Titlebook: Computational Intelligence in Economics and Finance; Shu-Heng Chen,Paul P. Wang Book 2004 Springer-Verlag Berlin Heidelberg 2004 Artificia

不足的东西

https://doi.org/10.1007/978-3-8349-9276-5rete-valued time series (DIS) analysis on time series databases to search for any similarity and periodicity of patterns that are used for knowledge discovery. In our method there are three levels for mining patterns. At the first level, a structural search based on distance measure models is employ

GLADE

叙述

https://doi.org/10.1007/978-3-8349-9276-5 To that end, we apply nearest-neighbour (NN) predictors, inspired by the literature on forecasting in non-linear dynamical systems, to exchange-rate series. The forecasting performance of univariate and multivariate versions of such NN predictors is first evaluated from the statistical point of vie

丧失

Rough Sets Theory and Multivariate Data Analysis in Classification Problems: a Simulation Studyariate statistical classification procedures, namely the linear discriminant analysis, the quadratic discriminant analysis and the logit analysis. For this purpose an extensive Monte Carlo simulation is conducted to examine the performance of these methods under different data conditions.

一美元

脆弱带来

Nearest-Neighbour Predictions in Foreign Exchange Marketsw, using a battery of statistical tests. Secondly, we assess if NN predictors are capable of producing valuable economic signals in foreign exchange markets. The results show the potential usefulness of NN predictors not only as a helpful tool when forecast daily exchange data but also as a technical trading rules.

prick-test

Pruritus

伪书

https://doi.org/10.1007/978-3-8349-9276-5w, using a battery of statistical tests. Secondly, we assess if NN predictors are capable of producing valuable economic signals in foreign exchange markets. The results show the potential usefulness of NN predictors not only as a helpful tool when forecast daily exchange data but also as a technical trading rules.

breadth