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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.

169,051 papers · 148 categories

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48 results for closeout payoffs
Robust XVAq-fin.PR

Framework for robust credit risk valuation adjustments.

problem Valuation of credit default swap portfolios with uncertain counterparty bond returns.
method Arbitrage-free framework, bounds derived from nonlinear ODEs, collateral and closeout payoffs considered.
result Upper and lower bounds for XVA process derived, showing nonlinear effects of credit contagion.

This paper addresses credit valuation adjustment with a new closeout convention.

problem Accurate estimation of financial claim value considering counterparty credit risk.
method Theoretical and computational analysis of a nonlinear valuation system using neural networks.
result A neural network-based algorithm effectively solves the high-dimensional nonlinear valuation system.

We compare two different bilateral counterparty valuation adjustment (BVA) formulas. The first formula is an approximation and is based on subtracting the two unilateral Credit Valuation Adjustment (CVA)'s formulas as seen from the two different parties in the transaction. This formula is only a simplified representati…

2011-06-17abs ↗pdf ↗

Study finds cheapest possible payoff under ambiguity, linking to maxmin expected utility.

problem Finding cost-efficient payoffs in uncertain market conditions.
method Developed a new concept of robust cost-efficient payoff and linked it to maxmin expected utility.
result Solutions to maxmin robust expected utility are robust cost-efficient.

The paper uncovers the impact of price and payoff autocorrelations in multi-period asset pricing models.

problem Hidden dependence of asset pricing models on price and payoff autocorrelations.
method Obtained approximations of the basic pricing equation describing various parameters.
result Valid results for other pricing models like ICAPM and APM.

Nonparametric pricing and hedging of exotic derivatives using signature payoffs.

problem Pricing and hedging exotic derivatives accurately and efficiently.
method Introducing signature payoffs and using them to approximate and price exotic derivatives nonparametrically.
result Signature payoffs enable accurate and computationally tractable pricing and hedging of exotic derivatives.

New findings show pure strategy equilibria are more robust in a war of attrition game.

problem Analyzing a game of war of attrition under complete information.
method Examined the stability of equilibria in pure and mixed strategies under varying payoffs.
result Pure strategy equilibria are more robust to perturbations of the canonical model.

New algorithms for stochastic linear bandits with heavy-tailed payoffs achieve nearly optimal regret.

problem Stochastic linear bandits with heavy-tailed payoffs.
method Median of means and dynamic truncation.
result Sublinear regret bound of O(d12T11+ε)O(d^{\frac{1}{2}}T^{\frac{1}{1+ε}}) for ε(0,1]ε\in(0,1].

We study the use of the multilevel Monte Carlo technique in the context of the calculation of Greeks. The pathwise sensitivity analysis differentiates the path evolution and reduces the payoff's smoothness. This leads to new challenges: the inapplicability of pathwise sensitivities to non-Lipschitz payoffs often makes …

2011-02-07abs ↗pdf ↗

Study of 2imes22 imes 2 zero-sum games with noisy observations and commitments.

problem Analyzing 2imes22 imes 2 zero-sum games with noisy observations and commitments.
method Modeling a 2imes22 imes 2 zero-sum game with a leader committing to a strategy and a follower observing a noisy version of the leader's action.
result Observing the leader's action is either beneficial or immaterial for the follower, and the equilibrium payoff is bounded.

This paper studies robust payoff allocation in submodular games, especially against replication.

problem Payoff allocation in submodular games, especially robustness against replication.
method Systematically studied replication manipulation in submodular games, introduced replication robustness metric, and validated with empirical ML data market.
result Conditions characterizing robustness of semivalues in submodular games.

Study on optimal information acquisition in Kyle model with entropy cost.

problem Optimal information acquisition in Kyle model with entropy cost.
method Continuous signals are optimal, and any signal with a logit posterior distribution yields the same ex-ante value.
result Posterior expected payoff becomes normally distributed as information acquisition cost increases.

We derive a formula for liquidity providers' payoff on DEXs, linking it to volatility.

problem Liquidity providers on DEXs are undercompensated for their service.
method We derive a payoff formula for liquidity providers on DEXs, assuming geometric Brownian price movements and zero arbitrage.
result The payoff from liquidity fees is a near-linear function of volatility.

In an online contract selection problem there is a seller which offers a set of contracts to sequentially arriving buyers whose types are drawn from an unknown distribution. If there exists a profitable contract for the buyer in the offered set, i.e., a contract with payoff higher than the payoff of not accepting any c…

2013-05-15abs ↗pdf ↗

The paper examines bounds for stop-loss payoffs using transformed random variables.

problem Bounding stop-loss payoffs for a difference of two random variables.
method Analyzes crossing points of cdfs of original and transformed random variables.
result Unique pairwise crossing points for mortality-linked securities under symmetric copulas.

Quantum Monte Carlo speeds up option pricing for complex payoff functions.

problem Efficiently pricing options with complex payoff functions using quantum computing.
method Developed a quantum Monte Carlo algorithm for multidimensional Black-Scholes PDEs.
result Proved polynomial computational complexity and speed-up over classical methods.

New method uses DistRL to estimate entire payoff distribution for financial derivatives.

problem Traditional methods focus on expected option value; this tackles risk-aware pricing.
method Reinterprets and proposes a framework using Distributional Reinforcement Learning (DistRL).
result Demonstrates enhanced risk-aware pricing and uncertainty quantification on Asian options.

We consider a sequential learning problem with Gaussian payoffs and side information: after selecting an action ii, the learner receives information about the payoff of every action jj in the form of Gaussian observations whose mean is the same as the mean payoff, but the variance depends on the pair (i,j)(i,j) (and may…

2015-10-27abs ↗pdf ↗

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.

In this work, we expand the idea of Samuelson[3] and Shepp[2,5,6] for stock optimization using the Bachelier model [4] as our models for the stock price at the money (X[stock price]= K[strike price]) for the American call and put options [1]. At the money (X= K) for American options, the expected payoff of both the cal…

2009-02-26abs ↗pdf ↗

Paper defines saddle points in asymmetric Dynkin games using martingale theory.

problem Tackles saddle point conditions in asymmetric Dynkin games with partial information.
method Uses martingale theory to identify super and submartingales related to equilibrium payoffs.
result Characterizes saddle point strategies in terms of equilibrium payoffs' dynamics and Doob-Meyer decompositions.

A new algorithm improves top-kk recommendation accuracy by considering item payoffs uncertainty.

problem Suboptimal performance in top-kk recommendation rankings due to varying item payoffs.
method Proposes a risk-seeking utility function for ranking items based on estimated preference scores.
result Risk-seeking ranking yields the best performance in top-kk recommendations.

The paper extends ERP framework to non-monotonic payoffs and short selling bans.

problem Valuation of contingent claims with short selling bans under ERP framework.
method Unified framework for ERP pricing, extending to non-monotonic payoffs, and comparing with Black-Scholes.
result Equal-risk prices differ from Black-Scholes prices under short selling bans.

This paper studies the payoff amounts in simple interest loans without arbitrage.

problem Understanding the payoff amounts in simple interest loans without arbitrage.
method Developed a formula for the payoff amount for simple interest loans, studied within a model of a loan market.
result The sequence of payoff amounts is increasing before a certain critical time and then decreasing.

A new method for calculating ES from VaR under Solvency II.

problem The need for a more appropriate risk measure (ES) than VaR.
method Developed PELVE method for multiple insurers, analyzing existence, uniqueness, and expressions for different payoff distributions.
result The choice of method is crucial when payoffs are from different distribution families.

In this article, we show how the scaling symmetry of the SABR model can be utilized to efficiently price European options. For special kinds of payoffs, the complexity of the problem is reduced by one dimension. For more generic payoffs, instead of solving the 1+2 dimensional SABR PDE, it is sufficient to solve NVN_V u…

2013-08-03abs ↗pdf ↗

In this paper we consider Dynkin's games with payoffs which are functions of an underlying process. Assuming extended weak convergence of underlying processes {S(n)}n=0\{S^{(n)}\}_{n=0}^{\infty} to a limit process SS we prove convergence Dynkin's games values corresponding to {S(n)}n=0\{S^{(n)}\}_{n=0}^{\infty} to the Dynkin's game…

2009-08-25abs ↗pdf ↗

New algorithms tackle heavy-tailed payoffs in linear stochastic bandits, matching lower bounds up to polylogarithmic factors.

problem Linear stochastic bandits with heavy-tailed payoffs.
method Median of means with well-designed allocation and truncation based on historical information.
result Regret upper bounds match the lower bound up to polylogarithmic factors.