زمان بندی موضوعات در بازار ارز خارجی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|14855||2012||7 صفحه PDF||سفارش دهید||3270 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Physica A: Statistical Mechanics and its Applications, Volume 391, Issue 3, 1 February 2012, Pages 760–766
We show using nonlinear time series analysis that the timing of trades in foreign exchange markets has significant information. We apply a set of methods for analyzing point process data developed in neuroscience and nonlinear science. Our results imply that foreign exchange markets might be chaotic and have short-term predictability.
For the last fifteen years, high-resolution foreign exchange data have been successfully characterized using techniques developed in econophysics , , , , , , , , , ,  and . Although price changes, the distribution of inter-trade intervals, and numbers of trades per unit time were intensively studied, the timing of trades is often assumed to be stochastic and has not been thoroughly investigated from a viewpoint of nonlinear dynamics. Here we report that trade times also provide fundamental information about foreign exchange markets. By applying techniques developed in neuroscience  and , we show that trade times do not follow the Poisson process and that they provide some information which cannot be obtained from short-term counts of trade times. Applications of the recently developed distance  for marked point processes with methods ,  and  in nonlinear science suggest that trades have serial dependence and that their generating process can be deterministically chaotic. Actually series of trades can be predicted for a short term. The results imply that by taking into account the timing of trades, the dynamics of foreign exchange markets may be controlled by chaos control .
نتیجه گیری انگلیسی
The authors would like to thank the EBS Service Company Limited, which provided the real sets of foreign exchange market data used in this paper. The datasets used in this paper are commercially available from the EBS Service Company Limited. This research was partially supported by the Aihara Innovative Mathematical Modelling Project, the Japanese Society for the Promotion of Science (JSPS) through its “Funding Program for World-Leading Innovative R&D on Science and Technology (FIRST Program)”, initiated by the Council for Science and Technology Policy (CSTP). The research of Y. H. was also partially supported by Grant in Aid for Young Scientists (B), No. 21700249 from the Japanese Ministry of Education, Culture, Sports, Science, and Technology, and No. 23700261, from the Japanese Society for the Promotion of Science (JSPS).