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.

168,657 papers · 148 categories

Trend · papers per month

10213141 · May 202619922001200920172026
48 results for path-dependent options

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.

Deep signature algorithm for pricing path-dependent options.

problem Pricing path-dependent options with complex payoff functions.
method Extended backward scheme for state-dependent FBSDEs with reflections, incorporating signature layer for path-dependent FBSDEs.
result Convergence analysis of the algorithm with explicit dependence on truncation order and neural network approximation errors.

Path-dependent PDEs model VIX and Realised Variance options.

problem Modeling volatility derivatives with path-dependence.
method Continuous stochastic volatility model with Gaussian Volterra process, proving well-posedness of PDEs.
result Formulae for greeks and implied volatility provided, finite-dimensional pricing PDEs obtained in Markovian models.

LOV model calibrates European and American options with path-dependent volatility.

problem Calibrating European and American options with path-dependent volatility.
method Designing a local volatility model that incorporates path-dependent shocks through an occupation sensitivity function.
result LOV model successfully calibrates options chains with automatic European vanilla option calibration and path-dependent flexibility.

Paper proposes method for generating paths of stochastic volatility CGMY process for option pricing.

problem Generating accurate sample paths for stochastic volatility models for option pricing.
method Monte-Carlo method for European and American options, least square regression for calibration.
result Calibrated model parameters to S\&P 100 index options market using path-dependent options.

In this paper, we give a numerical method for pricing long maturity, path dependent options by using the Markov property for each underlying asset. This enables us to approximate a path dependent option by using some kinds of plain vanillas. We give some examples whose underlying assets behave as some popular Levy proc…

2009-11-30abs ↗pdf ↗

Paper introduces a new volatility model for natural gas markets and discusses swing option pricing.

problem Modeling price and storage dynamics in natural gas markets with path-dependent volatility.
method Developed a novel stochastic path-dependent volatility model and used deep learning for swing option pricing.
result Proposed a deep learning method for numerical approximations of swing option pricing.

The paper compares machine learning methods with traditional techniques for pricing and sensitivities of financial products with path-dependent structures.

problem Evaluating financial products with early-termination clauses, especially those with path-dependent structures.
method The paper compares regression methods including randomized recurrent and feed-forward neural networks, and a novel approach using signatures of the underlying price process, with traditional polynomial basis functions for pricing and sensitivities.
result Machine learning algorithms often match the accuracy and efficiency of traditional methods for Asian and look-back options, while randomized neural networks are best for callable certificates.

Novel signature approach for pricing and hedging path-dependent options with market frictions.

problem Pricing and hedging path-dependent options with market frictions.
method Signature approach, mean-quadratic variation criterion, non-standard infinite-dimensional Riccati equations, time-augmented signature, non-Markovian stochastic control problem.
result Effective hedging strategies in frictional markets with low-truncated signature approximations.

The use of sequential Monte Carlo within simulation for path-dependent option pricing is proposed and evaluated. Recently, it was shown that explicit solutions and importance sampling are valuable for efficient simulation of spot price and volatility, especially for purposes of path-dependent option pricing. The result…

2019-06-29abs ↗pdf ↗

Extends Itô's formula for path-dependent functions in finance.

problem Modeling and hedging of path-dependent financial options.
method Functional extension of Itô's formula for C^{0,1}-functions of continuous weak Dirichlet processes.
result Validates the hedging or superhedging problems for path-dependent options.

Model-free approach to hedge path-dependent options using min-max optimization.

problem Hedging path-dependent options with maturity T using a static portfolio of vanilla options.
method Model-free approach based on primal-dual Martingale Optimal Transport (MOT) problem, solving a min-max optimization problem.
result Provides theoretical bounds on hedging error at maturity T.

In this paper I develop a new computational method for pricing path dependent options. Using the path integral representation of the option price, I show that in general it is possible to perform analytically a partial averaging over the underlying risk-neutral diffusion process. This result greatly eases the computati…

2000-05-19abs ↗pdf ↗

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.

The paper calculates option prices using Mellin transform for stochastic volatility models.

problem Calculating prices for path-dependent options under stochastic volatility.
method Asymptotic approach and Mellin transform for deriving closed-form formulas.
result Derives closed-form formulas for option prices with first-order approximation.

Study path-dependent affine models under uncertain parameters for financial applications.

problem Valuation of path-dependent financial derivatives under parameter uncertainty.
method Developed path-dependent setting for value function, established dynamic programming principle, approximated functional derivatives with neural networks.
result Efficient numerical methods for valuation of complex financial derivatives under parameter uncertainty.

In this paper we introduce a new approach to model-free path-dependent option pricing. We first introduce a general duality result for linear optimisation problems over signed measures introduced in [3] and show how the the problem of model-free option pricing can be formulated in the new framework. We then introduce a…

2015-01-15abs ↗pdf ↗

A fast Monte Carlo method for additive processes and option pricing.

problem Efficiently pricing path-dependent options with additive processes.
method Developed a fast Monte Carlo scheme for additive processes, analyzing and reducing numerical error sources.
result Shows significant reduction in error (1 bp or below) for pricing path-dependent options.

A new model for S&P 500 and VIX options pricing and calibration.

problem Calibrating and pricing S&P 500 and VIX options with a 4-factor path-dependent volatility model.
method Pathwise neural network approximation of VIX, leveraging Markovianity of the 4-factor model.
result The model accurately fits S&P 500 implied volatilities and reproduces VIX option smiles.

Paper presents a novel nonparametric method to price Asian options.

problem Difficulty in pricing Asian options, especially with arithmetic average price.
method Nonparametric Predictive Inference (NPI) for Asian option pricing.
result NPI method provides a more precise and uncertain prediction of future asset prices.

Study finds rough volatility models underperform in SPX option pricing.

problem Inconsistency of rough volatility models with SPX option prices.
method Empirical study using SPX options data, comparing rough and Markovian models.
result Rough volatility models with H(0,1/2)H \in (0,1/2) are inconsistent with SPX smiles, especially at short maturities.

Quantum computing for option pricing using MPS states.

problem Efficiently generating time series for path-dependent options on quantum computers.
method Proposes a Matrix Product State (MPS) model for time series generation and trains it for the Heston model.
result Demonstrates the MPS model's capability to generate paths in the Heston model for path-dependent option pricing.

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 …

2018-09-25abs ↗pdf ↗

Efficient hybrid method for pricing barrier options with stochastic volatility.

problem Valuation of barrier options on assets with stochastic volatility.
method Combining Monte Carlo simulation and semi-analytical heat potential method.
result Our method provides better accuracy and is orders of magnitude faster than existing methods.

We justify and give error estimates for binomial approximations of game (Israeli) options in the Black--Scholes market with Lipschitz continuous path dependent payoffs which are new also for usual American style options. We show also that rational (optimal) exercise times and hedging self-financing portfolios of binomi…

2006-07-05abs ↗pdf ↗

New method optimizes share buyback contracts without optimal control's limitations.

problem High-dimensional state spaces and risk penalty selection issues in traditional methods.
method Applies optimized heuristic strategies and classical pricing methods.
result Maximizes contract value and disentangles repurchase from hedging.

A new Bachelier model explains oil option volatility during the pandemic.

problem Describing and predicting the volatility surface of oil options during the pandemic.
method Additive Bachelier model with three parameters: volatility term structure, vol-of-vol, and skew.
result The model accurately describes the volatility surface and supports efficient pricing of exotic options.

In the framework of Black-Scholes-Merton model of financial derivatives, a path integral approach to option pricing is presented. A general formula to price European path dependent options on multidimensional assets is obtained and implemented by means of various flexible and efficient algorithms. As an example, we det…

2004-07-13abs ↗pdf ↗

We derive explicit valuation formulae for an exotic path-dependent interest rate derivative, namely an option on the composition of LIBOR rates. The formulae are based on Fourier transform methods for option pricing. We consider two models for the evolution of interest rates: an HJM-type forward rate model and a LIBOR-…

2009-02-19abs ↗pdf ↗

Researchers develop Malliavin calculus for signatures, simplifying option Greeks computation.

problem Lack of tractability and explicit representations in Malliavin calculus.
method Focus on finite linear combinations of time-extended Brownian motion signatures, derive explicit formulas for Malliavin derivative, and compute Greeks for path-dependent options.
result Closed-form expressions for classical operators of Malliavin calculus, providing algebraic formulations.