A new method for choosing thresholds in data sequences without assuming distribution.
problem Choosing thresholds for random sequences without distributional assumptions.
method Data-driven threshold machine (DTM) that estimates three parameters of extreme value distributions and extremal index.
result DTM provides a reliable estimate of thresholds with robustness and computational efficiency.
Counterexample disproves key index computation in Gromov's conjecture paper.
problem Disproving an index computation in Gromov's conjecture paper.
method Constructing a counterexample to an index computation.
result Counterexample disproves the main result of the paper.
New index theory proves Gromov's dihedral conjectures.
problem Comparisons and rigidity of scalar curvatures, mean curvatures, and dihedral angles.
method Developed a new index theory for manifolds with polyhedral boundary.
result Proved Gromov's dihedral extremality and rigidity conjectures.
Using daily returns of the S&P 500 stocks from 2001 to 2011, we perform a backtesting study of the portfolio optimization strategy based on the extreme risk index (ERI). This method uses multivariate extreme value theory to minimize the probability of large portfolio losses. With more than 400 stocks to choose from, ou…
Paper models spatio-temporal extremes using conditional variational autoencoders.
problem Modeling co-occurrence of extreme weather events under changing climate conditions.
method Conditional Variational Autoencoder (cXVAE) with CNN integration.
result Accurately emulates spatial fields and recovers extremal dependence with low computational cost.
Cryptocurrency markets show higher spreads during extreme fear and greed phases.
problem Understanding and predicting liquidity withdrawal in cryptocurrency markets.
method Analysis of Crypto Fear & Greed Index and Bitcoin daily data.
result Extreme fear and greed regimes exhibit significantly higher spreads than neutral periods.
Let γ be a non-degenerate Ustilovsky geodesic in Ham(M,ω) generated by H. We give a simple proof of a generalization of the conjecture stated in \cite{virtmorse}, relating the Morse index of γ, as a critical point of the Hofer length functional, with the Conley Zehnder index of the extremizers of H, consid…
Let E be the Engel group and D be a rank 2 bracket generating left invariant distribution with a Lorentzian metric, which is a nondegenerate metric of index 1. In this paper, we first prove that timelike normal extremals are locally maximizing. Second, we obtain a parametrization of timelike, spacelike, lightlike norma…
We investigate the variety of a portfolio of stocks in normal and extreme days of market activity. We show that the variety carries information about the market activity which is not present in the single-index model and we observe that the variety time evolution is not time reversal around the crash days. We obtain th…
Study extreme values of stable random fields on geometric spaces.
problem Understanding extreme values of stable random fields on various geometric spaces.
method Analyzing extreme values through Patterson-Sullivan measures and extremal cocycle growth.
result Established a dichotomy for the growth-rate of maxima sequences of stable random fields.
Punctuated Equilibrium (PE) states that after long periods of evolutionary quiescence, species evolution can take place in short time intervals, where sudden differentiation makes new species emerge and some species extinct. In this paper, we introduce and study the effect of punctuated equilibrium on two different ass…
This study analyzes dynamic connectedness in global supply chain infrastructure portfolios, identifying key risk factors and extreme events.
problem Understanding dynamic connectedness in global supply chain infrastructure portfolios under various risk factors and extreme events.
method Time-varying parameter vector autoregression (TVP-VAR) model to study spillover and interconnectedness of risk factors.
result Risk shocks influence dynamic connectedness between portfolios and risk factors, and extreme events affect investment outcomes.
A new decision tree variant improves linear model performance.
problem Improving decision tree performance on non-linear data.
method Extremely random tree with non-linear data transformation and linear observer.
result Outperforms linear models on benchmark dataset.
Paper proposes a risk index combining frequency and severity of abnormal driving patterns.
problem Assessing driver risk based on telematics data.
method Combines frequency of abnormal driving patterns with severity quantified through tail rarity.
result Developed a risk index that enables reliable discrimination and ranking of drivers.
The paper tackles extreme value statistics for censored data with heavy tails under competing risks.
problem Estimating extreme value index and quantiles of sub-distribution function in heavy-tailed data with censoring and competing risks.
method Asymptotic normality of a novel Aalen-Johansen integral estimator is established for the extreme value index. Estimation of extreme quantiles of cumulative incidence function is also addressed.
result Asymptotic normality of the proposed estimator for extreme value index is established.
Based on a recent theorem due to the authors, it is shown how the extreme tail dependence between an asset and a factor or index or between two assets can be easily calibrated. Portfolios constructed with stocks with minimal tail dependence with the market exhibit a remarkable degree of decorrelation with the market at…
We study the restless bandit associated with an extremely simple scalar Kalman filter model in discrete time. Under certain assumptions, we prove that the problem is indexable in the sense that the Whittle index is a non-decreasing function of the relevant belief state. In spite of the long history of this problem, thi…
Let α be a Morse closed 1-form of a smooth n-dimensional manifold M. The zeroes of α of index 0 or n are called \emph{centers}. It is known that every non-vanishing de Rham cohomology class u contains a Morse representative without centers. The result of this paper is the one-parameter analogue of the l…
Paper evaluates CRPS for extreme event forecasts, finding it unsuitable.
problem Verifying probabilistic forecasts of extreme events is challenging.
method Formal framework using extreme value theory to assess CRPS as a random variable.
result CRPS is unsuitable for extreme event verification.
The book chapter discusses tail risk analysis for financial data using extreme value statistics.
problem Serial dependence in financial time series complicates tail risk assessment.
method The approach involves unconditional and conditional quantile forecasting.
result Serial dependence impacts multivariate tail dependence.
Model captures asymmetric extreme events in financial returns.
problem Capturing asymmetric extreme events in financial returns.
method Two-tailed peak-over-threshold Hawkes model.
result Extreme losses contribute twice as much as gains but decay more quickly.
Formula found for minimum ARI between clusterings of fixed sizes.
problem Understanding the lowest possible agreement between clusterings.
method Explicit formula derivation for minimum ARI.
result A specific pair of clusterings achieving the minimum ARI is provided.
This letter uses the Block Maxima Extreme Value approach to quantify catastrophic risk in international equity markets. Risk measures are generated from a set threshold of the distribution of returns that avoids the pitfall of using absolute returns for markets exhibiting diverging levels of risk. From an application t…
This note studies the behavior of an index I_t which is assumed to be a tradable security, to satisfy the BSM model dI_t/I_t = μdt + σdW_t, and to be efficient in the following sense: we do not expect a prespecified trading strategy whose value is almost surely always nonnegative to outperform the index greatly. The ef…
Machine learning predicts US stock market crashes.
problem Early detection of stock market crises.
method Random Forest and Extreme Gradient Boosting models.
result Extreme Gradient Boosting outperforms other models.
Method identifies financial rogue waves close to their onset.
problem Identifying extreme financial events close to their onset.
method Analogy between rogue waves in optics and financial volatility, using Schrödinger equation with potential shaped by Kerr nonlinearity.
result Numerical gradient spikes at the onset of extreme financial events.
In this paper we discuss the index problem for geometric differential operators (Spin-Dirac operator, Gauß-Bonnet operator, Signature operator) on manifolds with metric horns. On singular manifolds these operators in general do not have unique closed extensions. But there always exist two extremal extensions Dmin …
The paper calculates critical configurations and Morse indices for polygons on circles or ellipses.
problem Finding critical configurations and their properties for polygons on circles or ellipses.
method Computing Morse indices and gradient vector fields for isolated critical points, relating to eigenvalue questions.
result Computed Morse indices and relationships to eigenvalue questions for polygons on circles or ellipses.
The paper examines extreme value statistics of high-dimensional sample covariances, with applications in finance and image analysis.
problem Statistical validation of normal conditions in high-dimensional time series data.
method Generalizes the maximal deviation of sample autocovariances to high dimensions and applies Gumbel-type extreme value asymptotics.
result Gumbel-type extreme value asymptotics holds true for high-dimensional sample covariances.
Accurate forecasting of risk is the key to successful risk management techniques. Using the largest stock index futures from twelve European bourses, this paper presents VaR measures based on their unconditional and conditional distributions for single and multi-period settings. These measures underpinned by extreme va…
New model explains volatility after extreme stock market events.
problem Understanding volatility dynamics after extreme stock market events.
method Proposed a new dynamical model using high frequency minute data.
result Volatility after extreme events follows a stretched exponential decay initially and a power law decay later.
The study finds solar terms significantly impact China's stock market returns and volatility.
problem Investigating the effect of solar terms on China's stock market.
method Regression framework, analyzing multiple solar terms and their impact on return and volatility.
result Solar terms 1, 3, and 4 cause significant positive returns, while 8, 11, and 14 bring high volatility.
We analyze bias in post-bandit inference for stable index algorithms.
problem Bias in post-bandit inference for stable index algorithms.
method Empirical fluid approximation of sampling dynamics.
result Sharp leading-order expressions for bias and expected Z-statistic.
The study uses machine learning to predict CAT bond coupons based on climate data.
problem Predicting CAT bond coupons using climate data.
method Combining climate indicators with machine learning models (random forest, gradient boosting, etc.).
result Extremely randomized trees achieved the lowest RMSE in predicting CAT bond coupons.
Given a triangulation of a closed topological cube, we show that (under some technical condition) there is an essentially unique tiling of a rectangular parallelepiped by cubes, indexed by the vertices of the triangulation. Moreover, i - the combinatorics is preserved, and ii- the boundary is preserved: vertices corres…
Bayesian GPR model predicts extreme stock market losses.
problem Forecasting rare but impactful extreme negative returns in equity markets.
method Developed a Bayesian Generalised Pareto Regression model linking scale parameter to market volatility.
result The Cauchy prior provides the best balance between predictive accuracy and model simplicity.
Let (M^n, g) be a closed smooth Riemannian spin manifold and denote by D its Atiyah-Singer-Dirac operator. We study the variation of Riemannian metrics for the zeta function and functional determinant of D^2, and prove finiteness of the Morse index at stationary metrics, and local extremality at such metrics under gene…
Deep learning improves survival analysis for customer behavior prediction.
problem Predicting customer behavior such as buying, churning, or defaulting.
method Multi-Task Logistic Regression (MTLR) combined with a deep learning architecture.
result The deep learning method outperforms MTLR and CoxPH models in predicting nonlinear dependencies.
This study examines local co-movements in energy, agriculture, and metal markets using copulas.
problem Identifying local dependencies and asymmetries in energy, agriculture, and metal markets.
method Non-parametric mixture copula and copula-based local Kendall's tau approach.
result Increased co-movements in extreme situations, asymmetric local dependence, and diversification potential.
The study measures systemic risk using common and tail dependence factors.
problem Measuring systemic risk accurately during economic downturns.
method Modeling systemic risk with a common factor for market-wide shocks and a tail dependence factor for extreme events.
result Measures including a tail dependence factor offer better forecasting of financial stress than measures based solely on a common factor.
The paper shows real market exists free lunches with vanishing risks.
problem The hypothesis of no free lunches with vanishing risk in real markets.
method Accurately hedged extreme-maturity zero-coupon bond.
result FLVRs naturally exist in the real market.
Large and stable indices of the world wide stock markets such as NYSE and SP 500 together with NASDAQ -- the index representing markets of new trends, and WIG -- the index of the local stock market of Eastern Europe, are considered. Due to the relation between artificial insymmetrised patterns (AIP) and time series, st…
The article models financial asset returns using Gaussian mixtures and EVT-based copulas to price equity options.
problem Modeling financial asset returns and pricing equity options considering extreme values.
method Modeling marginal distributions with Gaussian mixtures and joint dependence structure with EVT-based copulas.
result The approach accurately prices various equity options on Atos and Dassault Systems actions.
We present a new volatility model, simple to implement, that includes a leverage effect whose return-volatility correlation function fits to empirical observations. This model is able to capture both the "retarded effect" induced by the specific risk, and the "panic effect", which occurs whenever systematic risk become…
Paper proposes GAS-ALD model for financial risk prediction.
problem Skewed distribution of financial return data.
method Generalized autoregressive score (GAS) framework with asymmetric Laplace distribution (ALD).
result GAS-ALD model predicts VaR and ES more accurately than traditional models.
The paper bounds the expectation of empirical processes indexed by Hölder classes.
problem Estimating the expectation of the supremum of empirical processes for distributions on bounded sets.
method Providing upper bounds on the expectation of the supremum of empirical processes indexed by Hölder classes.
result Deriving non-asymptotic risk bounds for estimating distributions using empirical processes and IPM.
The so-called Pareto-Levy or power-law distribution has been successfully used as a model to describe probabilities associated to extreme variations of worldwide stock markets indexes data and it has the form Pr(X>x) x∗∗(−alpha)forgamma<x<infinity.Theselectionofthethresholdparametergamma from empirical d…
The paper develops a new geometric framework for analyzing optimal control problems.
problem Analyzing second-order conditions in constrained variational problems.
method Constructing Jacobi curves using L-derivatives and proving Morse-type theorems.
result Connecting the negative inertia index of the Hessian to symplectic invariants of Jacobi curves.