Abstract
In this paper, we focus on studying the statistical
properties (stylized facts) of the transactions data in the Foreign Exchange
(FX) market which is the most liquid financial market in the world. We use a unique
high-frequency dataset of anonymised individual traders’ historical transactions
on an account level provided by OANDA. To the best of our knowledge, this
dataset can be considered to be the biggest available high-frequency dataset of
the FX market individual traders’ historical transactions. The established
stylized facts can be grouped under three main headings: scaling laws,
seasonality statistics and correlation behaviour. Our work confirms established
stylized facts in the literature but also goes beyond those as we have
discovered four new scaling laws and established six quantitative relationships
amongst them, holding across EUR/USD and EUR/CHF transactions.