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.

168,742 papers · 148 categories

Trend · papers per month

5111621 · Mar 202619922001200920172026
48 results for Hedge Greeks

KrigHedge uses Gaussian processes to approximate option Greeks efficiently.

problem Computing option Greeks in complex models is computationally expensive or inexact.
method Gaussian process surrogates trained on noisy option prices, with analytical differentiation for sensitivities.
result The method provides accurate Delta approximations and quantifies hedging loss.

In this article, we investigate the behavior of long-term options. In many cases, option prices follow an exponential decay (or growth) rate for further maturity dates. We determine under what conditions option prices are characterized by this property. To see this, we use the martingale extraction method through which…

2014-10-29abs ↗pdf ↗

Fourier methods fail to accurately approximate option Greeks in realistic market conditions.

problem Failure of Fourier pricing techniques to approximate Greeks in realistic market parameters.
method Used Fourier techniques like Carr-Madan formula, COS method, and Lewis formula to approximate Greeks, which failed in some market conditions.
result Empirically showed that Fourier methods completely fail to approximate Greeks in realistic market environments.

Proposes a new framework for invariant quadratic P&L predictions in option books.

problem Inconsistent second-order P&L predictions across different factor parameterizations.
method Local, model-agnostic framework using covariant Hessian defined by an affine connection.
result Coordinate-invariant quadratic P&L predictions that match desk targets.

This paper is concerned with the asymptotics for Greeks of European-style options and the risk-neutral density function calculated under the constant elasticity of variance model. Formulae obtained help financial engineers to construct a perfect hedge with known behaviour and to price any options on financial assets.

2017-06-24abs ↗pdf ↗

We derive new formulas for the price of the European call and put options in the Black-Scholes model, under the form of uniformly convergent series generalizing previously known approximations. We also provide precise boundaries for the convergence speed and apply the results to the calculation of hedge parameters (Gre…

2018-09-17abs ↗pdf ↗

We consider option hedging in a model where the underlying follows an exponential Lévy process. We derive approximations to the variance-optimal and to some suboptimal strategies as well as to their mean squared hedging errors. The results are obtained by considering the Lévy model as a perturbation of the Black-Schole…

2013-09-30abs ↗pdf ↗

New method calibrates LV surfaces for exotic derivatives with smoother, more stable Greeks.

problem Challenges in LV calibration leading to spiky surfaces and unstable Greeks.
method Automatic local regression to pre-process market observables and smooth LV surfaces.
result Significantly smoother LV surfaces and greatly improved Greek stability with negligible additional cost.

Derivative-informed models improve financial surrogates for accurate hedging and risk management.

problem Developing fast surrogate models for financial derivatives and risk quantities.
method Derivative-informed operator learning framework combining neural operators, random features, and tangent sensitivity equations.
result The framework reduces hedging and risk errors by 40-76% compared to standard surrogates.

A machine learning method for short-maturity options with jumps and stochastic volatility.

problem Short-maturity options with jumps and stochastic volatility.
method Differential machine learning method combining supervision and PIDE-residual penalty.
result Improves jump-term approximation and reduces Greeks errors compared to baselines.

QMC and GSA improve option pricing and risk measures efficiency.

problem Efficiently pricing and hedging complex financial instruments.
method Application of QMC and GSA techniques for financial instrument pricing and hedging, comparing MC vs QMC and analyzing greeks computation.
result QMC outperforms MC in most cases, especially in high-dimensional simulations, leading to faster and more stable convergence.

Develops a machine-learning framework for optimal share repurchase hedging.

problem Challenges in hedging share repurchase programs due to market regulations and trading activity.
method Machine-learning framework that optimizes execution and hedging of share repurchase programs.
result Substantial performance improvements and an optimized hedging approach.

Efficient method for high-dimensional American option pricing and hedging.

problem High-dimensional American option pricing and hedging.
method Gradient-enhanced sparse Hermite polynomial expansions combined with least squares Monte Carlo.
result Outperforms state-of-the-art methods in high dimensions with comparable computational cost.

We propose a pricing technique based on coherent risk measures, which enables one to get finer price intervals than in the No Good Deals pricing. The main idea consists in splitting a liability into several parts and selling these parts to different agents. The technique is closely connected with the convolution of coh…

2006-05-02abs ↗pdf ↗

The paper develops methods to price and hedge options in path-dependent stock models.

problem Pricing and hedging options under complex stock models.
method Develops a path-dependent PDE for option pricing and differentiability of path-dependent SDE solutions.
result Provides formulas for option Greeks and differentiability of path-dependent SDE solutions.

This paper uses Malliavin calculus to price and compute delta of financial derivatives in jump-diffusion models.

problem Pricing and delta computation of financial derivatives in jump-diffusion models with stochastic intensity.
method Utilizes Malliavin calculus to price and compute delta, applying the Euler scheme for convergence analysis.
result Established the convergence of approximated solution, financial derivative, and its delta Greeks.

Paper assesses GMMB in VAs using FST for accurate net liability calculations.

problem Risk management of GMMB under stochastic mortality and regime-switching.
method Net liability model with FST algorithm for accurate numeric solutions.
result FST algorithm provides reliable results for net liability of GMMB.

FINN learns option pricing and hedging using financial theory.

problem Learning accurate option prices and sensitivities from financial theory.
method Self-supervised replication objective based on dynamic hedging.
result FINN accurately recovers classical Black--Scholes prices and performs robustly in stochastic volatility environments.

The computation of Greeks for exponential Lévy models are usually approached by Malliavin Calculus and other methods, as the Likelihood Ratio and the finite difference method. In this paper we obtain exact formulas for Greeks of European options based on the Lewis formula for the option value. Therefore, it is possible…

2014-07-04abs ↗pdf ↗

Researchers compute Greeks for rough Volterra SV models using Malliavin calculus.

problem Computing Greeks under rough Volterra stochastic volatility models.
method Malliavin calculus techniques, extending integration by parts to non-square integrable functionals.
result Formulas for computing Greeks (Delta, Gamma, Rho, Vega) under various rough Volterra SV models.

We investigate the pricing of cliquet options in a jump-diffusion model. The considered option is of monthly sum cap style while the underlying stock price model is driven by a drifted Lévy process entailing a Brownian diffusion component as well as compound Poisson jumps. We also derive representations for the density…

2018-10-23abs ↗pdf ↗

Matrix approximation method for Bachelier option pricing and Greeks under stochastic volatility models

problem Computing option prices and Greeks for stochastic volatility models
method Matrix approximation using elementary linear algebra
result Option prices and Greeks computed for infinitely many strikes with a finite number of expectations

The aim of the present article is to treat the Greek public debt issue strictly as a curve fitting problem. Thus, based on Eurostat data and using the Mathematica technical computing software, an exponential function that best fits the data is determined modelling how the Greek public debt expands with time. Exploring …

2012-12-07abs ↗pdf ↗

We consider the framework proposed by Burgard and Kjaer (2011) that derives the PDE which governs the price of an option including bilateral counterparty risk and funding. We extend this work by relaxing the assumption of absence of transaction costs in the hedging portfolio by proposing a cost proportional to the amou…

2018-02-13abs ↗pdf ↗

A new method computes Greeks for multi-asset options using tensor trains and Fourier transforms.

problem Efficient computation of Greeks for multi-asset options with high accuracy and low sample complexity.
method Tensor train (TT) representations of Fourier-based pricing functions, combined with numerical differentiation or analytical approaches.
result Significant speed-ups of up to 105imes10^{5} imes over Monte Carlo simulations while maintaining comparable accuracy.

Derives token price process for AMM tokens, finds leverage effect and pricing discrepancies.

problem Derives token price process for AMM tokens.
method Derives CEV process for token price, derives closed-form option prices, introduces liquidity-adjusted Greeks.
result Token price process is CEV, with leverage effect and pricing discrepancies.

Dupire's functional Itô calculus provides an alternative approach to the classical Malliavin calculus for the computation of sensitivities, also called Greeks, of path-dependent derivatives prices. In this paper, we introduce a measure of path-dependence of functionals within the functional Itô calculus framework. Name…

2013-11-15abs ↗pdf ↗

Greek POS Tagger and Entity Recognizer built using spaCy.

problem Developing a machine learning model for Greek language POS tagging and named entity recognition.
method Machine learning approach with spaCy platform, focusing on morphological features and token classification.
result The Greek spaCy platform improved performance in part-of-speech tagging and named entity recognition.

Effective dimensionality reduction improves accuracy and reduces costs in estimating option Greeks.

problem Estimating Greeks for barrier and arithmetic average Asian options.
method Global sensitivity analysis, Chebyshev interpolation, conditional pathwise method, randomized Quasi Monte Carlo, Brownian bridge discretization, importance sampling.
result Reduced effective dimensionality enhances convergence rate and accuracy of randomized Quasi Monte Carlo integration.

In the present work we propose an original analytical model of coopetitive game. We try to apply this analytical model of coopetition - based on game theory and conceived at a macro level - to the Greek crisis, suggesting feasible solutions in a cooperative perspective for the divergent interests which drive the econom…

2011-06-17abs ↗pdf ↗