SUMMARYWe propose a new test to detect chaotic dynamics, based on the stability of the largest Lyapunov exponent from different sample sizes. This test is applied to the data used in the single-blind controlled competition tests for non-linearity and chaos that were generated by Barnett et al. (1997), as well as to several other chaotic series. The results suggest that the new test is particularly effective when compared to other stochastic alternatives (both linear and non-linear). For large sample sizes the power of the test is one, although for small sample sizes it diminishes occasionally.
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* This research was funded by the Spanish Ministry of Education (project ECO2010-21318). We thank the editor (Esther Ruiz) and two anonymous referees for their constructive suggestions. We would also like to thank
This article assesses the economic significance of the non-linear predictability of EMS exchange rates. To that end, and using daily data for nine EMS currencies covering the 1 January 1978-31 December 1994 period, it considers nearest- neighbour non-linear predictors, transforming their forecasts into a technical trading rule, whose profitability has been evaluated against the traditional moving average trading rules, considering both interest rates and transaction costs. The results suggest that in most cases, a trading rule based on a non-linear predictor outperforms the moving average, both in terms of returns and in terms of the ideal profit and the Sharpe ratio profitability indicators.
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