To Study Trading Rules Using Biclustering in Financial Market

Abstract: As capital growth increased, trading system plays important role in world. Technical analysis analyses price, volume, and market information. Price patterns and market trends are analyzed by technical analyst for investing capital in financial market and these patterns are useful to take right decisions for making investments. For taking such a decisions, it needs to analyze the price movement and provide trading rules to guide investors, so that they can take correct trading decisions. For analyzing and trading decisions, the paper proposes to implement Biclustering mining to discover effective trading rules that contain a combination of indicators from historical financial data series. Biclustering is a clustering algorithm because it clusters the data along the row and the column simultaneously in a 2-D data matrix. The trading rules can be divided in three trading actions (buy, sell, and no-action signals). For optimizing the trading rules we proposed particle swarm algorithm. By particle swarm algorithm we get optimized rules which help investors for investing finance in market and also take right actions.

Keywords: Biclustering, Particle Swarm, Trading Rules.