Research
On-device research index

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.

168,695 papers · 148 categories

Trend · papers per month

3774111148 · Jun 202619922001200920172026
48 results for Price inequality

Study shows cryptocurrency price fluctuations become more similar to national currencies over time.

problem Understanding the volatility and inequality in cryptocurrency prices.
method Calculated inequality measures (Gini, Kolkata indices, QQ factor) for cryptocurrency and national currency price fluctuations over 10 years.
result Cryptocurrency price fluctuations become more similar to national currencies over time.

The space of call price functions has a natural noncommutative semigroup structure with an involution. A basic example is the Black--Scholes call price surface, from which an interesting inequality for Black--Scholes implied volatility is derived. The binary operation is compatible with the convex order, and therefore …

2017-01-14abs ↗pdf ↗

Paper introduces a new outer measure for continuous price paths with instant enforcement.

problem Defining a new outer measure for continuous price paths with instant enforcement.
method Introducing an outer measure on the space [0,+)imesΩ[0, +\infty) imes \Omega that assigns zero value to instantly blockable sets.
result Proves BDG inequalities and an Itô-type integral for the modified measure.

Microstructure of market dynamics is studied through analysis of tick price data. Linear trend is introduced as a tool for such analysis. Trend arbitrage inequality is developed and tested. The inequality sets limiting relationship between trend, bid-ask spread, market reaction and average update frequency of price inf…

2006-07-10abs ↗pdf ↗

Employee stock options (ESOs) are American-style call options that can be terminated early due to employment shock. This paper studies an ESO valuation framework that accounts for job termination risk and jumps in the company stock price. Under general Lévy stock price dynamics, we show that a higher job termination ri…

2015-04-30abs ↗pdf ↗

Proves Singer conjecture for graph manifolds with residually finite groups.

problem Proving the Singer conjecture for graph manifolds with specific properties.
method Used residual finiteness and graph manifold properties to prove the conjecture.
result Proved the Singer conjecture for extended graph manifolds and pure complex-hyperbolic higher graph manifolds.

We study Betti numbers of sequences of Riemannian manifolds which Benjamini-Schramm converge to their universal covers. Using the Price inequalities we developed elsewhere, we derive two distinct convergence results. First, under a negative Ricci curvature assumption and no assumption on sign of the sectional curvature…

2019-09-12abs ↗pdf ↗

ETCNN uses neural networks to price American options accurately.

problem Accurately pricing American options with inequality constraints.
method ETCNN framework solving BSM equations with exact terminal condition.
result ETCNN achieves high accuracy and robustness across various scenarios.

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 develops a novel numerical method for pricing American options in a two-asset jump-diffusion model.

problem Pricing American options under correlated two-asset jump-diffusion models using finite difference methods often fails to preserve monotonicity and accurately discretize jump integrals.
method Introduces a novel monotone integration scheme to solve 2-D Partial Integro-Differential Equations (PIDEs) efficiently and accurately.
result The proposed method ensures convergence to the viscosity solution of the variational inequality and is both \ell_{\infty}-stable and consistent.

Neural networks solve variational inequalities for optimal stopping problems.

problem Solving variational inequalities for optimal stopping problems in finance.
method Proposed neural network approach using loss functions directly incorporating variational inequality on whole domain.
result Existence and convergence of neural networks whose losses converge to zero.

We develop a class of pathwise inequalities of the form H(Bt)Mt+F(Lt)H(B_t)\ge M_t+F(L_t), where BtB_t is Brownian motion, LtL_t its local time at zero and MtM_t a local martingale. The concrete nature of the representation makes the inequality useful for a variety of applications. In this work, we use the inequalities to derive …

2007-02-07abs ↗pdf ↗

Study short-term behavior of up-and-in barrier options using Malliavin calculus.

problem Analyzing the decay rate of up-and-in barrier option prices as maturity decreases.
method Use Malliavin calculus to analyze the law of the supremum of the log-price process.
result Derive upper bound on asymptotic decay rate of up-and-in barrier option prices.

Study shows how algorithmic prediction affects US housing market, reducing racial wealth disparities.

problem Impact of algorithmic prediction on housing market and racial wealth disparities.
method Natural experiment using digitization of housing records to study entry, allocation, and prices.
result Digitization leads to increased sale prices for minority-owned homes, reducing racial wealth disparities.

New method estimates consumer surplus from randomized pricing data.

problem Estimating consumer surplus from observational data, especially in AI-driven pricing.
method Cumulative Propensity Weights (CPW) and Augmented CPW (ACPW) estimators.
result Validated methods for estimating consumer surplus from randomized pricing data.

Algorithm achieves optimal pricing with minimal exploration for dynamic markets.

problem Optimal pricing in dynamic markets with contextual information.
method Localized exploration-then-commit (LetC) algorithm with pure exploration, refinement, and exploitation stages.
result Achieves minimax optimal, dimension-free regret bound.

In this paper we introduce a class of information-based models for the pricing of fixed-income securities. We consider a set of continuous- time information processes that describe the flow of information about market factors in a monetary economy. The nominal pricing kernel is at any given time assumed to be given by …

2009-11-09abs ↗pdf ↗

We note a simple mechanism that may at least partially resolve several outstanding economic puzzles, including why the cyclically adjusted price to earnings ratio of the S&P 500 index has been oddly high for the past two decades, why gains to capital have outpaced gains to wages, and the persistence of the equity premi…

2016-10-25abs ↗pdf ↗

Develops a nonparametric model for arbitrage-free pricing of illiquid derivatives.

problem Modeling joint dynamics of liquid vanilla options for arbitrage-free pricing of illiquid derivatives.
method Derives a state space for prices respecting underlying financial constraints using neural networks and imposes constraints to preserve no-arbitrage conditions.
result Neural SDE models are guaranteed to satisfy a set of linear inequalities and validated with numerical experiments.

Study values American passport options in an exponential Lévy model.

problem Valuing an exotic derivative called the American passport option.
method Derived pricing equation using dynamic programming principle and proved viscosity solution.
result Option value is a viscosity solution of variational inequality and is convex.

Paper proposes a new dynamic pricing method with always-valid online statistical learning.

problem Designing dynamic pricing policies that adapt to online uncertainty and maintain validity.
method Regularized online statistical learning with theoretical guarantees and three major advantages.
result Proposed OORMLP pricing policy secures logarithmic regret in decision horizon.

This paper develops methods for pricing American Parisian options under general Markov models.

problem Pricing American Parisian options with various types and payoff functions.
method General approaches using CTMC approximation for time-inhomogeneous Markov models, including state augmentation and variational inequalities.
result Efficient algorithms for pricing American Parisian options confirmed with numerical experiments.

We consider model-free pricing of digital options, which pay out if the underlying asset has crossed both upper and lower barriers. We make only weak assumptions about the underlying process (typically continuity), but assume that the initial prices of call options with the same maturity and all strikes are known. Unde…

2008-08-29abs ↗pdf ↗

Study optimal stopping for diffusion processes with unknown primitives, applying RL and martingale methods.

problem Optimal stopping for diffusion processes with unknown model primitives.
method Continuous-time reinforcement learning framework, variational inequality formulation, stochastic optimal control, entropy regularizer, semi-analytical optimal Bernoulli distribution, policy improvement theorem, policy iterations.
result Demonstrated high accuracy in learning value functions and characterizing free boundaries for various optimal stopping problems.

Several authors have noticed the signature of log-periodic oscillations prior to large stock market crashes [cond-mat/9509033, cond-mat/9510036, Vandewalle et al 1998]. Unfortunately good fits of the corresponding equation to stock market prices are also observed in quiet times. To refine the method several approaches …

2002-04-13abs ↗pdf ↗

We study the problem of instance segmentation in biological images with crowded and compact cells. We formulate this task as an integer program where variables correspond to cells and constraints enforce that cells do not overlap. To solve this integer program, we propose a column generation formulation where the prici…

2017-09-21abs ↗pdf ↗

In this paper, we are concerned with the valuation of Guaranteed Annuity Options (GAOs) under the most generalised modelling framework where both interest and mortality rates are stochastic and correlated. Pricing these type of options in the correlated environment is a challenging task and no closed form solution exis…

2017-07-04abs ↗pdf ↗

In the present paper, we study the optimal execution problem under stochastic price recovery based on limit order book dynamics. We model price recovery after execution of a large order by accelerating the arrival of the refilling order, which is defined as a Cox process whose intensity increases by the degree of the m…

2015-02-16abs ↗pdf ↗

Develops a new method for pricing GMWBs with jumps and stochastic interest rates.

problem Pricing guaranteed minimum withdrawal benefits (GMWBs) with jumps and stochastic interest rates.
method Combines semi-Lagrangian method with Fourier pricing and Green's function.
result Mathematically demonstrates convergence to the viscosity solution of the HJB-QVI.

We develop a new market-making model, from the ground up, which is tailored towards high-frequency trading under a limit order book (LOB), based on the well-known classification of order types in market microstructure. Our flexible framework allows arbitrary order volume, price jump, and bid-ask spread distributions as…

2019-03-18abs ↗pdf ↗

The paper applies thermodynamics to financial markets to prove no-arbitrage constraints.

problem No arbitrage in financial markets under price impact.
method Stochastic thermodynamics applied to financial trading cycles.
result Proves any round-trip trading strategy yields non-positive expected profit.