This study proposes a multiple attributes decision making (MADM) method for solving glamor stock selection problem based on fundamental analysis. Traditional analyzes rely on choosing key financial ratios in making comparison, or by observing the trends of change in various financial variables (also termed as criteria or signals in this study). However, most of the criteria for stock selection ...

This paper generalizes a recently proposed spatial autoregressive model and introduces a spatiotemporalmodel for forecasting stock returns.We support the view that stock returns are affected not only by the absolute values of factors such as firm size, book-to-market ratio and momentum but also by the relative values of factors like trading volume ranking and market capitalization ranking in ea...

A novel method of stock portfolio management by using technical indicators is proposed in this paper. The method hybridizes the consensus trading signals generated by the gene expression programming (GEP) proposed by Lee et al., and the portfolio redemption scheme proposed by Tsai et al. with our stock ranking functions. The indicators were used not only for trading, but also for selecting prom...

stock selection criteria play a key role in contrarian portfolio construction. the usual approach is applying cumulative return as stock selection criteria however applying this criterion leads to ranking stocks without considering investment risk. in this study, we analyze contrarian strategies that are based on reward–risk stock selection criteria in contrast to ordinary contrarian strategies...

this study examines the empirical validity of claims that value stocks (stocks with high ratios of book value to price) have higher average returns than growth stocks (stocks with low book-to-market ratios). the analyses are performed using data pertaining to 70 firms for the period 1381-1389 and used the panel data methodology. this paper contains significant and consistent results. the result...

Ranking temporal data has not been studied until recently, even though ranking is an important operator (being promoted as a firstclass citizen) in database systems. However, only the instant top-k queries on temporal data were studied in, where objects with the k highest scores at a query time instance t are to be retrieved. The instant top-k definition clearly comes with limitations (sensitiv...

Quantitative stock selection has become a research hotspot in the field of investment decision. As the data mining technology becomes mature, quantitative stock selection has made great progress. From the perspective of value investment, this paper selects top 200 stocks of A share in terms of market value. With the random forest (RF), financial characteristic variables with significant impact ...

A methodology based on the algorithmic complexity theory has been applied to assess the relative efficiency of the stocks listed on Bovespa. We provide eight alternative listings of the top ten stocks according to their efficiency rates.