6 Conclusions
This chapter employs a new technique to compare the levels of noise present in different time series. Since the method requires very long series, high-frequency data from foreign exchange markets are used. It is shown that of the three markets analyzed, the $-DM market has the least amount of noise, the Y-$ market has about 10 percent more noise, and there is about 70 percent more noise in the DM-Y time series. We also see that, on average, there is less noise during the winter than during the late summer and fall. Intraday data show some autocorrelation for the days of the week. The amount of noise may be related to the amount of news that arrives at certain times during the week, during the months, or in various markets.
The analysis presented in this chapter is meant to be an attempt at the comparative study of noise. It does not provide explanations as to why the level of noise in one series is higher or lower than in another. Further research about the intensity of noise and related issues, for example, the arrival and assimilation of new information, is warranted.
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Szpiro, G.G. (2006). Noise in Foreign Exchange Markets. In: Zomaya, A.Y. (eds) Handbook of Nature-Inspired and Innovative Computing. Springer, Boston, MA. https://doi.org/10.1007/0-387-27705-6_22
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