The foreign exchange market generates millions of daily tick data, often referred to as high frequency data (HFD), as a result of market participants decisions. By analyzing these data, one could reveal many of the market properties. However, HFD may possibly contain observations that are not reliable in terms of actual market activity. We manipulate a real dataset storing the full transaction history of more than 40,000 traders on an account level for 2.25 years.

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.