Author(s)

N. Sazuka & T. Ohira

Abstract

High frequency market data has become available with recent developments in computer technology. These data have some unique characteristics that do not appear in low frequency data. They are important in understanding financial markets. We present evidence of a unique property of high frequency data by proposing a new model. In this paper, we analyze tick-by-tick data, the most high frequency data available, of yen-dollar currency exchange rates. Focusing on the direction of up or down price movement, we show that a non-trivial structure exists in conditional probabilities of binarized data, which is apparently invisible from the price change itself. The probabilistic structure has a strong bias not only in the first order conditional probabilities but also in the higher order ones. Logit model

Keywords