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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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7142128 · Jun 202619922001200920172026
48 results for Value-at-Risk caps

Comonotonic allocations are restored under certain constraints, improving risk-sharing.

problem Feasibility constraints can distort optimal risk-sharing allocations.
method Identified componentwise convex-order solidity as a sufficient condition to restore comonotonic allocations.
result Componentwise convex-order solidity ensures comonotonic improvements under feasible constraints.

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

problem Approximating angular variation in multivariate extremes.
method Anchored geodesic component analysis (AGCA) approximates angular variation by great subspheres constrained to pass through a chosen reference direction.
result AGCA finds concentrated tail directions in daily equity-portfolio losses, explaining about 91% of anchored variation.

Study improves portfolio risk estimation methods using robust covariance and CVaR constraints.

problem Improving portfolio risk estimation in the presence of financial data noise and extreme market conditions.
method Exploration of robust covariance estimators, application of CVaR constraints, use of K-means clustering in optimization.
result Robust covariance estimators can outperform market-weighted benchmarks, especially during bull markets.

It is classically known that generic smooth maps of R^2 into R^3 admit only cross cap singularities. This suggests that the class of cross caps might be an important object in differential geometry. We show that the standard cross cap (u,uv,v^2) has non-trivial isometric deformations with infinite dimensional freedom. …

2012-07-17abs ↗pdf ↗

This paper proves geodesic curvature measures are bounded for curves near cross cap singularities.

problem Boundedness of geodesic curvature measures near cross cap singularities.
method Analyzes intrinsic cross cap singularities and extends Gauss-Bonnet formula.
result Proves boundedness of geodesic curvature measures for curves near cross cap singularities.

This research improves value-at-risk estimation during financial crises using non-extensive statistical methods.

problem Underestimation of value-at-risk during financial crises.
method Non-extensive value-at-risk model based on Tsallis entropy and q-Gaussian probability density function.
result The q-Gaussian model provides better value-at-risk estimation during financial crises.

We give a variational proof of the existence and uniqueness of a convex cap with the given upper boundary. The proof uses the concavity of the total scalar curvature functional on the space of generalized convex caps. As a byproduct, we prove that generalized convex caps with the fixed boundary are globally rigid, that…

2007-03-06abs ↗pdf ↗

In the paper we consider the following conjecture: if a finite group GG possesses a solvable ππ-Hall subgroup HH, then there exist elements x,y,z,tGx,y,z,t\in G such that the identity HHxHyHzHt=Oπ(G)H\cap H^x\cap H^y\cap H^z\cap H^t=O_π(G) holds. The minimal counter example is shown to be an almost simple group of Lie type.

2008-12-17abs ↗pdf ↗

Study analyzes order transitions in high, medium, and low market cap stocks using Markov chains.

problem Understanding order transitions in stocks of different market caps.
method First-order discrete-time Markov chain model applied to NASDAQ100 stocks.
result Limit orders exhibit higher inertia during opening hours but decrease in subsequent hours, while market orders increase.

Researchers extend CCVaR to multivariate data using Archimedean copulas.

problem No multivariate extension for CCVaR when dependence is given by Archimedean copulas.
method Derive an almost closed-form expression for CCVaR under an Archimedean copula, examine coherence conditions, and conduct numerical experiments.
result An almost closed-form expression for CCVaR under an Archimedean copula is derived.

We show that there is a well-defined cap-product structure on the Fintushel-Stern spectral sequence. Hence we obtain the induced cap-product structure on the ${\BZ}_8$-graded instanton Floer homology. The cap-product structure provides an essentially new property of the instanton Floer homology, from a topological poin…

1997-10-20abs ↗pdf ↗

Let MM be a smooth closed 4k4k-manifold whose Yamabe invariant Y(M)Y(M) is nonpositive. We show that Y(MlHPkmHPkˉ)=Y(M),Y(M\sharp l \Bbb HP^k\sharp m \bar{\Bbb HP^k})=Y(M), where l,ml,m are nonnegative integers, and HPk\Bbb HP^k is the quaternionic projective space. When k=4k=4, we also have $$Y(M\sharp l CaP^2\sharp m \bar{CaP^2})=Y(M),…

2007-10-12abs ↗pdf ↗

This paper examines the valuation of American capped call options with two-level caps. The structure of the immediate exercise region is significantly more complex than in the classical case with constant cap. When the cap grows over time, making extensive use of probabilistic arguments and local time, we show that the…

2017-07-19abs ↗pdf ↗

We construct cup and cap products in intersection (co)homology with field coefficients. The existence of the cap product allows us to give a new proof of Poincare duality in intersection (co)homology which is similar in spirit to the usual proof for ordinary (co)homology of manifolds.

2011-06-23abs ↗pdf ↗

Financial institutions have to allocate so-called "economic capital" in order to guarantee solvency to their clients and counter parties. Mathematically speaking, any methodology of allocating capital is a "risk measure", i.e. a function mapping random variables to the real numbers. Nowadays "value-at-risk", which is d…

2002-03-27abs ↗pdf ↗

Investors face constraints in Heston's model; optimal allocation differs from naive capped strategy.

problem Optimizing portfolio allocation with convex constraints in Heston's stochastic volatility model.
method Applied duality methods to derive a closed-form solution.
result The optimal constrained portfolio allocation differs from the naive capped portfolio, leading to different wealth outcomes.

Study optimal portfolio selection with Recovery Average Value at Risk, showing better control over liabilities.

problem Optimizing portfolios with a new risk measure under known or uncertain distributions.
method Existence results for mean-risk optimal portfolios under different distributional assumptions.
result Portfolio selection under Recovery Average Value at Risk provides better control over liabilities.

The paper studies parallel surfaces of cuspidal cross caps and their degeneracy.

problem Investigating the geometry and singularities of parallel surfaces of cuspidal cross caps.
method Established a criterion for the degeneracy of the distance squared function using geometric invariants.
result Parallel surfaces degenerate into a degenerated cuspidal S1 singularity at specific distances.

Approximate Incremental Value-at-Risk formulae provide an easy-to-use preliminary guideline for risk allocation. Both the cases of risk adding and risk pooling are examined and beta-based formulae achieved. Results highlight how much the conditions for adding new risky positions are stronger than those required for ris…

2002-04-28abs ↗pdf ↗

Improved multilevel scheme for value-at-risk computation.

problem Discontinuity in Heaviside function affects value-at-risk computation.
method Adaptive multilevel stochastic approximation to mitigate discontinuity.
result Best complexity improved to O(ε2lnε52\varepsilon^{-2}|\ln{\varepsilon}|^\frac52).

Value-at-Risk is a flawed substitute for non-ruin capital, leading to misleading financial standards.

problem Misuse of Value-at-Risk as a risk measure, replacing non-ruin capital, leads to flawed financial standards.
method Mathematical analysis of risk measures and their implications on financial standards.
result Non-ruin capital is a more accurate risk measure than Value-at-Risk, necessitating its adoption over the former.

Extended univariate Range Value-at-Risk to multivariate settings.

problem Inability of traditional risk measures for heavy-tail distributions and infinite tail expectations.
method Multivariate definitions of robust truncated tail expectations, robustness and properties derived, closed-form expressions and special cases discussed.
result Empirical estimators accuracy examined through numerical and graphical examples.

The paper analyzes how to combine self-protection and self-insurance for risk reduction.

problem Combining self-protection and self-insurance for risk reduction when market insurance is absent.
method The approach uses Value-at-Risk and Tail Value-at-Risk to evaluate residual risk and solves the problem using isoquant geometry based on marginal-balance curves.
result The analysis identifies the conditions under which self-protection and self-insurance behave as substitutes or complements.

A new tail-shape index based on Value at Risk and Expected Shortfall.

problem Measuring and comparing tail behavior of loss distributions.
method Introducing a new θθ-index based on equal level relationships between Value at Risk and Expected Shortfall.
result The θθ-index provides a level-dependent, scale-free measure of upper tail behavior.

FSD-CAP improves graph feature imputation under high missing rates.

problem Challenges in imputing missing node features in graphs, especially under high missing rates.
method Two-stage framework: subgraph expansion, fractional diffusion, class-aware propagation.
result Significantly improved imputation quality compared to existing methods, achieving high accuracy on benchmark datasets.

The study finds the optimal metrics for free boundary minimal surfaces in spherical caps.

problem Optimizing metrics for free boundary minimal surfaces in spherical caps.
method Introducing functionals based on eigenvalues of Steklov-type problems and proving maximizers are induced by immersions.
result Maximizing metrics are induced by free boundary minimal immersions in geodesic balls of a round sphere.

A new framework for robust risk measurement and portfolio optimization.

problem Uncertainty in mean-covariance space and portfolio optimization challenges.
method Modeling uncertainty with Gelbrich distance and prior structural information, related to optimal transport theory.
result Mean-covariance robust portfolio optimization simplifies to Markowitz model with a regularization term.