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Identification of market trends with string and D2-brane maps

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  • Bartoš, Erik
  • Pinčák, Richard

Abstract

The multidimensional string objects are introduced as a new alternative for an application of string models for time series forecasting in trading on financial markets. The objects are represented by open string with 2-endpoints and D2-brane, which are continuous enhancement of 1-endpoint open string model. We show how new object properties can change the statistics of the predictors, which makes them the candidates for modeling a wide range of time series systems. String angular momentum is proposed as another tool to analyze the stability of currency rates except the historical volatility. To show the reliability of our approach with application of string models for time series forecasting we present the results of real demo simulations for four currency exchange pairs.

Suggested Citation

  • Bartoš, Erik & Pinčák, Richard, 2017. "Identification of market trends with string and D2-brane maps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 57-70.
    • Handle: RePEc:eee:phsmap:v:479:y:2017:i:c:p:57-70
    DOI: 10.1016/j.physa.2017.03.014
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    1. Kanjamapornkul, Kabin & Pinčák, Richard & Bartoš, Erik, 2020. "Cohomology theory for financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 546(C).
    2. Asit Kumar Das & Debahuti Mishra & Kaberi Das & Arup Kumar Mohanty & Mazin Abed Mohammed & Alaa S. Al-Waisy & Seifedine Kadry & Jungeun Kim, 2022. "A Deep Network-Based Trade and Trend Analysis System to Observe Entry and Exit Points in the Forex Market," Mathematics, MDPI, vol. 10(19), pages 1-23, October.

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