Long-Term Memory and Correct Answer Rate of Foreign Exchange Data
Sek-Jun Weon · The Transactions of the Korea Information Processing Society · 2000
In this paper, we investigates the long-term memory and the Correct answer rate of the foreign exchange data (Yen/Dollar) that is one of economic time series, There are many cases where two kinds of fractal dimensions exist in time series generated from dynamical systems such as AR models that are typical models having a short terrr memory, The sample interval separating from these two dimensions are denoted by kcrossover. Let the fractal dimension be in K ,and in K > from the statistics mode. In usual, Statistic models have dimensions D1 and D2 such that and But it showed a result contrary to this in the real time series such as NIKKEL The exchange data that is one of real time series have relation of > When the interval between data increases, the correlation between data increases, which is quite a peculiar phenomenon, We predict exchange data by neural networks, We confirm that obrained from prediction errors and D calculated from time series data precisely satisfy the relationship = 2-2D which is provided from a non-linear model having fractal dimension, And We identified that the difference of fractal dimension appeaed in the Correct answer rate.