Quantifying Similarity between Markets with Application to High Frequency Financial Data

抄録

Recent accumulation of high frequency financial data due to development of information technology allows us to analyze behaviors of market participants in high resolution. In this article, we focus on tick frequency obtained from the high frequency data and investigate the characteristics of the tick frequency by utilizing spectrograms. Moreover the method to quantify the similarity between currency pairs based on the Kullback–Leibler divergence between spectrograms of the tick frequency for two currency pairs is proposed, and the time series of the similarities between currency pairs are computed. It is found that the recent markets are more similar than the past markets from the viewpoint of the tick frequency.