Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Using Recurrent Neural Networks To Forecasting of Forex   This paper reports empirical evidence that a neural networks model is
applicable to the statistically reliable prediction of foreign exchange rates.
Time series data and technical indicators such as moving average, are fed to
neural nets to capture the underlying "rules" of the movement in currency
exchange rates. The trained recurrent neural networks forecast the exchange
rates between American Dollar and four other major currencies, Japanese Yen,
Swiss Frank, British Pound and EURO. Various statistical estimates of forecast
quality have been carried out. Obtained results show, that neural networks are
able to give forecast with coefficient of multiple determination not worse then
0.65. Linear and nonlinear statistical data preprocessing, such as
Kolmogorov-Smirnov test and Hurst exponents for each currency were calculated
and analyzed.

29
The categories of this paper are: funct-an
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
1
The categories of this paper are: cs