By the empirical results it is possible to say, first of all, that empirical research conducted largely support the two research hypothesis discussed in section 1, justifying the attempt to forecast the exchange rate Euro/USD per-formed in this research through a non-linear methodol-ogy. The good forecasting performance of the network developed show that the process of formation of rate ex-change is not completely governed by noise.
The research therefore provides evidence to support the hypothesis of serial dependence of prices in financial markets, according to which prices evolve according to a trend not completely random, and then, at least in part, predictable. This hypothesis, which draws its origins from chaos theory applied to financial systems [46,65- 72], is based on the idea that what the theory of random walk considers noise, it is probably the result of complex interaction between different market players, who react to the dynamics of price with behaviours that can be bet-ter identified by models of nonlinear nature. Therefore, the analysis provides evidence to support the research hypothesis that the processes of pricing in financial mar-kets have seemingly ruled by chance but in reality are determined by interaction between actors and relation-ships between variables of nonlinear nature, which are difficult to detect because of the chaotic component that
By the empirical results it is possible to say, first of all, that empirical research conducted largely support the two research hypothesis discussed in section 1, justifying the attempt to forecast the exchange rate Euro/USD per-formed in this research through a non-linear methodol-ogy. The good forecasting performance of the network developed show that the process of formation of rate ex-change is not completely governed by noise.The research therefore provides evidence to support the hypothesis of serial dependence of prices in financial markets, according to which prices evolve according to a trend not completely random, and then, at least in part, predictable. This hypothesis, which draws its origins from chaos theory applied to financial systems [46,65- 72], is based on the idea that what the theory of random walk considers noise, it is probably the result of complex interaction between different market players, who react to the dynamics of price with behaviours that can be bet-ter identified by models of nonlinear nature. Therefore, the analysis provides evidence to support the research hypothesis that the processes of pricing in financial mar-kets have seemingly ruled by chance but in reality are determined by interaction between actors and relation-ships between variables of nonlinear nature, which are difficult to detect because of the chaotic component that
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