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Related papers: Hedging under rough volatility

200 papers

We investigate model risk and distributionally robust optimization (DRO) under marginal and martingale constraints. Building on our previous work, we address the previously open case of static hedging with second-period maturity vanilla…

Probability · Mathematics 2026-01-29 Nathan Sauldubois

We study the weak convergence rate in the discretization of rough volatility models. After showing a lower bound $2H$ under a general model, where $H$ is the Hurst index of the volatility process, we give a sharper bound $H + 1/2$ under a…

Computational Finance · Quantitative Finance 2022-03-08 Christian Bayer , Masaaki Fukasawa , Shonosuke Nakahara

This work studies the dynamic risk management of the risk-neutral value of the potential credit losses on a portfolio of derivatives. Sensitivities-based hedging of such liability is sub-optimal because of bid-ask costs, pricing models…

Computational Finance · Quantitative Finance 2023-12-22 Roberto Daluiso , Marco Pinciroli , Michele Trapletti , Edoardo Vittori

In complete markets, there are risky assets and a riskless asset. It is assumed that the riskless asset and the risky asset are traded continuously in time and that the market is frictionless. In this paper, we propose a new method for…

Pricing of Securities · Quantitative Finance 2019-10-02 Abootaleb Shirvani , Stoyan V. Stoyanov , Svetlozar T. Rachev , Frank J. Fabozzi

Derivative hedging and pricing are important and continuously studied topics in financial markets. Recently, deep hedging has been proposed as a promising approach that uses deep learning to approximate the optimal hedging strategy and can…

Computational Finance · Quantitative Finance 2024-04-16 Masanori Hirano

Rough volatility models have gained considerable interest in the quantitative finance community in recent years. In this paradigm, the volatility of the asset price is driven by a fractional Brownian motion with a small value for the Hurst…

Statistics Theory · Mathematics 2024-02-16 Carsten Chong , Marc Hoffmann , Yanghui Liu , Mathieu Rosenbaum , Grégoire Szymanski

We investigate the statistical evidence for the use of `rough' fractional processes with Hurst exponent $H< 0.5$ for the modeling of volatility of financial assets, using a model-free approach. We introduce a non-parametric method for…

Statistical Finance · Quantitative Finance 2023-07-11 Rama Cont , Purba Das

We introduce a new class of continuous-time models of the stochastic volatility of asset prices. The models can simultaneously incorporate roughness and slowly decaying autocorrelations, including proper long memory, which are two stylized…

Statistical Finance · Quantitative Finance 2021-01-06 Mikkel Bennedsen , Asger Lunde , Mikko S. Pakkanen

This paper develops a flexible and computationally efficient multivariate volatility model, which allows for dynamic conditional correlations and volatility spillover effects among financial assets. The new model has desirable properties…

Methodology · Statistics 2025-07-25 Wenyu Li , Yuchang Lin , Qianqian Zhu , Guodong Li

The collateral choice option allows a collateral-posting party the opportunity to change the type of security in which the collateral is deposited. Due to non-zero collateral basis spreads, this optionality significantly impacts asset…

Risk Management · Quantitative Finance 2022-08-17 Griselda Deelstra , Lech A. Grzelak , Felix L. Wolf

In this paper, we relax the power parameter of instantaneous variance and develop a new stochastic volatility plus jumps model that generalize the Heston model and 3/2 model as special cases. This model has two distinctive features. First,…

Mathematical Finance · Quantitative Finance 2017-03-20 Wei Lin , Shenghong Li , Shane Chern

It is known that the implied volatility skew of FX options demonstrates a stochastic behavior which is called stochastic skew. In this paper we create stochastic skew by assuming the spot/instantaneous variance correlation to be stochastic.…

Computational Finance · Quantitative Finance 2017-01-20 Andrey Itkin

Recent years have seen an increased level of interest in pricing equity options under a stochastic volatility model such as the Heston model. Often, simulating a Heston model is difficult, as a standard finite difference scheme may lead to…

Computational Finance · Quantitative Finance 2011-11-28 Ian Iscoe , Asif Lakhany

We provide explicit small-time formulae for the at-the-money implied volatility, skew and curvature in a large class of models, including rough volatility models and their multi-factor versions. Our general setup encompasses both European…

Mathematical Finance · Quantitative Finance 2023-11-15 Antoine Jacquier , Aitor Muguruza , Alexandre Pannier

This paper examines the volatility and covariance dynamics of cash and futures contracts that underlie the Optimal Hedge Ratio (OHR) across different hedging time horizons. We examine whether hedge ratios calculated over a short term…

Risk Management · Quantitative Finance 2011-03-31 John Cotter , Jim Hanly

We develop a semi-static framework for the variance-optimal hedging of multi-asset derivatives exposed to correlation and covariance risk. The approach combines continuous-time dynamic trading in the underlying assets with a static…

Mathematical Finance · Quantitative Finance 2026-03-27 Konstantinos Chatziandreou , Sven Karbach

This paper introduces one new multivariate volatility model that can accommodate an appropriately defined network structure based on low-frequency and high-frequency data. The model reduces the number of unknown parameters and the…

Statistical Finance · Quantitative Finance 2022-04-28 Huiling Yuan , Guodong Li , Junhui Wang

This paper focuses on a dynamic multi-asset mean-variance portfolio selection problem under model uncertainty. We develop a continuous time framework for taking into account ambiguity aversion about both expected return rates and…

Portfolio Management · Quantitative Finance 2021-12-02 Huyen Pham , Xiaoli Wei , Chao Zhou

We present a new volatility model, simple to implement, that includes a leverage effect whose return-volatility correlation function fits to empirical observations. This model is able to capture both the "retarded effect" induced by the…

Statistical Finance · Quantitative Finance 2020-01-03 Sebastien Valeyre , Denis Grebenkov , Sofiane Aboura , Qian Liu

In Gatheral et al. 2018, first posted in 2014, volatility is characterized by fractional behavior with a Hurst exponent $H < 0.5$, challenging traditional views of volatility dynamics. Gatheral et al. demonstrated this using realized…

Statistical Finance · Quantitative Finance 2024-09-06 Saad Mouti