Detecting Environmental Changes through High-Resolution Data of Financial Markets
This article proposes methods to detect states of financial markets both comprehensively and with a high-resolution. In order to quantify trading patterns several mathematical methods are proposed based on frequencies of quotations/ transactions estimated from high-resolution data of financial markets. The empirical results (graphical network representation and quantification of states of market participants) for the foreign exchange market are shown. It is concluded that synchronous behavior associated with a large population of market participants may be a candidate of precursory signs leading to an environmental change.
KeywordsBipartite Graph Market Participant Physical Review Letter Foreign Exchange Market Synchronous State
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