Future grid scenario analysis requires a major departure from conventional power system planning, where only a handful of most critical conditions is typically analyzed. To capture the inter-seasonal variations in renewable generation of a future grid scenario necessitates the use of computationally intensive time-seri…
On-device research index
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
Trend · papers per month
48 results for “future stability”
Future stability of FLRW solutions in expanding 3D space is shown for compact perturbations.
problem Future stability of expanding FLRW solutions with spatial topology R^3.
method Nonlinear stability analysis of spherically symmetric perturbations.
result Decay rates of energy momentum tensor components compared to Minkowski space.
The study establishes stability in WMOT, crucial for finance with imprecise data.
problem Stability in weak martingale optimal transport for finance with imprecise data.
method Established stability through rigorous mathematical analysis.
result Stability of WMOT is proven, with applications to VIX futures and Brownian motion.
We study constant mean curvature Lorentzian hypersurfaces of from the point of view of its Cauchy problem. We completely classify the spherically symmetric solutions, which include among them a manifold isometric to the de Sitter space of general relativity. We show that the spherically symmetric s…
Study on future stability of FLRW spacetime solutions with decelerated expansion.
problem Stability of solutions to Einstein equations coupled with a nonlinear scalar field.
method Decomposition of metric and scalar field perturbations into spatial averages and oscillatory remainders.
result Future-stability of FLRW spacetime solutions for .
We study the small perturbations of the -dimensional Milne model for the Einstein-Klein-Gordon (EKG) system. We prove the nonlinear future stability, and show that the perturbed spacetimes are future causally geodesically complete. For the proof, we work within the constant mean curvature (CMC) gauge and focus on …
Optimizes dividends with stability for risky businesses.
problem Maximizing dividends with stability in risky businesses.
method Linear-quadratic optimization for a general Lévy process.
result Derives optimal affine dividend strategies with stability.
New proof of stability for expanding Kerr-de Sitter spacetimes with smoothness at the boundary.
problem Stability of expanding region of Kerr-de Sitter spacetimes.
method Modified generalized harmonic gauge, local stability near conformal boundary, smoothness down to future conformal boundary.
result Smoothness of conformally rescaled metric down to future conformal boundary with mild singularity.
New proof of Schwarzschild stability using geometric gauge.
problem Linear stability of Schwarzschild spacetime under gravitational perturbations.
method Employing a new geometric gauge and exploiting the structure of transport equations.
result Established both orbital and asymptotic stability for linearised quantities.
A new proof of Friedrich's theorem on the existence and stability of asymptotically de Sitter spaces in 3+1 dimensions is given, which extends to all even dimensions. In addition, we characterize the possible limits of spaces which are globally asymptotically de Sitter, to the past and future.
Paper uses Ricci curvature to measure and forecast China's stock market stability.
problem Measuring and predicting systemic stability of China's stock market.
method Geometric measure derived from discrete Ricci curvature applied to financial networks.
result Ricci curvature effectively captures market stability and predicts future trends.
Survey of stablecoins to reduce cryptocurrency volatility.
problem Reduction of cryptocurrency volatility during financial crises.
method Classification of stablecoin approaches and assessment of tradeoffs.
result Different stablecoin types offer varying tradeoffs and challenges.
Stability of a special spacetime solution is proven under certain symmetries.
problem Understanding the long-time behavior of cosmological solutions with symmetries.
method Proves stability of double-cusp spacetime solution under small T2-symmetry-preserving perturbations.
result Double-cusp solution is stable under small T2-symmetry-preserving perturbations.
Feedback loops amplify dataset biases, affecting future model performance.
problem Feedback loops amplify biases in datasets, risking future model reliability.
method Formalized system where model interactions are recorded and reused, analyzed for bias amplification.
result Models that behave like samples from the training distribution are more stable and calibrated.
Extends martingale transport for robust finance problems.
problem Addressing specific robust finance problems not covered by standard martingale transport.
method Introduces an additional parameter to the weak martingale optimal transport problem and proves stability.
result Stability of the extended problem with respect to risk-neutral marginal distributions.
The paper proves smoothness of event horizons in Kerr spacetime perturbations.
problem Smoothness of event horizons in Kerr spacetime perturbations.
method Proof of smoothness using stability of slowly rotating Kerr spacetimes.
result Smooth null hypersurfaces of event horizons are proven for Kerr spacetime perturbations.
Humans learn a predictive model of the world and use this model to reason about future events and the consequences of actions. In contrast to most machine predictors, we exhibit an impressive ability to generalize to unseen scenarios and reason intelligently in these settings. One important aspect of this ability is ph…
Proves stability of Schwarzschild black holes without symmetry assumptions.
problem Stability of Schwarzschild black holes under general conditions.
method Teleologically normalised double null gauges, analysis of linear stability, and control of non-linearities.
result Proves non-linear asymptotic stability of Schwarzschild family as solutions to Einstein vacuum equations.
We propose a modelling framework for the optimal selection of crypto assets. Crypto assets differ by two essential features: security (technological) and stability (governance). Investors make choices over crypto assets similarly to how they make choices by using a recommender app: the app presents each investor with a…
Gradient descent on neural nets often operates at the Edge of Stability, where loss behavior is complex but loss decreases over time.
problem Understanding the optimization dynamics of neural networks at the Edge of Stability.
method Empirical demonstration of gradient descent behavior in neural network training.
result Gradient descent on neural networks typically occurs at the Edge of Stability, where loss behavior is non-monotonic but loss decreases over time.
We prove nonlinear stability for a large class of solutions to the Einstein equations with a positive cosmological constant and compact spatial topology in arbitrary dimensions, where the spatial metric is Einstein with either positive or negative Einstein constant. The proof uses the CMC Einstein flow and stability fo…
Proves stability of Minkowski space for specific initial data.
problem Stability of Minkowski space under spacelike-characteristic initial data.
method Vectorfield method and bootstrapping argument, with new geometric constructions.
result Global nonlinear stability of Minkowski space proved for the spacelike-characteristic Cauchy problem.
Paper analyzes stability and generalization of SCO algorithms.
problem Understanding how SCO algorithms perform on unseen data.
method Algorithmic stability analysis in statistical learning theory.
result Derives dimension-independent excess risk bounds for SCGD and SCSC.
New framework for gravitational perturbations of Kerr spacetimes, focusing on stability.
problem Stability of Kerr spacetimes to gravitational perturbations.
method New geometric framework with tailored null frames and gauge, reformulating Einstein equations.
result Derivation of linearised vacuum Einstein equations in the new framework.
New memory effect discovered in gravitational wave behavior.
problem Understanding gravitational wave behavior in spacetimes with angular momentum.
method Mathematical analysis of Minkowski spacetime and Kerr black holes.
result Angular momentum memory effect observed at future null infinity.
New algorithm borrows future randomness to stabilize model-free control.
problem Double sampling problem in model-free control with nonlinear approximations.
method Borrowing from the future (BFF) algorithm to approximate re-sampling of next states.
result BFF is close to unbiased SGD under smooth dynamics, validated by simulations.
Efficiently calibrates Bergomi models to VIX derivatives using vector quantization.
problem Calibrating Bergomi models to VIX derivatives for accurate pricing.
method Applied vector quantization in mixed Bergomi models for fast and efficient option pricing.
result Calibration of Bergomi models to VIX derivatives is feasible and accurate over daily data.
We introduce a method to predict which correlation matrix coefficients are likely to change their signs in the future in the high-dimensional regime, i.e. when the number of features is larger than the number of samples per feature. The stability of correlation signs, two-by-two relationships, is found to depend on thr…
Analyzes how many people can receive stable income in a pooled annuity fund.
problem Quantifying the trade-off between income stability and the number of members in a pooled annuity fund.
method Investment returns held constant, systematic longevity risk omitted. Derived an analytical expression for income stability.
result The number of fund members who receive stable income is independent of the mortality model.
This paper contains the second part of a two-part series on the stability and instability of extreme Reissner-Nordstrom spacetimes for linear scalar perturbations. We continue our study of solutions to the linear wave equation on a suitable globally hyperbolic subset of such a spacetime, arising from regular initial da…
We study the problem of stability and instability of extreme Reissner-Nordstrom spacetimes for linear scalar perturbations. Specifically, we consider solutions to the linear wave equation on a suitable globally hyperbolic subset of such a spacetime, arising from regular initial data prescribed on a Cauchy hypersurface …
In this global study of solutions to the linear wave equation on Schwarzschild de Sitter spacetimes we attend to the cosmological region of spacetime which is bounded in the past by cosmological horizons and to the future by a spacelike hypersurface at infinity. We prove an energy estimate capturing the expansion of th…
We show that a set of conformally invariant equations derived from the Fefferman-Graham tensor can be used to construct global solutions of the vacuum Einstein equations, in all even dimensions. This gives, in particular, a new, simple proof of Friedrich's result on the future hyperboloidal stability of Minkowski space…
Due to the liberalization of markets, the change in the energy mix and the surrounding energy laws, electricity research is a dynamically altering field with steadily changing challenges. One challenge especially for investment decisions is to provide reliable short to mid-term forecasts despite high variation in the t…
New credit attribution methods for machine learning models using relaxed stability guarantees.
problem Ensuring proper attribution in generative models trained on existing works.
method Proposed new definitions of stability that allow for non-stable processing of a subset of datapoints with permission.
result Extended well-studied stability notions and provided a comprehensive characterization of learnability.
We propose a framework for general probabilistic multi-step time series regression. Specifically, we exploit the expressiveness and temporal nature of Sequence-to-Sequence Neural Networks (e.g. recurrent and convolutional structures), the nonparametric nature of Quantile Regression and the efficiency of Direct Multi-Ho…
This paper considers the stability of online learning algorithms and its implications for learnability (bounded regret). We introduce a novel quantity called {\em forward regret} that intuitively measures how good an online learning algorithm is if it is allowed a one-step look-ahead into the future. We show that given…
Neuro-symbolic traders suppress market prices, highlighting risks to stability.
problem Understanding and quantifying the influence of AI-generated financial models on markets.
method Developed virtual neuro-symbolic traders using deep generative models and tested them in a virtual market.
result Neuro-symbolic traders suppress market prices compared to historical data, indicating potential market instability.
Partially performative prediction studies how predictive models influence future data.
problem Distribution shift in predictive models due to endogenous and exogenous factors.
method Generalizing performative prediction to capture both endogenous and exogenous sources of distribution shift.
result Developed online analogues of performative stability and optimality for partially performative environments.
The Impact of Bitcoin ETF Approval on Bitcoin's Hedging Properties Against Traditional Assetsq-fin.GN
ETF approval boosts Bitcoin's correlation with equities, stabilizes with gold, and maintains negative correlation with fiat currencies.
problem Impact of Bitcoin ETF approval on Bitcoin's relationships with traditional assets.
method Rolling correlation analysis, Chow tests, and DCC-GARCH models.
result Bitcoin's correlation with equities increased significantly post-ETF approval, while its relationship with gold stabilized and remained negatively correlated with fiat currencies.
This paper introduces Libra to analyze and optimize generalization in Federated Learning.
problem Inconsistent local optima in Federated Learning lead to poor generalization performance.
method Introduces Libra, a generalization dynamics analysis framework for algorithm-dependent excess risk minimization.
result Libra highlights the trade-offs between model stability and gradient norms in Federated Learning.
Eight different refinements of trapped surfaces are proposed, of three basic types, each intended as potential stability conditions. Minimal trapped surfaces are strictly minimal with respect to the dual expansion vector. Outer trapped surfaces have positivity of a certain curvature, related to surface gravity. Increas…
Online algorithms stabilize in feedback loops of performative prediction.
problem Feedback loops in algorithmic predictions influence data distributions.
method Martingale argument and randomization to avoid distributional assumptions.
result No-regret algorithms converge to performatively stable equilibria.
This study analyzes AdaGrad's stability and convergence in non-convex optimization.
problem Lack of theoretical analysis for AdaGrad in non-convex optimization.
method Novel stopping time-based techniques from probability theory.
result Established stability and derived convergence rates for AdaGrad.
MuZero visualizes its internal representations to stabilize planning.
problem Stability issues in MuZero's planning process.
method Visualized MuZero's latent representations and proposed regularization techniques.
result Action trajectories diverge between observation embeddings and internal state transitions, leading to instability.
The paper validates a classifier for identifying intraday regime shifts in MNQ futures.
problem Developing reliable trading signals from intraday regime shifts in MNQ futures.
method Constructed a composite day-classification system using three observable conditions.
result Classifier-positive days exhibit distinct intraday behavior but fail to generate profitable trading signals.
Study finds machine learning interpretations are often unstable and unreliable.
problem Reliability of machine learning interpretations in high-stakes domains.
method Stability study on global interpretations using tabular data.
result Popular interpretation methods are frequently unstable, less stable than predictions, and not associated with prediction accuracy.
Survey on learning with graph-dependent data, deriving new generalization bounds.
problem Traditional i.i.d. data assumption fails in many real-life applications.
method Collect and analyze graph-dependent concentration bounds, derive generalization bounds.
result New generalization bounds for graph-dependent data.