Identification of market trends with string and D2-brane maps

TL;DR

This paper introduces multi-dimensional string objects, including open strings and D2-branes, as innovative tools for modeling and forecasting financial market trends, demonstrating their potential through real currency exchange simulations.

Contribution

It presents a novel application of string and D2-brane models for time series forecasting in financial markets, highlighting new object properties and stability analysis methods.

Findings

String models alter predictor statistics for better modeling.

String angular momentum helps analyze currency stability.

Demo simulations show promising forecasting results.

Abstract

The multi dimensional 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.