With string model to time series forecasting

TL;DR

This paper introduces a novel string model approach to analyze and forecast financial forex markets, incorporating real market features like transaction costs and non-equidistant data, leading to more robust trading strategies.

Contribution

It proposes a new string topology-based method for forex market analysis and forecasting, improving stability and robustness over traditional models.

Findings

Stable prediction models for forex trading developed.

Comparison shows improved robustness against transaction costs.

Demonstrated effectiveness in portfolio selection.

Abstract

Overwhelming majority of econometric models applied on a long term basis in the financial forex market do not work sufficiently well. The reason is that transaction costs and arbitrage opportunity are not included, as this does not simulate the real financial markets. Analyses are not conducted on the non equidistant date but rather on the aggregate date, which is also not a real financial case. In this paper, we would like to show a new way how to analyze and, moreover, forecast financial market. We utilize the projections of the real exchange rate dynamics onto the string-like topology in the OANDA market. The latter approach allows us to build the stable prediction models in trading in the financial forex market. The real application of the multi-string structures is provided to demonstrate our ideas for the solution of the problem of the robust portfolio selection. The comparison with the trend following strategies was performed, the stability of the algorithm on the transaction costs for long trade periods was confirmed.