In this paper we investigate the profitability of a simple technical trading rule based on Artificial Neural Networks (ANNs). Our results, based on applying this investment strategy to the General Index of the Madrid Stock Market, suggest that, in absence of trading costs, the technical trading...

We 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 nonlinearity and chaos that were generated by Barnett et al. (1997),...

This paper investigates the profitability of a simple and very common technical trading rule applied to the General Index of the Madrid Stock Market. The optimal trading rule parameter values are found using a genetic algorithm. The results suggest that, for reasonable trading costs, the...

The purpose of this paper is to contribute to the debate on the relevance of non-linear predictors of high-frequency data in foreign exchange markets. To that end, we apply nearest-neighbour (NN) predictors, inspired by the literature on forecasting in non-linear dynamical systems, to...

In this paper we present new evidence on the positive correlation Between returns from technical trading rules and periods of central bank intervention. To that end, we evaluate the profitability of a trading strategy based on nearest-neighbour (nonlinear) predictors, which may be viewed as a...

In this paper, we propose a new test, based on the stability of the largest Lyapunov exponent from different sample sizes, to detect chaotic dynamics in economic and financial time series. We apply this new test to the simulated data used in the single-blind controlled competition among tests...

In this paper we assesss whether some simple forms of technical analysis can predict stock price movements in the Madrid Stock Exchange. To that end, we use daily data for General Index of the Madrid Stock Exchange, covering the thirty-one-year period from January 1966-October 1997. Our results...