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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.

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491317 · Mar 202619922001200920172026
48 results for martingale deflators

Paper investigates existence of deflators in financial markets.

problem Existence of equivalent local martingale deflators in semimartingale markets.
method Characterization of deflators using modified semimartingale characteristics.
result Existence of deflators can be characterized by modified semimartingale characteristics.

Let FG\mathbb{F}\subset \mathbb{G} be two filtrations and SS be a F\mathbb{F} semimartingale possessing a F\mathbb{F} local martingale deflator. Consider ττ a G\mathbb{G} stopping time. We study the problem whether SτS^{τ-} or SτS^τ can have G\mathbb{G} local martingale deflators. A suitable theoretical framework…

2014-05-18abs ↗pdf ↗

No arbitrage in financial markets with special semimartingales.

problem Proving the absence of arbitrage in non-numéraire financial markets.
method Proving the absence of arbitrage using a multiplicative special semimartingale deflator.
result The market is free of arbitrage if and only if there exists a multiplicative special semimartingale deflator.

A constrained informationally efficient market is defined to be one whose price process arises as the outcome of some equilibrium where agents face restrictions on trade. This paper investigates the case of short sale constraints, a setting which despite its simplicity, generates new insights. In particular, it is show…

2014-01-08abs ↗pdf ↗

Unified framework models multiple financial and insurance term structures.

problem Modeling multiple term structures in various markets.
method Extended Heath-Jarrow-Morton (HJM) approach under real-world probability.
result Characterization of local martingale deflators and existence of affine realizations.

The paper describes how martingales can be represented after a random time in financial models.

problem Representing martingales after a random event in financial markets.
method Explicit representation of G-local martingales in terms of F-local martingales and parameters of the random time.
result Comprehensive representation of G-local martingales, complementing previous work.

In the context of jump-diffusion market models we construct examples that satisfy the weaker no-arbitrage condition of NA1 (NUPBR), but not NFLVR. We show that in these examples the only candidate for the density process of an equivalent local martingale measure is a supermartingale that is not a martingale, not even a…

2015-11-26abs ↗pdf ↗

In a semimartingale financial market model, it is shown that there is equivalence between absence of arbitrage of the first kind (a weak viability condition) and the existence of a strictly positive process that acts as a local martingale deflator on nonnegative wealth processes.

2009-04-11abs ↗pdf ↗

Our goal is to resolve a problem proposed by Fernholz and Karatzas [On optimal arbitrage (2008) Columbia Univ.]: to characterize the minimum amount of initial capital with which an investor can beat the market portfolio with a certain probability, as a function of the market configuration and time to maturity. We show …

2010-06-13abs ↗pdf ↗

We consider a financial market model with a single risky asset whose price process evolves according to a general jump-diffusion with locally bounded coefficients and where market participants have only access to a partial information flow. For any utility function, we prove that the partial information financial marke…

2013-02-18abs ↗pdf ↗

A financial market model where agents trade using realistic combinations of buy-and-hold strategies is considered. Minimal assumptions are made on the discounted asset-price process - in particular, the semimartingale property is not assumed. Via a natural market viability assumption, namely, absence of arbitrages of t…

2008-03-13abs ↗pdf ↗

Extends utility maximization theory for infinite horizons without strong no-arbitrage assumptions.

problem Maximizing lifetime utility from wealth over an infinite horizon.
method Develops a duality theory using deflators and supermartingale properties, extending previous work.
result Establishes a strong duality theorem for infinite horizon utility maximization under minimal no-arbitrage assumptions.

This paper addresses the question of how an arbitrage-free semimartingale model is affected when stopped at a random horizon. We focus on No-Unbounded-Profit-with-Bounded-Risk (called NUPBR hereafter) concept, which is also known in the literature as the first kind of non-arbitrage. For this non-arbitrage notion, we ob…

2013-10-04abs ↗pdf ↗

In the context of a general continuous financial market model, we study whether the additional information associated with an honest time gives rise to arbitrage profits. By relying on the theory of progressive enlargement of filtrations, we explicitly show that no kind of arbitrage profit can ever be realised strictly…

2012-07-07abs ↗pdf ↗

The paper analyzes deflation for estimating a low-rank spike in large tensors with noise.

problem Estimating a low-rank symmetric spike in large tensors with additive Gaussian noise.
method Characterization of deflation performance in terms of vector alignments and weights.
result Understanding deflation mechanism in noisy conditions and designing more efficient methods.

In Karatzas and Kardaras's paper on semimartingale financial models, it is proved that the NUPBR condition is a property of the local characteristic of the asset process alone. In Takaoka's paper on NUPBR, it is proved that the NUPBR condition is equivalent to the existence of a simga-martingale deflator. However, Taka…

2013-06-05abs ↗pdf ↗

Paper optimizes tensor deflation for non-orthogonal signals.

problem Recovering low-rank signals from noisy tensors with correlated components.
method Developed an asymptotic analysis and optimized deflation procedure using random tensor theory.
result Proposed an efficient tensor deflation algorithm that optimizes a parameter introduced in the deflation mechanism.

The paper shows how gradient flow on over-parametrized tensor decomposition behaves like deflation.

problem Understanding the training dynamics of gradient flow on tensor decomposition.
method Empirical observation and mathematical proof of gradient flow dynamics for orthogonally decomposable tensors.
result Gradient flow dynamics for orthogonally decomposable tensors follows a tensor deflation process, recovering all tensor components.

Study analyzes Hotelling-type tensor deflation for spiked tensors, providing insights into signal and noise.

problem Characterizing singular values and alignments in Hotelling-type tensor deflation.
method Asymptotic study of Hotelling-type tensor deflation in large dimensional regime using random tensor theory.
result Characterization of singular values and alignments at each step of the deflation procedure.

The paper studies optimal maps between hyperbolic surfaces, focusing on their rigidity and obstructions.

problem Finding optimal Lipschitz maps between hyperbolic surfaces and understanding their rigidity and obstructions.
method Introducing deflations, optimal maps to trees that obstruct optimal maps between surfaces, and using a smooth orthogeodesic foliation.
result Deflations are the main obstructions to optimal maps between hyperbolic surfaces, and they are essentially the only ones.

Corrects an earlier theorem, establishing new facts about information structures and non-anticipative aggregation.

problem The nature of information structures and their impact on non-anticipative aggregation.
method Local reduction of pricing to the natural price filtration, stability properties, and the establishment of new facts.
result Non-anticipative signals can reveal future information, requiring dependence among signals (masking relation) and not independence.

DFSOS improves sparse discriminant analysis for high-dimensional data.

problem Sparse discriminant analysis in high-dimensional settings with feature selection.
method Deflation-Free Sparse Optimal Scoring (DFSOS) using Bregman iteration and orthogonality-constrained optimization.
result DFSOS achieves comparable or better classification accuracy than deflation-based methods.

Study analyzes accuracy of tensor deflation in noisy conditions.

problem Analyzing accuracy of tensor deflation in noisy conditions.
method Asymptotic study of Hotelling-type tensor deflation in large tensor dimensions.
result Characterization of estimated singular values and singular vector alignments.

We undertake a study of markets from the perspective of a financial agent with limited access to information. The set of wealth processes available to the agent is structured with reasonable economic properties, instead of the usual practice of taking it to consist of stochastic integrals against a semimartingale integ…

2009-04-19abs ↗pdf ↗

We introduce polynomial processes in the sense of [8] in the context of stochastic portfolio theory to model simultaneously companies' market capitalizations and the corresponding market weights. These models substantially extend volatility stabilized market models considered by Robert Fernholz and Ioannis Karatzas in …

2017-05-10abs ↗pdf ↗

In this paper we study arbitrage theory of financial markets in the absence of a numéraire both in discrete and continuous time. In our main results, we provide a generalization of the classical equivalence between no unbounded profits with bounded risk (NUPBR) and the existence of a supermartingale deflator. To obtain…

2020-01-16abs ↗pdf ↗

Bayesian method improves dictionary learning for complex problems.

problem Efficiently identifying relevant dictionary entries for complex inverse problems.
method Bayesian group sparsity coding and deflation steps to compress and identify relevant subdictionaries.
result Significant computational complexity reduction and improved glitch detection in LIGO experiment.

The paper provides a new uniform tail bound for empirical processes.

problem Developing a uniform tail bound for empirical processes indexed by a class of functions.
method Introducing a deflation step to the standard generic chaining argument, and using a natural seminorm based on Cramér functions.
result Established a new uniform tail bound for empirical processes.

A new method inflates and deflates data manifolds to estimate densities without losing universality.

problem Density estimation on low-dimensional manifolds with non-Euclidean support.
method Inflation-deflation approach using Normalizing Flows with added noise.
result Exact estimation of densities on manifolds with sufficient conditions and Gaussian noise approximation.