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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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2457 · Jun 202619922001200920172026
48 results for no-arbitrage

In a discrete time and multiple-priors setting, we propose a new characterisation of the condition of quasi-sure no-arbitrage which has become a standard assumption. This characterisation shows that it is indeed a well-chosen condition being equivalent to several previously used alternative notions of no-arbitrage and …

2019-04-18abs ↗pdf ↗

Paper develops a continuous-time framework for financial markets without stochastic calculus.

problem Developing continuous-time financial models without stochastic calculus.
method A general framework using conditional topologies and pseudo-distance topologies.
result No-arbitrage conditions hold in continuous time if and only if they hold in discrete time.

Abstract framework for no-arbitrage concepts in topological vector lattices.

problem Generalization of no-arbitrage concepts in topological vector lattices.
method Imposing a structural condition on trading strategies and deriving abstract FTAP.
result NUPBR, NAA1_1, and NA1_1 may not be equivalent in general setting.

The paper sets criteria for no arbitrage in complex financial models.

problem Determining conditions for the absence of arbitrage in financial markets.
method Established deterministic conditions for no arbitrage, NUPBR, and NFLVR in diffusion market models.
result Provided criteria in terms of scale function and speed measure.

Deep learning models reconstruct volatility surfaces from noisy data under no-arbitrage constraints.

problem Reconstructing implied volatility surfaces from sparse and noisy option quotes.
method Compared multiple neural architectures including Transformers, U-Nets, and variational autoencoders.
result Transformer and U-Net architectures achieve strong reconstruction accuracy, especially under sparse observation regimes.

We study the stability of several no-arbitrage conditions with respect to absolutely continuous, but not necessarily equivalent, changes of measure. We first consider models based on continuous semimartingales and show that no-arbitrage conditions weaker than NA and NFLVR are always stable. Then, in the context of gene…

2013-12-16abs ↗pdf ↗

The present paper deals with the characterization of no-arbitrage properties of a continuous semimartingale. The first main result, Theorem \refMainTheoremCharNA, extends the no-arbitrage criterion by Levental and Skorohod [Ann. Appl. Probab. 5 (1995) 906-925] from diffusion processes to arbitrary continuous semimartin…

2005-03-23abs ↗pdf ↗

We generalize Merton's asset valuation approach to systems of multiple financial firms where cross-ownership of equities and liabilities is present. The liabilities, which may include debts and derivatives, can be of differing seniority. We derive equations for the prices of equities and recovery claims under no-arbitr…

2010-05-05abs ↗pdf ↗

Study analyzes bond price covariation robustly under no-arbitrage conditions.

problem Identifying the number of statistically relevant factors in the bond market.
method Nonparametric analysis of realized covariations in a general no-arbitrage setting.
result A high number of factors is needed to describe term structure evolution and term structure of volatility varies over time.

No-arbitrage constraints on implied variance slope are weak, leading to almost guaranteed arbitrage in many cases.

problem Weak constraints on implied variance slope in the Black-Scholes model lead to arbitrage opportunities.
method Analysis of constraints on implied variance slope and their implications for arbitrage.
result Arbitrage is almost always guaranteed in a wide range of slope values where constraints are enforced.

Strict local martingales may admit arbitrage opportunities with respect to the class of simple trading strategies. (Since there is no possibility of using doubling strategies in this framework, the losses are not assumed to be bounded from below.) We show that for a class of non-negative strict local martingales, the s…

2008-01-26abs ↗pdf ↗

Develops a deep learning method for enforcing no-arbitrage in local volatility surfaces.

problem No-arbitrage conditions not enforced in deep learning approaches for local volatility.
method Jointly interpolates European vanilla option prices, enforcing no-arbitrage through modified loss functions or network architectures.
result Demonstrates the effectiveness of enforcing no-arbitrage in local volatility surfaces using deep learning.

Study no-arbitrage conditions in 1D diffusion markets with interest rates.

problem Determining no-arbitrage conditions in 1D diffusion markets with interest rates.
method Established deterministic criteria for no-arbitrage notions in terms of scale function and speed measure.
result Revealed various effects, e.g., NIP not excluded by reflecting boundaries.

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.

Market impact is the link between the volume of a (large) order and the price move during and after the execution of this order. We show that under no-arbitrage assumption, the market impact function can only be of power-law type. Furthermore, we prove that this implies that the macroscopic price is diffusive with roug…

2018-05-18abs ↗pdf ↗

Generative adversarial networks enforce no-arbitrage in volatility surface computation.

problem Efficiently compute volatility surfaces without arbitrage violations.
method Generative adversarial network (GAN) with no-arbitrage constraints.
result Proposed GAN model outperforms ANN approaches in accuracy and computational time.

The study examines a financial model with sticky prices and finds no arbitrage when interest rate is zero.

problem Analyzing financial markets with sticky asset prices and proving no arbitrage conditions.
method Introduced a financial market model with a risky asset following a sticky geometric Brownian motion and a riskless asset with a constant interest rate. Proved no arbitrage conditions and derived pricing equations.
result No arbitrage conditions are met only when the interest rate is zero, and all replicable payoffs are derived under this condition.

Develops a method to predict stock returns with time-varying risk premia.

problem Predicting stock returns with time-varying risk premia while maintaining no-arbitrage restrictions.
method Penalized two-pass regression with time-varying factor loadings, incorporating penalization in the first pass and grouping in the second pass.
result The proposed method reduces prediction errors compared to other approaches.

Develops a framework for consistent pricing of interest rate derivatives.

problem Consistent pricing of bivariate interest rate exotics across interconnected markets.
method Schrödinger optimal transport problem with constraints.
result Demonstrates practical applicability and no-arbitrage bounds computation.

Markets composed of stocks with capitalization processes represented by positive continuous semimartingales are studied under the condition that the market excess growth rate is bounded away from zero. The following examples of these markets are given: i) a market with a singular covariance matrix and instantaneous rel…

2015-12-08abs ↗pdf ↗

In commodity markets the convergence of futures towards spot prices, at the expiration of the contract, is usually justified by no-arbitrage arguments. In this article, we propose an alternative approach that relies on the expected profit maximization problem of an agent, producing and storing a commodity while trading…

2015-01-01abs ↗pdf ↗

For several decades, the no-arbitrage (NA) condition and the martingale measures have played a major role in the financial asset's pricing theory. We propose a new approach for estimating the super-replication cost based on convex duality instead of martingale measures duality: Our prices will be expressed using Fenche…

2018-07-12abs ↗pdf ↗

DCNN improves volatility smile and skewness calibration without arbitrage constraints.

problem Calibrating volatility smile and skewness surfaces with no arbitrage constraints.
method Derivative-Constrained Neural Network (DCNN) incorporating derivatives in the loss function.
result DCNN generates a smooth surface that satisfies no-arbitrage conditions.

Novel approach to financial derivatives pricing using rough path theory.

problem No-arbitrage conditions in financial markets necessitating precise integration methods.
method Developed a polynomial-based approximation class for rough path functionals, extending to non-geometric rough paths.
result Motivated a hypothesis for payoff functionals in financial markets, facilitating analysis.