We present a new method, inspired by the bootstrap, whose goal it is to determine the quality and reliability of a neural network predictor. Our method leads to more robust forecasting along with a large amount of statistical information on forecast performance that we exploit. We exhibit the...

This paper tests whether fitted linear models can replicate results from moment tests inspired by moving average technical trading rules for weekly foreign exchange series. Estimation is performed using standard OLS and maximum likelihood methods, along with a simulated method of moments...

This paper performs tests on several different foreign exchange series using a methodology inspired by technical trading rules. Moving average based rules are used as specification tests on the process for foreign exchange rates. Several models for regime shifts and persistent trends are...

This paper examines the joint process for volume and volatility. Locallinear models are used to analyze stability of the joint processes in different regions of volatility-volume space. It is found that this way of looking at the series changes dramatically the results found by using a global...

This paper documents a relation between the persistence of stock returns for a large firm index and trading volume. Previous results on the negative relation between volume and persistence are replicated, but a second effect is discovered. Persistence is directly related to the current rate of...

Combining ideas from evolution and learning to understand empirical puzzles in financial markets is a growing area of interest in economic research. This paper provides a short survey of some of the ongoing work in this area with special attention paid to computational models relying on...

There is reliable evidence that simple rules used by traders have some predictive value over the future movement of foreign exchange prices. This paper will review some of this evidence and discuss the economic magnitude of this predictability. The profitability of these trading rules will then...