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.
Method constructs CFMMs matching desired payoffs.
We study a non-parametric multi-armed bandit problem with stochastic covariates, where a key complexity driver is the smoothness of payoff functions with respect to covariates. Previous studies have focused on deriving minimax-optimal algorithms in cases where it is a priori known how smooth the payoff functions are. I…
Optimal payoff choice constrained by Bregman-Wasserstein divergence.
Paper shows how to replicate payoffs without oracles in CFMMs.
Agent optimizes perpetual contract liquidation with transaction costs and risk.
Quantum Monte Carlo speeds up option pricing for complex payoff functions.
Novel approach to financial derivatives pricing using rough path theory.
New method uses neural networks for better financial hedging.
The portfolio optimization problem is a basic problem of financial analysis. In the study, an optimization model for constructing an options portfolio with a certain payoff function has been proposed. The model is formulated as an integer linear programming problem and includes an objective payoff function and a system…
We derive a formula for liquidity providers' payoff on DEXs, linking it to volatility.
The paper bounds payoffs and option prices in discrete models.
This paper studies robust payoff allocation in submodular games, especially against replication.
In this paper we propose a new robust algorithm to find the optimal static replicating portfolios for general nonlinear payoff functions and give the estimate of the rate of convergence that is absent in the literature. We choose the static replication by minimizing the error bound between the nonlinear payoff function…
New method uses DistRL to estimate entire payoff distribution for financial derivatives.
We study the online saddle point problem, an online learning problem where at each iteration a pair of actions need to be chosen without knowledge of the current and future (convex-concave) payoff functions. The objective is to minimize the gap between the cumulative payoffs and the saddle point value of the aggregate …
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…
New acquisition function for extreme rewards in bandits.
Distributed strategic learning has been getting attention in recent years. As systems become distributed finding Nash equilibria in a distributed fashion is becoming more important for various applications. In this paper, we develop a distributed strategic learning framework for seeking Nash equilibria under stochastic…
The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions. Our main tool is to combine the one-step survival idea of Glasserman and Staum wi…
In this paper we consider Dynkin's games with payoffs which are functions of an underlying process. Assuming extended weak convergence of underlying processes to a limit process we prove convergence Dynkin's games values corresponding to to the Dynkin's game…
The paper examines bounds for stop-loss payoffs using transformed random variables.
A new Bayesian method optimizes time-dependent expensive functions with lookahead.
Optimal portfolio yields a digital option payoff.
Adaptive populations such as those in financial markets and distributed control can be modeled by the Minority Game. We consider how their dynamics depends on the agents' initial preferences of strategies, when the agents use linear or quadratic payoff functions to evaluate their strategies. We find that the fluctuatio…
Study finds cheapest possible payoff under ambiguity, linking to maxmin expected utility.
We introduce signature payoffs, a family of path-dependent derivatives that are given in terms of the signature of the price path of the underlying asset. We show that these derivatives are dense in the space of continuous payoffs, a result that is exploited to quickly price arbitrary continuous payoffs. This approach …
The aim of this article is to provide a systematic analysis of the conditions such that Fourier transform valuation formulas are valid in a general framework; i.e. when the option has an arbitrary payoff function and depends on the path of the asset price process. An interplay between the conditions on the payoff funct…
The paper uncovers the impact of price and payoff autocorrelations in multi-period asset pricing models.
This paper analyzes a time-dependent CFMM called RMM-01, focusing on its pricing and stability.
Neural nets replicate hedging payoffs for realistic discrete-time settings.
We present the quantum model of Bertrand duopoly and study the entanglement behavior on the profit functions of the firms. Using the concept of optimal response of each firm to the price of the opponent, we found only one Nash equilibirum point for maximally entangled initial state. The very presence of quantum entangl…
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…
New neural network approximates convex option prices.
Study best-response learning dynamics in zero-sum polymatrix games under full and minimal information settings.
Study path-dependent affine models under uncertain parameters for financial applications.
We analyze the relation between earning forecast accuracy and expected profitability of financial analysts. Modeling forecast errors with a multivariate Gaussian distribution, a complete characterization of the payoff of each analyst is provided. In particular, closed-form expressions for the probability density functi…
New method reduces errors in pricing and sensitivities for discontinuous payoffs.
This paper studies the payoff amounts in simple interest loans without arbitrage.
Paper uses deep learning to price and hedge options in incomplete markets.
Improved regret bounds for contextual combinatorial semi-bandits with linear payoffs.
We consider the impact of ambiguity on the optimal timing of a class of two-dimensional integral option contracts when the exercise payoff is a positively homogeneous measurable function. Hence, the considered class of exercise payoffs includes discontinuous functions as well. We identify a parameterized family of exce…
The extremely useful method of Malliavin calculus has not yet gained adequate popularity because of the complicated analytic apparatus of this method. The author attempts here to propose a simplified algebraic formalism similar to Malliavin calculus, but based on the notion of creation-annihilation operators instead of…
Adaptive Multilevel Splitting improves rare event pricing for financial derivatives.
Study optimal stopping times under regime-switching models with constraints.
Develops a new method for robust risk measurement by averaging nearby payoffs.
R2-B2 optimizes game interactions with recursive reasoning.
We study the optimal stopping problem of pricing an American Put option on a Zero Coupon Bond (ZCB) in the Musiela's parametrization of the Heath-Jarrow-Morton (HJM) model for forward interest rates. First we show regularity properties of the price function by probabilistic methods. Then we find an infinite dimensional…
Exponential Lévy processes have been used for modelling financial derivatives because of their ability to exhibit many empirical features of markets. Using their multidimensional analogue, a general analytic pricing formula is obtained, allowing for the direct valuation of multi-asset options on $n \in \z^+$ risky asse…