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May 11, 2017·Physica A Statistical Mechanics and its Applications
447 cites
Some stylized facts of the Bitcoin market

Aurelio F. Bariviera, María José Basgall, Waldo Hasperué, Marcelo Naiouf

In recent years a new type of tradable assets appeared, generically known as cryptocurrencies. Among them, the most widespread is Bitcoin. Given its novelty, this paper investigates some statistical properties of the Bitcoin market. This study compares Bitcoin and standard currencies dynamics and focuses on the analysis of returns at different time scales. We test the presence of long memory in return time series from 2011 to 2017, using transaction data from one Bitcoin platform. We compute the Hurst exponent by means of the Detrended Fluctuation Analysis method, using a sliding window in order to measure long range dependence. We detect that Hurst exponents changes significantly during the first years of existence of Bitcoin, tending to stabilize in recent times. Additionally, multiscale analysis shows a similar behavior of the Hurst exponent, implying a self-similar process.

Open access
4 source records
Complex Systems and Time Series Analysis
Theoretical and Computational Physics
Complex Network Analysis Techniques
Original source
Jan 1, 2017·Decisions in Economics and Finance
35 cites
A confidence-based model for asset and derivative prices in the BitCoin market

Alessandra Cretarola, Gianna Figà‐Talamanca, Marco Patacca

In recent literature it is claimed that BitCoin price behaves more likely to a volatile stock asset than a currency and that changes in its price are influenced by sentiment about the BitCoin system itself; in Kristoufek [10] the author analyses transaction based as well as popularity based potential drivers of the BitCoin price finding positive evidence. Here, we endorse this finding and consider a bivariate model in continuous time to describe the price dynamics of one BitCoin as well as a second factor, affecting the price itself, which represents a sentiment indicator. We prove that the suggested model is arbitrage-free under a mild condition and, based on risk-neutral evaluation, we obtain a closed formula to approximate the price of European style derivatives on the BitCoin. By applying the same approximation technique to the joint likelihood of a discrete sample of the bivariate process, we are also able to fit the model to market data. This is done by using both the Volume and the number of Google searches as possible proxies for the sentiment factor. Further, the performance of the pricing formula is assessed on a sample of market option prices obtained by the website deribit.com.

Open access
5 source records
q-fin.MF
Complex Systems and Time Series Analysis
Financial Markets and Investment Strategies
Original source
Mar 29, 2016·arXiv (Cornell University)
12 cites
Convergence to the Stochastic Burgers Equation from a degenerate\n microscopic dynamics

Oriane Blondel, Patrícia Gonçalves, Marielle Simon

In this paper we prove the convergence to the stochastic Burgers equation\nfrom one-dimensional interacting particle systems, whose dynamics allow the\ndegeneracy of the jump rates. To this aim, we provide a new proof of the second\norder Boltzmann-Gibbs principle introduced in [Gon\\c{c}alves, Jara 2014]. The\nmain technical difficulty is that our models exhibit configurations that do not\nevolve under the dynamics - the blocked configurations - and are locally\nnon-ergodic. Our proof does not impose any knowledge on the spectral gap for\nthe microscopic models. Instead, it relies on the fact that, under the\nequilibrium measure, the probability to find a blocked configuration in a\nfinite box is exponentially small in the size of the box. Then, a dynamical\nmechanism allows to exchange particles even when the jump rate for the direct\nexchange is zero.\n

Open access
Stochastic processes and statistical mechanics
Markov Chains and Monte Carlo Methods
Theoretical and Computational Physics
Original source
Jan 1, 2016·Electronic Journal of Probability
3 cites
Convergence to the stochastic Burgers equation from a degenerate microscopic dynamics

Oriane Blondel, Patrícia Gonçalves, Marielle Simon

In this paper we prove the convergence to the stochastic Burgers equation from one-dimensional interacting particle systems, whose dynamics allow the degeneracy of the jump rates. To this aim, we provide a new proof of the second order Boltzmann-Gibbs principle introduced in [7]. The main technical difficulty is that our models exhibit configurations that do not evolve under the dynamics - the blocked configurations - and are locally non-ergodic. Our proof does not impose any knowledge on the spectral gap for the microscopic models. Instead, it relies on the fact that, under the equilibrium measure, the probability to find a blocked configuration in a finite box is exponentially small in the size of the box. Then, a dynamical mechanism allows to exchange particles even when the jump rate for the direct exchange is zero.

Open access
Stochastic processes and statistical mechanics
Markov Chains and Monte Carlo Methods
Theoretical and Computational Physics
Original source
Jul 29, 2015·PLoS ONE
180 cites
Statistical Analysis of the Exchange Rate of Bitcoin

Jeffrey Chu, Saralees Nadarajah, Stephen Chan

Bitcoin, the first electronic payment system, is becoming a popular currency. We provide a statistical analysis of the log-returns of the exchange rate of Bitcoin versus the United States Dollar. Fifteen of the most popular parametric distributions in finance are fitted to the log-returns. The generalized hyperbolic distribution is shown to give the best fit. Predictions are given for future values of the exchange rate.

Open access
Complex Systems and Time Series Analysis
Stochastic processes and financial applications
Theoretical and Computational Physics
Original source
Jan 1, 2012·Journal of the European Mathematical Society
18 cites
Zero-temperature 2D stochastic Ising model and anisotropic curve-shortening flow

Hubert Lacoin, François Simenhaus, Fabio, Lucio Toninelli

Let \mathcal D be a simply connected, smooth enough domain of \mathbb R^2 . For L>0 consider the continuous time, zero-temperature heat bath dynamics for the nearest-neighbor Ising model on \mathbb Z^2 with initial condition such that \sigma_x=-1 if x\in L\mathcal D and \sigma_x=+1 otherwise. It is conjectured [23] that, in the diffusive limit where space is rescaled by L , time by L^2 and L\to\infty , the boundary of the droplet of " - " spins follows a deterministic anisotropic curve-shortening flow, where the normal velocity at a point of its boundary is given by the local curvature times an explicit function of the local slope. The behavior should be similar at finite temperature T<T_c , with a different temperature-dependent anisotropy function. We prove this conjecture (at zero temperature) when \mathcal D is convex. Existence and regularity of the solution of the deterministic curve-shortening flow is not obvious a priori and is part of our result. To our knowledge, this is the first proof of mean curvature-type droplet shrinking for a model with genuine microscopic dynamics.

Open access
2 source records
Stochastic processes and statistical mechanics
Theoretical and Computational Physics
Mathematical Dynamics and Fractals
Original source
Feb 17, 2011·Communications in Mathematical Physics
8 cites
Approximate Lifshitz Law for the Zero-Temperature Stochastic Ising Model in any Dimension

Hubert Lacoin

We study the Glauber dynamics for the zero-temperature Ising model in dimension d=4 with "plus" boundary condition.Let T+ be the time needed for an hypercube of size L entirely filled with "minus" spins to become entirely "plus". We prove that T+ is O(L^2(log L)^c) for some constant c, not depending on the dimension. This brings further rigorous justification for the so-called "Lifshitz law" T+ = O(L^2) [5, 3] conjectured on heuristic grounds. The key point of our proof is to use the detail knowledge that we have on the three-dimensional problem: results for fluctuation of monotone interfaces at equilibrium and mixing time for monotone interfaces dynamics extracted from [2], to get the result in higher dimension.

Open access
2 source records
Markov Chains and Monte Carlo Methods
Stochastic processes and statistical mechanics
Theoretical and Computational Physics
Original source
Feb 16, 2011·arXiv (Cornell University)
0 cites
Approximate Lifshitz law for the zero-temperature stochastic Ising model\n in any dimension

Hubert Lacoin

We study the Glauber dynamics for the zero-temperature Ising model in\ndimension d=4 with "plus" boundary condition.Let T+ be the time needed for an\nhypercube of size L entirely filled with "minus" spins to become entirely\n"plus". We prove that T+ is O(L^2(log L)^c) for some constant c, not depending\non the dimension. This brings further rigorous justification for the so-called\n"Lifshitz law" T+ = O(L^2) [5, 3] conjectured on heuristic grounds. The key\npoint of our proof is to use the detail knowledge that we have on the\nthree-dimensional problem: results for fluctuation of monotone interfaces at\nequilibrium and mixing time for monotone interfaces dynamics extracted from\n[2], to get the result in higher dimension.\n

Open access
Stochastic processes and statistical mechanics
Theoretical and Computational Physics
Stochastic processes and financial applications
Original source
Feb 8, 2006·Proceedings of the International Congress of Mathematicians Madrid, August 22–30, 2006
104 cites
Conformally invariant scaling limits: an overview and a collection of problems

Oded Schramm

Many mathematical models of statistical physics in two dimensions are either known or conjectured to exhibit conformal invariance. Over the years, physicists proposed predictions of various exponents describing the behavior of these models. Only recently have some of these predictions become accessible to mathematical proof. One of the new developments is the discovery of a one-parameter family of random curves called stochastic Loewner evolution or SLE. The SLE curves appear as limits of interfaces or paths occurring in a variety of statistical physics models as the mesh of the grid on which the model is defined tends to zero. The main purpose of this article is to list a collection of open problems. Some of the open problems indicate aspects of the physics knowledge that have not yet been understood mathematically. Other problems are questions about the nature of the SLE curves themselves. Before we present the open problems, the definition of SLE will be motivated and explained, and a brief sketch of recent results will be presented.

Open access
3 source records
Stochastic processes and statistical mechanics
Theoretical and Computational Physics
Geometry and complex manifolds
Original source
Jan 1, 1990·UA Campus Repository (The University of Arizona)
0 cites
Percolation in half spaces and Markov fields on branching planes.

C. Chris Wu

We study two sets of models: independent percolation models in half spaces Zᔈ⁻Âč x Z₊, and Ising/Potts models as well as the Fortuin-Kasteleyn (FK) random cluster models on branching planes T x Z, where Z is the one-dimensional lattice, Z₊ = {0,1,2,...} and T is a Bethe lattice. We prove that for independent percolation in half spaces, the infinite cluster is unique whenever it exists. For the Ising/Potts models on branching planes, there are (at least) two phase transitions; that is, there exist(s) a unique Gibbs state, tree-like nonunique Gibbs states or plane-like nonunique Gibbs states corresponding to high temperature, intermediate temperature or low temperature. In the low temperature plus phase, the plus infinite cluster is unique and it "traps" the space T x Z and prevents co-existence of the minus infinite cluster. For the FK random cluster models (which are dependent percolation models) on T x Z, the number of infinite (open) clusters may be zero, infinity or one depending on the value of p--the probability of each bond being open. This is an extension of Grimmett and Newman's results for independent percolation on T x Z. We also prove that both the independent percolation model and the FK random cluster models satisfy a finite island property when p is close to 1. Chapter 1 is an introduction. Chapter 2 contains the proof of the uniqueness theorem for independent percolation in half spaces. The proof utilizes only a large deviation estimate and translation invariance of the models along the hyperplane Zᔈ⁻Âč x {0}. The Ising/Potts models and the FK random cluster models on the branching planes are studied in Chapter 3. The methods are to use the FK representation of Ising/Potts systems as dependent percolation models to carry over Grimmett and Newman's results for independent percolation to the Ising/Potts models. However, in order to prove the plane-like behavior of the Ising/Potts models, the corresponding results for independent percolation are not sufficient and this led us to investigate independent percolation again and prove a new finite island property. Chapters 2 and 3 are independent. Readers with basic knowledge of percolation and Ising models can omit chapter 1 and read chapters 2 and 3 directly.

Stochastic processes and statistical mechanics
Mathematical Dynamics and Fractals
Theoretical and Computational Physics
Original source