Quantitative Theory of Meaning Application to Financial Markets EUR/USD case study
<|reference_start|>Quantitative Theory of Meaning Application to Financial Markets EUR/USD case study: The paper focuses on the link between information, investors' expectations and market price movement. EUR/USD market is examined from communication-theoretical perspective on the dynamics of information and meaning. 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 Transformation (CWT) to analyze EUR/USD market. 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. Proposed methodology can be used to better understand and forecast future market assets' price movement.<|reference_end|>
@article{ivanova2024quantitative,
    title={Quantitative Theory of Meaning. Application to Financial Markets.
  EUR/USD case study},
    author={Inga Ivanova, Grzegorz Rzadkowski and Loet Leydesdorff},
    journal={arXiv preprint arXiv:2410.06476},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.06476},
    primaryClass={cs.CY}
}