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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.

169,051 papers · 148 categories

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2.7%5.4%8.0%10.7% · Oct 199919922001200920182026
48 results for Fair price

Doubly fair dynamic pricing ensures equal prices for different groups over time.

problem Achieving equal prices for different groups in online dynamic pricing.
method Online learning algorithm that balances procedural and substantive fairness.
result Achieves ildeO(T) ilde{O}(\sqrt{T}) regret, zero procedural unfairness, and ildeO(T) ilde{O}(\sqrt{T}) substantive unfairness.

This paper addresses dynamic price discrimination with fairness constraints.

problem Dynamic price discrimination with fairness constraints in online retailing.
method Nonparametric demand models, dynamic pricing policy, regret minimization.
result Optimal dynamic pricing policy with ildeO(T4/5) ilde{O}(T^{4/5}) regret for price fairness.

We develop a theory which applies to any market dynamics that satisfy a fair market assumption on the nullity of the average profit of simple market making strategies. We show that for any such fair market, there exists a martingale fair price which corresponds to the average liquidation value (at the ask or the bid) o…

2015-06-08abs ↗pdf ↗

The paper addresses fairness in dynamic pricing for strategic buyers.

problem Price disparities among specific groups can lead to unfair perceptions and legal violations.
method Proposes a dynamic pricing policy that achieves fairness and discourages strategic behavior.
result Achieves an upper bound of O(T+H(T))O(\sqrt{T}+H(T)) regret over TT time horizons, reducing regret by 35.06% compared to a benchmark policy.

The paper examines fair pricing and hedging stability under small numéraire perturbations.

problem Fair pricing and hedging stability under numéraire perturbations.
method Reformulating the stochastic control problem to show stability and deriving asymptotic formulas.
result Fair price and hedging strategy are stable with small numéraire perturbations.

The paper studies fairness in multi-stage selection problems and introduces a method to compute fair selections.

problem Fairness in multi-stage selection problems with additional features at each stage.
method Introducing fairness notions, proposing a linear program for fair selections, and defining the price of local fairness.
result It is possible to have a selection that has a small price of local fairness and is close to locally fair.

Unfair pricing policies have been shown to be one of the most negative perceptions customers can have concerning pricing, and may result in long-term losses for a company. Despite the fact that dynamic pricing models help companies maximize revenue, fairness and equality should be taken into account in order to avoid u…

2018-03-27abs ↗pdf ↗

A novel multi-objective optimization framework improves insurance pricing fairness.

problem Exacerbated trade-offs between competing fairness criteria in insurance pricing using machine learning.
method Proposes a novel multi-objective optimization framework using NSGA-II to jointly optimize accuracy and fairness criteria.
result Consistently achieves a balanced compromise between accuracy and fairness, outperforming single-model approaches.

The paper explores fairness, welfare, and equity in personalized pricing across various applications.

problem Interplay of fairness, welfare, and equity in personalized pricing based on customer features.
method Comprehensive literature review and observational metrics without underlying valuation distribution assumptions.
result Personalized pricing can expand access, improve welfare, and increase revenue or budget utilization.

Study provides error estimates for approximating game options with diffusion asset prices.

problem Approximating fair prices of game options with diffusion asset prices.
method Error estimates for discrete approximations of diffusion processes, applied to game options.
result Effective tool for computing fair prices of game options in multi-asset markets.

The QLBS model is enhanced with a large trader's impact, leading to optimal hedging strategies.

problem Finding an optimal hedging strategy with low transaction costs and fair price convergence.
method Extending the QLBS model, defining a hypothetical limit order book, and using batch-mode reinforcement learning.
result Optimal hedging strategy with lower transaction costs and fair price convergence.

A concept of martingale-fair index of return, consistent with Arbitrage Free Pricing Theory, is introduced. An explicit formula for the average rate of return of a group of investment/pension funds in a discrete time stochastic model is derived and several properties of this index are shown. In particular, it is proven…

2015-01-15abs ↗pdf ↗

Paper develops methods for fair insurance pricing without direct access to sensitive attributes.

problem Fairness in insurance pricing with restricted access to sensitive attributes.
method Develops statistical methods for estimating discrimination-free premiums using privatized sensitive attributes.
result The proposed methods enable fair insurance pricing while respecting privacy and regulatory constraints.

We introduce a flexible family of fairness regularizers for (linear and logistic) regression problems. These regularizers all enjoy convexity, permitting fast optimization, and they span the rang from notions of group fairness to strong individual fairness. By varying the weight on the fairness regularizer, we can comp…

2017-06-07abs ↗pdf ↗

Bielecki and Rutkowski (2014) introduced and studied a generic nonlinear market model, which includes several risky assets, multiple funding accounts and margin accounts. In this paper, we examine the pricing and hedging of contract both from the perspective of the hedger and the counterparty with arbitrary initial end…

2014-10-02abs ↗pdf ↗

This paper deals with applications of coherent risk measures to pricing in incomplete markets. Namely, we study the No Good Deals pricing technique based on coherent risk. Two forms of this technique are presented: one defines a good deal as a trade with negative risk; the other one defines a good deal as a trade with …

2006-05-02abs ↗pdf ↗

Our goal here is to discuss the pricing problem of European and American options in discrete time using elementary calculus so as to be an easy reference for first year undergraduate students. Using the binomial model we compute the fair price of European and American options. We explain the notion of Arbitrage and the…

2015-10-20abs ↗pdf ↗

New rule-based method for classification with scalability, interpretability, and fairness.

problem Developing a scalable and fair classification method.
method Column generation for linear programming, decision tree-based heuristic, and rule-based optimization.
result The method returns interpretable rules with optimal weights and addresses fairness constraints.

Modeling insider trading with transaction costs and fair pricing.

problem Maximizing profits for an informed trader in a market with transaction costs and fair pricing.
method Single auction model and continuous time analogue, analyzing equilibrium behavior with polynomial and differential equations.
result Equilibrium trading strategy and pricing rules are affected by transaction costs, revealing an information gap.

The paper introduces a new price model based on entropy that better fits high-frequency market data.

problem Understanding fair prices in high-frequency markets with bid-ask imbalance.
method A parametrized family of prices derived from the Maximum Entropy Principle, minimizing bias given volume imbalance.
result The model can generate higher kurtosis and heavy-tailed distributions compared to standard models.

Study aims to measure and mitigate biases in motor insurance pricing.

problem Ethical biases in motor insurance pricing that affect fairness and regulatory compliance.
method Statistical methodologies and data analysis to measure and mitigate biases.
result Developed tools to measure and mitigate ethical biases in motor insurance pricing.

A framework for fair derivative contract pricing and risk-sharing between parties with funding differences.

problem Price asymmetry due to funding differences in bilateral contracts.
method Defines a negotiation problem that maximizes the sum of utilities for two parties, deriving optimal prices and collateral.
result Optimal negotiation price and collateral can be used to interpret margin requirements.

We investigate the relation between the fair price for European-style vanilla options and the distribution of short-term returns on the underlying asset ignoring transaction and other costs. We compute the risk-neutral probability density conditional on the total variance of the asset's returns when the option expires.…

2002-10-06abs ↗pdf ↗

This paper optimizes revenue and resource balance in network revenue management.

problem Maximizing revenue while ensuring fair resource consumption across different suppliers.
method Introduces a regularized revenue objective and a primal-dual UCB algorithm for continuous prices and balancing.
result Achieves a worst-case regret of O~(N5/2T)\widetilde O(N^{5/2}\sqrt{T}) for revenue maximization and balancing.

In general it is not clear which kind of information is supposed to be used for calculating the fair value of a contingent claim. Even if the information is specified, it is not guaranteed that the fair value is uniquely determined by the given information. A further problem is that asset prices are typically expressed…

2013-04-13abs ↗pdf ↗

The paper studies martingales and super-martingales under a convex set of measures.

problem Understanding martingales and super-martingales in a convex set of equivalent measures.
method Introduced local regular super-martingales and proved necessary and sufficient conditions for their regularity.
result Generalized Doob's decomposition theorem for super-martingales under a convex set of measures.

This paper tackles fair online decision-making in contextual bandits, achieving optimal performance and fairness.

problem Fairness in online decision-making systems under strategic manipulation.
method Develops algorithms for linear and smooth reward functions, maintaining fairness and optimal regret.
result Achieves nearly minimax-optimal regret with strong fairness guarantees, even in the presence of attacks.

This paper optimizes crypto portfolios and valuates crypto options.

problem High volatility and lack of standard pricing models for crypto assets.
method Optimization techniques to minimize tail risk, dynamic pricing model for crypto assets, Esscher transform for fair valuation.
result Optimized crypto portfolios outperform major stock indices.

This article presents FVA and CVA of a bilateral derivative in a coherent manner, based on recent developments in fair value accounting and ISDA standards. We argue that a derivative liability, after primary risk factors being hedged, resembles in economics an issued variable funding note, and should be priced at the m…

2015-10-25abs ↗pdf ↗

We study the fair strike of a discrete variance swap for a general time-homogeneous stochastic volatility model. In the special cases of Heston, Hull-White and Schobel-Zhu stochastic volatility models we give simple explicit expressions (improving Broadie and Jain (2008a) in the case of the Heston model). We give condi…

2013-05-30abs ↗pdf ↗

The paper explores the tradeoff between fairness and accuracy in regression models.

problem Characterizing the tradeoff between fairness and accuracy in regression models.
method Provided a lower bound on the error of any fair regressor and extended the result to joint error using Wasserstein distance.
result Lower bounds on the error of fair regressors and their connection to Wasserstein distance.