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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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48 results for nonextensive systems

Stock market indices are one of the most investigated complex systems in econophysics. Here we extend the existing literature on stock markets in connection with nonextensive statistical mechanics. We explore the nonextensivity of price volatilities for 34 major stock market indices between 2010 and 2019. We discover t…

2019-01-23abs ↗pdf ↗

Estimate relaxation times in nonextensive systems using gradient flow for Tsallis entropy maximization.

problem Estimating relaxation times in financial market dynamics.
method Developing a method using EGF for maximizing Tsallis entropy.
result Longer relaxation times for nonextensive systems compared to Shannon entropy.

Study detects anomalies in financial markets using GNN and nonextensive entropy.

problem Detecting anomalies in global financial markets with many correlated assets.
method Used Graph Neural Networks (GNN) with nonextensive entropy to measure uncertainty.
result Anomalies are statistically different for nonextensive entropy parameters before, during, and after a crisis.

Ergodicity, this is to say, dynamics whose time averages coincide with ensemble averages, naturally leads to Boltzmann-Gibbs (BG) statistical mechanics, hence to standard thermodynamics. This formalism has been at the basis of an enormous success in describing, among others, the particular stationary state correspondin…

2003-01-16abs ↗pdf ↗

The cornerstone of Boltzmann-Gibbs (BGBG) statistical mechanics is the Boltzmann-Gibbs-Jaynes-Shannon entropy SBGkdxf(x)lnf(x)S_{BG} \equiv -k\int dx f(x)\ln f(x), where kk is a positive constant and f(x)f(x) a probability density function. This theory has exibited, along more than one century, great success in the treatment of syste…

2005-03-02abs ↗pdf ↗

Engle's ARCH algorithm is a generator of stochastic time series for financial returns (and similar quantities) characterized by a time-dependent variance. It involves a memory parameter bb (b=0b=0 corresponds to {\it no memory}), and the noise is currently chosen to be Gaussian. We assume here a generalized noise, name…

2004-01-12abs ↗pdf ↗

Constructions of metrics with special holonomy by methods of exterior differential systems are reviewed and the interpretations of these construction as `flows' on hypersurface geometries are considered. It is shown that these hypersurface 'flows' are not generally well-posed for smooth initial data and counterexamples…

2012-05-31abs ↗pdf ↗

We present results about financial market observables, specifically returns and traded volumes. They are obtained within the current nonextensive statistical mechanical framework based on the entropy Sq=k1i=1Wpiq1q(q)S_{q}=k\frac{1-\sum\limits_{i=1}^{W} p_{i} ^{q}}{1-q} (q\in \Re) ($S_{1} \equiv S_{BG}=-k\sum\limits_{i=1}^{W}p_{i} \l…

2006-01-31abs ↗pdf ↗

We provide evidence that cumulative distributions of absolute normalized returns for the 100100 American companies with the highest market capitalization, uncover a critical behavior for different time scales ΔtΔt. Such cumulative distributions, in accordance with a variety of complex --and financial-- systems, can be m…

2017-02-20abs ↗pdf ↗

The statistics of return distributions on various time scales constitutes one of the most informative characteristics of the financial dynamics. Here we present a systematic study of such characteristics for the Polish stock market index WIG20 over the period 04.01.1999 - 31.10.2005 for the time lags ranging from one m…

2006-03-09abs ↗pdf ↗

Introduces q-paths for generalizing geometric annealing paths in machine learning.

problem Limited applicability of existing path methods in machine learning.
method Develops a family of paths derived from a generalized mean, including geometric and arithmetic mixtures.
result Empirical gains in Bayesian inference and generative model evaluation.

In this article we study the dependence degree of the traded volume of the Dow Jones 30 constituent equities by using a nonextensive generalised form of the Kullback-Leibler information measure. Our results show a slow decay of the dependence degree as a function of the lag. This feature is compatible with the existenc…

2005-10-12abs ↗pdf ↗

Options are financial instruments that depend on the underlying stock. We explain their non-Gaussian fluctuations using the nonextensive thermodynamics parameter qq. A generalized form of the Black-Scholes (B-S) partial differential equation, and some closed-form solutions are obtained. The standard B-S equation ($q=1…

2002-04-15abs ↗pdf ↗

We present a nonlinear stochastic differential equation (SDE) which mimics the probability density function (PDF) of the return and the power spectrum of the absolute return in financial markets. Absolute return as a measure of market volatility is considered in the proposed model as a long-range memory stochastic vari…

2009-01-07abs ↗pdf ↗

Most people are risk-averse (risk-seeking) when they expect to gain (lose). Based on a generalization of ``expected utility theory'' which takes this into account, we introduce an automaton mimicking the dynamics of economic operations. Each operator is characterized by a parameter q which gauges people's attitude unde…

2001-09-11abs ↗pdf ↗

Option pricing formulas are derived from a non-Gaussian model of stock returns. Fluctuations are assumed to evolve according to a nonlinear Fokker-Planck equation which maximizes the Tsallis nonextensive entropy of index qq. A generalized form of the Black-Scholes differential equation is found, and we derive a martin…

2002-05-03abs ↗pdf ↗

The behavior of stock market returns over a period of 1-60 days has been investigated for S&P 500 and Nasdaq within the framework of nonextensive Tsallis statistics. Even for such long terms, the distributions of the returns are non-Gaussian. They have fat tails indicating that the stock returns do not follow a random …

2016-08-28abs ↗pdf ↗

Overview of integrable systems with symmetries, focusing on toric and semitoric systems.

problem Classifying and understanding integrable systems with symmetries.
method Using decorated polygons and controlled bifurcations in one-parameter families of systems.
result Construction of explicit semitoric systems with prescribed invariants.

Learning to control linear systems is statistically hard, especially for underactuated systems.

problem Statistical difficulty of learning to control linear systems, especially underactuated ones.
method Utilized minimax lower bounds and structural assumptions to prove learning complexity can be exponential.
result Learning complexity can be at most exponential with the controllability index of the system.

Discrete-time systems can be characterized by simple flat coordinates and their shifts.

problem Characterizing flatness of discrete-time systems.
method Developed a map from flat coordinates and their shifts to system state and input, fulfilling system equations identically.
result Derived necessary conditions for a system to be flat, without requiring differential geometry methods.

The paper explores when linear system identification is hard or easy, especially for under-actuated systems.

problem Statistical hardness of learning linear systems, especially under-actuated or under-excited systems.
method Using tools from minimax theory and recent statistical tools for finite sample analysis of system identification.
result The controllability index of linear systems affects the sample complexity of identification, making some systems hard to learn.

This paper improves system identification by reducing sample complexity for high-dimensional linear dynamical systems.

problem High sample complexity for learning partially observed linear dynamical systems in high dimensions.
method Introduces an 1\ell_1-regularized estimation method that reduces sample complexity from linear to logarithmic with system dimension.
result Markov parameters can be learned with logarithmic number of samples relative to system dimension, improving sample complexity.

In integrable hydrodynamic systems, coordinates exist where generators and symmetries are simple.

problem Existence of Riemannian invariants for integrable systems of hydrodynamic type.
method Finding coordinates where the generator and all symmetries are diagonal.
result In integrable hydrodynamic systems, there exist coordinates where the generator and all symmetries are diagonal.

This paper studies nonholonomic constraints in Hamiltonian systems, deriving equations and theorems.

problem Analyzing nonholonomic constraints in Hamiltonian systems.
method Deriving distributional RCH systems, geometric constraint conditions, and Hamilton-Jacobi theorems.
result Derives precise geometric constraint conditions and Hamilton-Jacobi theorems for nonholonomic systems.

Estimates input from output of nonlinear systems using ANN.

problem Estimating unknown compositional input from system output.
method Artificial Neural Networks (ANNs) for nonlinear system inversion.
result ANNs can compete with optimal bounds for linear systems and demonstrate promising results for nonlinear systems.

This paper considers control systems defined on Lie algebroids. After deriving basic controllability tests for general control systems, we specialize our discussion to the class of mechanical control systems on Lie algebroids. This class of systems includes mechanical systems subject to holonomic and nonholonomic const…

2004-02-26abs ↗pdf ↗

Systemic risk refers to the risk that the financial system is susceptible to failures due to the characteristics of the system itself. The tremendous cost of systemic risk requires the design and implementation of tools for the efficient macroprudential regulation of financial institutions. The current paper proposes a…

2015-02-27abs ↗pdf ↗

The paper develops methods to derive mixed superposition rules for Lie systems and applies them to various physical systems.

problem Finding general solutions for Lie systems.
method Develops mixed superposition rules for Lie systems with imprimitive Lie algebras and semidirect sums.
result Extends coalgebra method to Lie systems of partial differential equations.

Paper develops reduction theory for controlled Lagrangian systems with symmetry and momentum map.

problem Reduction of controlled Lagrangian systems with symmetry and momentum map.
method Using Legendre transformation and Euler-Lagrange vector field, the paper extends symmetric reduction theory.
result Established regular reduction theory for RCL systems with symmetry and momentum map.

The paper studies connections in superintegrable systems, revealing geometric insights.

problem Understanding non- and semi-degenerate superintegrable systems.
method Analyzes two torsion-free connections associated with superintegrable systems.
result Semi-degenerate secondary structure tensor is the Ricci curvature of a natural torsion-free connection.

This paper proposes a system-agnostic policy for dynamic scheduling.

problem Dynamic scheduling in changing systems is challenging due to system-specific optimal policies.
method Descriptive policy that learns a system-agnostic scheduling principle.
result System-agnostic meta-learning enables adaptation to unseen system characteristics.