arXiv research

PCA simplifies multivariate extreme data analysis.

We develop a framework for analyzing extreme values in correlated financial data.

Taxicab correspondence analysis visualizes sparse text data sets.

The book chapter discusses tail risk analysis for financial data using extreme value statistics.

Develops statistical framework for analyzing functional data extremes.

The paper examines extreme value statistics of high-dimensional sample covariances, with applications in finance and image analysis.

We win EVA2025 by estimating extreme precipitation events using Peaks Over Thresholds and martingale testing.

Estimates treatment effects in rare extreme events using EVT.

The study identifies extremal dependence in financial markets using a bootstrap-based testing procedure.

Survey of extreme value modeling techniques for insurance.

Framework reconstructs missing spatio-temporal data for extreme value prediction.

Study of harmonic maps with extreme Kerr-like singularities.

Study axisymmetric waves on extremal Kerr spacetime using physical-space estimates.

Analyzes premium data of Indian non-life insurers, finding GEV distribution best fits Lognormal and GEV extremes.

Sharp inequalities and extremals on compact Riemann surfaces with boundary.

The price of electricity is far more volatile than that of other commodities normally noted for extreme volatility. The possibility of extreme price movements increases the risk of trading in electricity markets. However, underlying the process of price returns is a strong mean-reverting mechanism. We study this featur…

Biarchetype analysis identifies extreme instances of observations and features.

New method uses topological data analysis to study stock market crashes.

Being able to predict the occurrence of extreme returns is important in financial risk management. Using the distribution of recurrence intervals---the waiting time between consecutive extremes---we show that these extreme returns are predictable on the short term. Examining a range of different types of returns and th…

Kernel PCA helps analyze multivariate extremes and clusters them effectively.

Study efficient resource allocation for detecting extreme values.

This paper analyzes extreme flooding risks and proposes insurance and bond solutions.

New method identifies extreme risk propagation in financial networks.

Empirical study on UEEs reveals liquidity's role and universal recovery patterns.

Researchers extend microlocal analysis across event horizons of rotating black holes.

Extends fractional $L^p$ uncertainty principles with extremizers and stability results.

In an Ultrafast Extreme Event (or Mini Flash Crash), the price of a traded stock increases or decreases strongly within milliseconds. We present a detailed study of Ultrafast Extreme Events in stock market data. In contrast to popular belief, our analysis suggests that most of the Ultrafast Extreme Events are not prima…

xVAE models extreme turbulence events in turbulent flows.

This paper uses MIS to identify key financial institutions with minimal risk contagion.

AGCA approximates angular variation on the unit sphere, reducing extremal dependence problems to eigenanalysis.

We generalize to the finite-state case the notion of the extreme effect variable $Y$ that accumulates all the effect of a variant variable $V$ observed in changes of another variable $X$. We conduct theoretical analysis and turn the problem of finding of an effect variable into a problem of a simultaneous decomposition…

This paper is devoted to the study of the max K-armed bandit problem, which consists in sequentially allocating resources in order to detect extreme values. Our contribution is twofold. We first significantly refine the analysis of the ExtremeHunter algorithm carried out in Carpentier and Valko (2014), and next propose…

New model predicts financial tail events using RIA-EVT-Copula.

Study on black holes and photon surfaces in 4D spacetimes, proving uniqueness theorems.

Extremal length is a classical tool in 1-dimensional complex analysis for building conformal invariants. We propose a higher-dimensional generalization for complex manifolds and provide some ideas on how to estimate and calculate it. We also show how to formulate certain natural geometric inequalities concerning moduli…

The paper studies extremal hypersurfaces in ellipsoids using centro-affine geometry.

Introduces Polar Depth for analyzing multivariate heavy-tailed data extremes.

Capturing the dependence structure of multivariate extreme events is a major concern in many fields involving the management of risks stemming from multiple sources, e.g. portfolio monitoring, insurance, environmental risk management and anomaly detection. One convenient (non-parametric) characterization of extremal de…

We derive an extremal fractional Gaussian by employing the Lévy-Khintchine theorem and Lévian noise. With the fractional Gaussian we then generalize the Black-Scholes-Merton option-pricing formula. We obtain an easily applicable and exponentially convergent option-pricing formula for fractional markets. We also carry o…

Generalized diffusion type equations are considered and point symmetry analysis is applied to them. The equations with extremal order point symmetry algebras are described. Some old geometrical results are rederived in connection with theory of these equation.

Study on charged parallel spinors and mass-charge inequalities.

Study of charged scalar fields on Reissner-Nordström spacetimes via energy estimates.

The paper analyzes extreme temperature forecasting using machine learning models.

Neural network model forecasts extreme flood risk.

New framework assesses extreme errors in machine learning models.

We present an alternative to the pseudo-inverse method for determining the hidden to output weight values for Extreme Learning Machines performing classification tasks. The method is based on linear discriminant analysis and provides Bayes optimal single point estimates for the weight values.

In this article we show the relationship between the Pareto distribution and the gamma distribution. This shows that the second one, appropriately extended, explains some anomalies that arise in the practical use of extreme value theory. The results are useful to certain phenomena that are fitted by the Pareto distribu…

Researchers investigate extremal eigenvalues of GJMS operators in fixed conformal classes.