SearcharxivSearch

arXiv · cond-mat/0104260

Correlations Between Reconstructed EUR Exchange Rates vs. CHF, DKK, GBP, JPY and USD

Abstract

On Jan. 1, 1999 the European Union introduced a common currency Euro ($EUR$), to become the legal currency in all eleven countries which form the $EUR$. In order to test the $EUR$ behavior and understand various features, the $EUR$ exchange rate is artificially extrapolated back to 1993 by a linear superposition of the exchange rates of the 11 currencies composing $EUR$ with respect to several currencies not belonging to the $EUR$, i.e. Swiss Franc ($CHF$), Danish Kroner ($DKK$), British Pound ($GBP$), Japanese Yen ($JPY$) and U.S. Dollar ($USD$) of interest for reasons given in the text. The distribution of fluctuations of the exchange rates is shown to be Gaussian for the central part of the distribution, and having fat tails for the large size fluctuations. Within the {\it Detrended Fluctuation Analysis} ($DFA$) statistical method we have obtained the power law behavior describing the root-mean-square deviation of the exchange rate fluctuations as a function of time. For the period between Jan. 1995 and Jan. 1999 we have compared the time-dependent exponent of these exchange rate fluctuations for $EUR$ and that of the 11 currencies which form the $EUR$. The German Mark ($DEM$) and the French Franc ($FRF$) have been the currencies primarily leading the fluctuations of the exchange rates, while Italian Lira ($ITL$) and ($PTE$) Portuguese Escudo are the less relevant currencies from this point of view. Technical considerations for the $EUR$ implementation are given as conclusions. The cases of exchange rates with $DKK$ appear quite different from the other four major currencies.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M. Ausloos, K. Ivanova. 2001-04-13. Correlations Between Reconstructed EUR Exchange Rates vs. CHF, DKK, GBP, JPY and USD. https://doi.org/10.1142/s0129183101001572

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Universal sampling of spin systems across quenched disorder

Statistical physics extracts macroscopic laws by averaging over the many microscopic degrees of freedom of a system. Disordered systems demand a second and far harder average, one over the quenched randomness itself. The classic analytical routes, the replica and cavity methods, become uncontrolled outside mean-field or tree-like limits, and conventional numerical algorithms like parallel tempering require expensive, independent equilibration for every disorder realization. In this work, we introduce a universal neural variational framework that amortizes inference across the disorder ensemble, eliminating both the need for per-instance Markov chain equilibration and the cost of retraining instance-specific variational ansatzes. Built on an encoder-decoder Transformer architecture, after training once, it produces an explicit approximation to the Boltzmann distribution given previously unseen disorder realizations without further optimization. We validate this framework on 2D Edwards-Anderson models, and apply it to the random-bond Ising model, successfully capturing the Binder cumulant crossings near the Nishimori multicritical point. These results shift the object of variational inference from the single instance to the disorder ensemble, opening a route to frustrated many-body systems where instance-by-instance computation is prohibitive.

cond-mat.stat-mech

Information-Theoretic Characterization of Macroscopic Chaos Emerging from the Chemical Master Equation

Open chemical reaction networks exhibit stochastic concentration dynamics at finite system sizes, whereas their macroscopic limit is governed by deterministic rate equations that can display chaos. In this Letter, we show theoretically that a rate of information loss constructed from two-time mutual information recovers the Kolmogorov-Sinai entropy in the deterministic limit. We verify this result through numerical simulations of a Markov jump process for a three-species system involving seven reactions.

cond-mat.stat-mech

Orientational order on non-orientable domains

We study the statistical properties of passive and active many-body systems with orientational degrees of freedom on non-orientable domains. By rephrasing topological constraints as non-local symmetry relations on an orientable double-cover, we show that non-orientability eliminates global rotational soft modes without acting like an external field. In a passive XY model, this results in topological caging, where orientational fluctuations that exhibit conventional diffusive behavior on a torus saturate on a Klein bottle to a finite value that we compute exactly in the thermodynamic limit. In models of active self-propelled particles with orientational degrees of freedom, topological caging persists despite continuously changing interaction neighborhoods. In an active Ising spin model, non-orientability enforces the coexistence of ordered anti-parallel domains with vanishing global polar order, a state that is absent on orientable domains.

cond-mat.stat-mech