This paper investigates the predictability of spot foreign exchange rate returns from past buy-sell signals of the simple technical trading rules by using the nearest neighbors and the feedforward network regressions. The optimal choices for nearest neighbors, hidden units in a feedforward network and the training set are determined by the cross validation method which minimizes the mean square...

Listed: Ren, Louie (University of Houston-Victoria, TX, USA) Peter Houston-Downtown, Houston, Registered:

A novel algorithm for actively trading stocks is presented. While traditional expert advice and “universal” algorithms (as well as standard technical trading heuristics) attempt to predict winners or trends, our approach relies on predictable statistical relations between all pairs of stocks in the market. Our empirical results on historical markets provide strong evidence that this type of tec...

Motivated by empirical evidence, we construct a model where heterogeneous boundedly rational market participants rely on a mix of technical and fundamental trading rules. The rules are applied according to a weighting scheme. Traders evaluate and update their mix of rules by a genetic algorithm. Already for a low probability of fundamental shocks the interaction between the traders results in a...

Whether one takes a qualitative or a quantitative approach, the techniques available are many and varied, and that complicates a systematic assessment of the usefulness of technical analysis. It comes as no wonder then, that empirical tests of specific trading rules and their attendant signals are often less than satisfactory tests of the efficiency of technical analysis in general, since trade...

We explored the application of a machine learning method, Logitboost, to automatically calibrate a trading model using different versions of the same technical analysis indicators. This approach takes advantage of boosting’s feature selection capability to select an optimal combination of technical indicators and design a new set of trading rules. We tested this approach with high frequency dat...