Pattern recognition analysis based on k-nearest neighbors classifiers is applied to the representation of the stock market dynamics with the help of the Japanese candlesticks augmented by the accompanying volume of transactions. Examples from a post-emerging Warsaw stock market are given. Conditions under which the Japanese candlesticks appear to have a reasonable predictive power are provided. The dependence of the results on the number of nearest neighbors, the length of the candlestick sequence, and the forecast horizon are shown. Possible ways of the forecast improvement are discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.