchmark portfolios provide no evidence that the returns to these rules are compensation for bearing systematic risk. ‘Bootstrapping’ results for the $/DM indicate that the trading rules are detecting patterns in the data that are not captured by standard statistical models.
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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number
1480.
Find related papers by JEL classification: F31 - International Economics - - International Finance - - - Foreign Exchange G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
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