Tail Dependence of Factor Models

Y. Malevergne; D. Sornette

Home/Archive/arXiv

arXiv · cond-mat/0202356

Tail Dependence of Factor Models

Y. Malevergne·D. Sornette

View original source ↗Read source document ↗Export metadata ↓

Abstract

Using the framework of factor models, we establish the general expression of the coefficient of tail dependence between the market and a stock (i.e., the probability that the stock incurs a large loss, assuming that the market has also undergone a large loss) as a function of the parameters of the underlying factor model and of the tail parameters of the distributions of the factor and of the idiosyncratic noise of each stock. Our formula holds for arbitrary marginal distributions and in addition does not require any parameterization of the multivariate distributions of the market and stocks. The determination of the extreme parameter, which is not accessible by a direct statistical inference, is made possible by the measurement of parameters whose estimation involves a significant part of the data with sufficient statistics. Our empirical tests find a good agreement between the calibration of the tail dependence coefficient and the realized large losses over the period from 1962 to 2000. Nevertheless, a bias is detected which suggests the presence of an outlier in the form of the crash of October 1987.

Explore related subjects

cond-mat.stat-mech q-fin.PM

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Y. Malevergne, D. Sornette. 2002-02-20. Tail Dependence of Factor Models. https://arxiv.org/abs/cond-mat/0202356

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

KEEP EXPLORING

Related papers

arXiv2026

Feedback percolation on complex networks

Traditional percolation theory assumes static microscopic rules, limiting its ability to describe real-world complex systems where macroscopic order actively regulates local interactions. Here, we introduce feedback percolation, an unified framework that dynamically couples the microscopic activation probability to the macroscopic size of the giant component. We show that this simple feedback mechanism produces a rich variety of behaviors both analytically and numerically. Depending on the feedback functions, the system exhibits explosive discontinuous jumps, hybrid transitions, limit-cycle oscillations, and routes to chaos, absent in classical percolation. Our findings establish that macroscopic feedback provides a unifying physical mechanism for phenomena ranging from self-regulating oscillations to systemic infrastructure collapse.

cond-mat.stat-mech↗

arXiv2026

$\mathbb{Z}_2$ gauge and exact solution of the $\pm J$ Edwards-Anderson model in a transverse field

Using the Majorana representation of spin-1/2 operators, we study the $\pm J$ Edwards--Anderson model in a transverse field at $T=0$. We show that, in this representation, the quantity describing the coupling between neighboring spins commutes with the Hamiltonian and, unlike in the Kitaev model, is not subject to any Gauss law. The resulting $\mathbb{Z}_2$ gauge freedom allows the disorder in the signs of the exchange integrals to be eliminated by an exact gauge transformation, so that the spectrum of the system coincides with that of the model with uniform couplings. The resulting theory is quadratic in the Majorana fields. Computing the local Green's functions, we find that the Edwards--Anderson order parameter vanishes for $Δ>J\sqrt{Z}$ and equals $1/4$ for $Δ<J\sqrt{Z}$, which signals a second-order transition from a paramagnetic phase to a spin-glass ground state that is degenerate over spin configurations and replica symmetric at $T=0$.

cond-mat.stat-mech↗

arXiv2026

Thermalization of coarse-grained variables in the Toda lattice: a numerical study

We present here a numerical study of the Toda lattice Hamiltonian dynamics showing how, despite model integrability, it is possible to find many macroscopic observables which display standard equilibrium behavior. In particular, we study numerically the energy time correlation of certain coarse-grained variables, showing that it decays with either exponential or stretched exponential behaviour, thus indicating good thermalization properties. The spirit of our observation is complementary to that of standard Fermi-Pasta-Ulam-Tsingou-like numerical experiments, in which the breaking of integrability is regarded as the key ingredient for relaxation to thermal equilibrium. The present communication corroborates, on the contrary, the view that integrability is not an obstacle to thermalization, provided that a sufficiently weak definition of the latter is accepted. In the Toda lattice we have introduced several kinds of coarse-grained variables, constructed with the purpose to maintain a thermodynamic relevance also for large system sizes, which all show good thermalization properties.

cond-mat.stat-mech↗