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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.

168,657 papers · 148 categories

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2615227821,043 · Jun 202019922001200920172026
48 results for relative performance concerns

This paper studies how relative performance concerns affect stock prices in a tree-like market model.

problem The impact of relative performance concerns on stock prices in a tree-like market model.
method Mean-field equilibrium analysis in a binomial tree framework with exponential utility.
result Existence and uniqueness of market-clearing mean-field equilibrium in both single- and multi-population settings.

Study of portfolio management under relative performance concerns using mean field games.

problem Portfolio management problems under relative performance concerns.
method Forward utilities of CARA type, mean field games, best response and equilibrium strategies.
result Solve forward-utility finite player game and mean-field game under asset specialization.

New framework for portfolio management using binomial markets and game theory.

problem Investment behavior in competitive and incomplete markets.
method Introduces PRFPP framework, constructs and analyzes for both finite and mean field games.
result Relative performance concerns do not always lead to more risky asset investment.

Study Nash equilibrium in market with relative wealth concerns under partial information and heterogeneous priors.

problem Analyzing Nash equilibrium in a market with unobservable return rates and heterogeneous priors.
method Established a Nash equilibrium through a separation result and martingale argument. Used fully-coupled linear FBSDEs and deep neural networks for numerical computation.
result Investment strategies under relative wealth concerns exhibit a herd effect, with accurate prior estimators leading the market.

We investigate the effects of the social interactions of a finite set of agents on an equilibrium pricing mechanism. A derivative written on non-tradable underlyings is introduced to the market and priced in an equilibrium framework by agents who assess risk using convex dynamic risk measures expressed by Backward Stoc…

2015-11-13abs ↗pdf ↗

This paper addresses privacy concerns in ratio statistics using differential privacy.

problem Privacy concerns in ratio statistics across machine learning areas.
method Develops a simple algorithm for differentially private ratio statistics, proving consistency and constructing confidence intervals.
result A simple algorithm can provide excellent privacy, sample accuracy, and bias properties in ratio statistics.

The paper analyzes performance criteria for competing fund managers in Ito-diffusion markets.

problem Analyzing performance of competing fund managers in Ito-diffusion markets.
method Developed forward relative performance criteria and forward Nash equilibrium for passive and competitive cases.
result Extended performance criteria for investment problems in Ito-diffusion markets.

Relative notions of combinatorial asphericity have been used to prove that injective labeled oriented trees (which encode spines of ribbon 2-knots) are aspherical. This article presents an overview and comparison of the different notions of relative combinatorial asphericity. It also contains new results concerning cha…

2019-04-16abs ↗pdf ↗

This is the third and last in our series of papers concerning rough solutions of the Einstein vacuum equations expressed relative to wave coordinates. In this paper we prove an important result concerning Ricci defects of microlocalized solutions, stated and used in the proof of the crucial Asymptotics Theorem in our s…

2001-10-08abs ↗pdf ↗

Ditto improves fairness and robustness in federated learning.

problem Fairness and robustness in statistically heterogeneous federated learning networks.
method Personalized federated learning framework (Ditto) with a scalable solver.
result Ditto achieves competitive performance and superior fairness and robustness compared to existing methods.

The concept of an objective spatial direction in special relativity is investigated and theories assuming light-speed isotropy while accepting the existence of a privileged spatial direction are classified. A natural generalization of the proper time principle is introduced which makes it possible to devise experimenta…

2010-08-21abs ↗pdf ↗

We revisit McLean's second variation formulas for calibrated submanifolds in exceptional geometries, and correct his formulas concerning associative submanifolds and Cayley submanifolds, using a unified treatment based on the (relative) calibration method and Harvey-Lawson's identities.

2016-05-04abs ↗pdf ↗

We consider a skew ruled surface ΦΦ in the Euclidean space E3E^{3} and relative normalizations of it, so that the relative normals at each point lie in the corresponding asymptotic plane of ΦΦ. We call such relative normalizations and the resulting relative images of ΦΦ \emph{asymptotic}. We determine all ruled surf…

2013-07-23abs ↗pdf ↗

Study of insurer games with model uncertainty in reinsurance and investment strategies.

problem Model uncertainty and competitive insurers' performance under worst-case scenarios.
method Formulated robust mean-field game for non-linear system, derived closed-form solutions.
result Relative concerns lead to new hedging terms in investment and reinsurance strategies.

In this paper we deal with relative normalizations of hypersurfaces in the (n+1)-dimensional Euclidean space Rn+1\mathbb{R}^{n+1}. Considering a relative normalization yˉ\bar{y} of an hypersurface ΦΦ we decompose the corresponding Tchebychev vector Tˉ\bar{T} in two components, one parallel to the Tchebychev vector $\bar…

2015-11-29abs ↗pdf ↗

A new framework evaluates deep learning vs classical forecasting methods for time series predictions.

problem Current forecasting model evaluation metrics fail to capture model performance differences.
method Proposes a novel framework for evaluating univariate time series forecasting models from multiple perspectives.
result Deep learning models like NHITS outperform classical methods in multi-step ahead forecasting but not in anomaly handling.

This paper deals with skew ruled surfaces Φ\varPhi in the Euclidean space E3\mathbb{E}^{3} which are right normalized, that is they are equipped with relative normalizations, whose support function is of the form q(u,v)=f(u)+g(u)vw(u,v)q(u,v) = \frac{f(u) + g(u)\, v}{w(u,v)}, where w2(u,v)w^2(u,v) is the discriminant of the first fundamental f…

2017-06-21abs ↗pdf ↗

Deep network learns Obstacle Tower challenge without human demonstrations.

problem Master procedurally generated levels that get progressively harder.
method Deep Reinforcement Learning with a simple feed-forward network.
result Performed competitively in a reinforcement learning competition.

In this paper we define and develop the theory of the cohomology of a profinite group relative to a collection of closed subgroups. Having made the relevant definitions we establish a robust theory of cup products and use this theory to define profinite Poincaré duality pairs. We use the theory of groups acting on prof…

2017-10-02abs ↗pdf ↗

Study Nash equilibrium in mean field portfolio games with random market parameters.

problem Modeling wealth and relative performance in competitive financial markets.
method Martingale optimality principle approach to characterize Nash equilibrium in mean field FBSDE.
result Unique Nash equilibrium found under weak interaction assumption and market parameters independence.

The paper analyzes how investors' wealth can decline collectively under partial information.

problem Investors' wealth can decline collectively under partial information.
method The paper derives a Nash equilibrium for mean-variance portfolio selection under relative performance criteria, considering both full and partial information.
result Relative performance criteria can lead to downward self-reinforcement of investors' wealth, which is more pronounced under partial information.

While the Machine Learning (ML) landscape is evolving rapidly, there has been a relative lag in the development of the "learning systems" needed to enable broad adoption. Furthermore, few such systems are designed to support the specialized requirements of scientific ML. Here we present the Data and Learning Hub for sc…

2018-11-27abs ↗pdf ↗

We introduce the notion of directed diagrammatic reducibility which is a relative version of diagrammatic reducibility. Directed diagrammatic reducibility has strong group theoretic and topological consequences. A multi-relator version of the Freiheitssatz in the presence of directed diagrammatic reducibility is given.…

2019-03-11abs ↗pdf ↗

The classical notion of center of mass for an isolated system in general relativity is derived from the Hamiltonian formulation and represented by a flux integral at infinity. In contrast to mass and linear momentum which are well-defined for asymptotically flat manifolds, center of mass and angular momentum seem less …

2011-01-03abs ↗pdf ↗

Study many-player investment-consumption games with power FPPs, finding market-risk preference affects consumption.

problem Investment and consumption optimization in a mean field competition setting.
method Solve many-player and mean field games using power FPPs, providing closed-form solutions.
result Market-risk relative consumption preference affects agent's consumption decisions.

In this paper we consider the problem of minimizing the relative perimeter under a volume constraint in the interior of a conically bounded convex set, i.e., an unbounded convex body admitting an \emph{exterior} asymptotic cone. Results concerning existence of isoperimetric regions, the behavior of the isoperimetric pr…

2014-04-01abs ↗pdf ↗

Bayes factors and relative belief ratios are compared as measures of statistical evidence.

problem Which measure of evidence is more appropriate: Bayes factors or relative belief ratios?
method Comparison of Bayes factors and relative belief ratios, considering properties and restrictions.
result Relative belief ratio has better properties as a measure of evidence.

The issue of giving an explicit description of the flow of information concerning the time of bankruptcy of a company (or a state) arriving on the market is tackled by defining a bridge process starting from zero and conditioned to be equal to zero when the default occurs. This enables to catch some empirical facts on …

2016-01-08abs ↗pdf ↗

In this paper we first give a one-move version of Markov's braid theorem for knot isotopy in S3S^3 that sharpens the classical theorem. Then a relative version of Markov's theorem concerning a fixed braided portion in the knot. We also prove an analogue of Markov's theorem for knot isotopy in knot complements. Finally …

2004-05-26abs ↗pdf ↗

Optimizes portfolio growth rate for a behavioral investor considering terminal relative growth rate.

problem Optimizing a behavioral investor's portfolio growth rate under relative growth criterion.
method Martingale method, concavification, and quantile optimization techniques.
result Derives closed-form optimal growth rate and finds significant impact of benchmark growth rate.

Paper proves existence and uniqueness of solutions to nonlocal systems, generalizing stochastic game theory.

problem Time inconsistency in stochastic differential games.
method Proves existence and uniqueness of solutions to nonlocal fully-nonlinear parabolic systems.
result Generalizes stochastic game theory to include time-inconsistent preferences.

Let \nabla be a linear connection on an 2n2n-dimensional almost anti-Hermitian manifold MM\ equipped with an almost complex structure JJ, a pseudo-Riemannian metric gg and the twin metric G=gJG=g\circ J. In this paper, we first introduce three types of conjugate connections of linear connections relative to gg, $G…

2019-11-12abs ↗pdf ↗

The paper introduces Relative Bias to quantify LLM bias systematically.

problem Quantifying bias in LLMs is challenging due to ambiguity and rapid model emergence.
method Relative Bias framework using Embedding Transformation and LLM-as-a-Judge methodologies.
result The two scoring methods show strong alignment, providing a systematic approach.

Model patching closes subgroup performance gaps in skin cancer classification.

problem Inconsistent model performance on specific subgroups of a class.
method Two-stage framework that models subgroup features and learns semantic transformations, followed by data augmentation.
result Reductions in robust error of up to 33% relative to best baseline on benchmark datasets.

The paper is concerned with regularity properties of boundaries of causal pasts of points in a 3+1-dimensional Einstein-vacuum spacetime. In a Lorentzian manifold such boundaries play crucial role in propagation of linear and nonlinear waves. We prove a uniform lower bound on the radius of injectivity of these null bou…

2006-03-01abs ↗pdf ↗