Quantitative Theory of Meaning. Application to Financial Markets. EUR/USD case study

Abstract

Purpose-The paper focuses on the link between information, investors' expectations and market price movement. EUR/USD market is examined from communication-theoretical perspectives on the dynamics of information and meaning. Design/methodology/approach-We build upon the quantitative theory of meaning as a complement to the quantitative theory of information. Different groups of investors entertain different criteria to process information, so that the same information can be supplied with different meanings. Meanings shape investors' expectations which are revealed in market asset price movement. This dynamics can be captured by non-linear evolutionary equation. We use a computationally efficient technique of logistic Continuous Wavelet Transform (CWT) to analyze EUR/USD market. Findings-The results reveal the latent EUR/USD trend structure which coincides with the model predicted time series indicating that proposed model can adequately describe some patterns of investors' behavior. Originality/value-To our best knowledge this is the first paper where investors' expectations and market assets price movement are analyzed on the base of quantitative theory of meaning. Practical implication-Proposed methodology can be used to better understand and forecast future market assets' price movement. Social implication-Information is a universal concept. From this viewpoint communication of information in financial markets doesn't much differ from communication of information in other social systems. The same conceptual tools can be applied to study other complex social systems with similar topology.

Keywords: information, meaning, non-linearity, EUR/USD financial market, model Paper type Research paper

JEL Classification: C22, G10, G15, G40, E32, D01, D84, D91