id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_rjehwmoalvgknnzgl5b2jfpziq	Huseyin Ince	Kernel methods for short-term portfolio management	2006	3	.pdf	application/pdf	1532	180	61	Some of the studies show that the stock market is not efficient around the earning season. Based on these findings, we formulate the problem as a classification problem by using state of the art machine learning techniques such as minimax probability machine (MPM) and support vector machines (SVM). The MPM method finds a bound on the misclassification probabilities. Keywords: Support vector machines; Minimax probability machine; Kernel methods; Portfolio management; Earning announcements derived from earning announcements and volatility of stocks markets and earning announcements focus on the information announcements of decrease in earnings for the USA firms. to earnings announcements, there is no consistent price Quarterly earnings announcement is probably one of the with two classes; 'buy a certain stock whose earning/eps is Data mining techniques such as SVMs, MPM and multilayer portfolio selection problem by using MPM and SVMs. This can earning announcement. announcement in terms of individual stocks. H. Ince, T.B. Trafalis / Expert Systems with Applications 30 (2006) 535–542536	./cache/work_rjehwmoalvgknnzgl5b2jfpziq.pdf	./txt/work_rjehwmoalvgknnzgl5b2jfpziq.txt