CrossCorrelation of FOREX exchange rates using power law classification scheme. 
Janusz Miśkiewicz 
Wrocław University, Institute of Theoretical Physics (IFT UWr), pl. Maksa Borna 9, Wrocław 50205, Poland 
Abstract 
The paper presents results of the crosscorrelation analysis among currencies exchange time series quoted on FOREX. The analysis was performed by the power law classification scheme (PLCS) introduced in [1]. The key advantage of PLCS is that it define strength (α) and stability (β) of correlation. Moreover it was proven that PLCS properly classify crises and prosperity periods for macroeconomy (GDP of the most developed countries [2]) as well as stock markets [3]. In the present analysis 42 time series of the daily exchange rates of the following pairs: PLNARS, PLNAUD, PLNBGN, PLNCAD, PLNCHF, PLNCLP, PLNCNY, PLNCZK, PLNDKK, PLNEGP, PLNEUR, PLNGBP, PLNHKD, PLNHRK, PLNHUF, PLNIDR, PLNILS, PLNINR, PLNISK, PLNJPY, PLNKRW, PLNMXN, PLNMYR, PLNNAD, PLNNOK, PLNNZD, PLNPHP, PLNRON, PLNRUB, PLNSEK, PLNSGD, PLNTHB, PLNTRY, PLNTWD, PLNUAH, PLNUSD, PLNXAG, PLNXAU, PLNXDR, PLNXPD, PLNXPT, PLNZAR, where analysed. The common currency of the chosen pairs is PLN. The considered period was from 08.08.2015 till 09.10.2007 i.e. 2000 data points. The data were acquired at the stooq.com web page. The time series were converted to the daily return time series and evolution of theirs PLCS strength of correlation analysed. The evolution of α was determined by the moving time window technique, were the time window of the 50 days length was moved at each calculation step by one data point along the time axis. The calculated matrices of α were analysed by calculating theirs descriptive statistics parameters as well as by the network analysis. The analysed networks were constructed with the assumption that only the pairs with α>0 are connected. The vertex degree, degree centrality and cliques formation are discussed. It is showed that PLCS correlation strength accompanied be the described analysis properly classify not only the macroeconomy or stock market indices but also can be successfully applied to the currencies exchange markets. Bibliography: [1] J. Miśkiewicz, Phys. A 392, 2150 (2013). [2] J. Miśkiewicz, Acta Phys. Pol. A 123, 589 (2013). [3] J. Miśkiewicz, Acta Phys. Pol. A 127, A (2015).

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Presentation: Oral at 8 Ogólnopolskie Sympozjum "Fizyka w Ekonomii i Naukach Społecznych", by Janusz Miśkiewicz Submitted: 20150813 22:59 Revised: 20150905 15:12 