[PDF] Top 20 Stock Selection Based on a Hybrid Quantitative Method

... Quantitative stock selection has become a research hotspot in the field of investment ...mature, quantitative stock selection has made great ...year-to-year stock ranking. ... See full document

... 1999; Stephens and Fisch 1998). These articles use the There is a major difference between our approach “reversible jump” methodology of Green (1995) for and others that consider multiple models. Previous ap- ... See full document

... floating selection (SFFS) and sequential backward floating selection (SBFS), are now considered as standard feature selection tools, providing good performance and close-to-optimum or optimum results ... See full document

... subsequent selection of initial seed and reduces the possibility for its mis- ...better selection of initial seed because values of STD inside those regions will be more ...RG method must be ... See full document

... Feature selection has been proven to be effective and efficient in preparing high- dimensional data for data mining and machine learning problem ...Feature selection process consist of two main components: ... See full document

... on hybrid algorithm of the principle of the gene microarray data selection method is first calculated by a scoring function score of each gene, then gene in descending order according to the score, ... See full document

... a hybrid credit scoring model using feature selection ...model based on parallel GBM (Gradient Boosted Model), filter and wrapper approaches to evaluate the applicant’s credit score from the input ... See full document

... progressive selection algorithm that hybridizes heuristic search and extended reformulation into a single ...The method has the advantage of generating a strong bound using the extended reformulation, which ... See full document

... The prediction of "living data ' victimizing networks ' prediction capacity for several extremely volatile and client stocks[ 3],[ 4] and[ 5] is employed by time - delayed, repeated and probabilistic neural network. ... See full document

... variable selection method for pulverizing capability prediction of tumbling mill based on improved hybrid genetic algorithm is ...proposed. Based on the tradition GA, the proposed ... See full document

... resources based on the primary suggested set of CNs, the company may be wasting the resources and ...reassigned based on the new priorities of ...The hybrid-QFD is employed to follow changes in CNs ... See full document

... feature selection is used to reduce the dimensionality before applying any data mining ...Feature selection, techniques like wrapper, filter, embedded or hybrid method is ...clustering ... See full document

... simulation method [3]. Zhang et al. [41] used causal feature selec- tion method to predict the studied data of stock ...Shanghai Stock Exchanges and used principal component analysis and ... See full document

... solution space. So this method is called ReF-HS. ReF-HS takes both the measurement of individual features and considers the correlation between features into account. Compared with the traditional methods, it is ... See full document

... Classification method to classify the causality of a disease is of two stages with gene selection mechanism with individual or gene subset ranking as the first stage and classification tool with or without ... See full document

... However, spams can attack some widely-used spam filters which use specific spam detection algorithms. Such attacks seriously affect the effectiveness and practicality of current anti-spam technology. So we should improve ... See full document

... Each diagram is a perspective view of the influence of the variable on the size of the propeller pitch of the tugboats. Therefore, the 41 equations show a multi-variable influence of the tugboat main parameters on the ... See full document

... are based on “repeating pattern extraction”, “Model-based” & “Pitch based” Although all methods give good results but some of their individual draw back led us to discovery of new methods for ... See full document

... (MF) based on coherent algorithm with high sampling rate ...learning method based on some selected channel ...ranging method based on kernel principal component is pro- posed, where the ... See full document

... proposed method, the theoretical times of mode searching are 336 × 1 + 21 × 6 = 562 while 357 × 6 = 2142 times are needed for the full-search ...mode selection method based on the mode ... See full document