ENMX: An elastic network model to predict the FOREX market evolution (2018). Simulation Modelling Practice and Theory, 86, 1-10.

[:es]Antonio V. Contrerasa (Universidad Católica de Murcia), Antonio Llanes (Universidad Católica de Murcia), Alberto Pérez-Bernabeu (Miguel Hernandez University), Sergio Navarro (Artificial Intelligence Talentum, S.L., Campus Universitario de Espinardo de Murcia), Horacio Pérez-Sánchez (Universidad Católica de Murcia), Jose J. López-Espín (Miguel Hernandez University), José M. Cecilia (Universidad Católica de Murcia).
Abstract. The foreign exchange (FOREX) market is a financial market in which participants, such as international banks, companies or private investors, can both invest in and speculate on exchange rates. This market is considered one of the largest financial markets in the world in terms of trading volume. Indeed, the just-in-time price prediction for a currency pair exchange rate (e.g. EUR/USD) provides valuable information for companies and investors as they can take different actions to improve their business. This paper introduces a new algorithm, inspired by the behaviour of macromolecules in dissolution, to model the evolution of the FOREX market, called the ENMX (elastic network model for FOREX market) algorithm. This algorithm allows the system to escape from a potential local minimum, so it can reproduce the unstable nature of the FOREX market, allowing the simulation to get away from equilibrium. ENMX introduces several novelties in the simulation of the FOREX market. First, ENMX enables the user to simulate the market evolution of up to 21 currency pairs, connected, and thus emulating behaviour of the realworld FOREX market. Second, the interaction between investors and each particular quotation, which may introduce slight deviations from the quotation prices, is represented by a random movement. We analyse different probability distributions like Gaussian and Pseudo-Voigt, the latter showing better behaviour distributions, to model the variations in quotation prices. Finally, the ENMX algorithm is also compared to traditional econometric approaches such as the VAR model and a driftless random walk, using a classical statistical and a profitability measure. The results show that the ENMX outperforms both models in terms of quality by a wide margin.[:]