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Finite difference approximations to multi-asset American put option price are considered. The assets are modelled as a multi-dimensional diffusion process with variable drift and volatility. Approximation error of order one quarter with…

Computational Finance · Quantitative Finance 2011-10-03 David Šiška

The vast majority of works on option pricing operate on the assumption of risk neutral valuation, and consequently focus on the expected value of option returns, and do not consider risk parameters, such as variance. We show that it is…

Pricing of Securities · Quantitative Finance 2012-04-17 Adi Ben-Meir , Jeremy Schiff

We propose a new, data-driven approach for efficient pricing of - fixed- and float-strike - discrete arithmetic Asian and Lookback options when the underlying process is driven by the Heston model dynamics. The method proposed in this…

Computational Finance · Quantitative Finance 2024-02-19 Leonardo Perotti , Lech A. Grzelak

These are course notes on the application of SDEs to options pricing. The author was partially supported by NSF grant DMS-0739195.

Mathematical Finance · Quantitative Finance 2019-01-03 Andrew Papanicolaou

We derive a new high-order compact finite difference scheme for option pricing in stochastic volatility jump models, e.g. in Bates model. In such models the option price is determined as the solution of a partial integro-differential…

Computational Finance · Quantitative Finance 2019-02-25 Bertram Düring , Alexander Pitkin

We consider the pricing of derivatives written on the discretely sampled realized variance of an underlying security. In the literature, the realized variance is usually approximated by its continuous-time limit, the quadratic variation of…

Pricing of Securities · Quantitative Finance 2010-11-24 Martin Keller-Ressel , Johannes Muhle-Karbe

We present an option pricing formula for European options in a stochastic volatility model. In particular, the volatility process is defined using a fractional integral of a diffusion process and both the stock price and the volatility…

Pricing of Securities · Quantitative Finance 2020-07-29 Marc Lagunas-Merino , Salvador Ortiz-Latorre

New simulation approaches to evaluating path-dependent options without matrix inversion issues nor Euler bias are evaluated. They employ three main contributions: Stochastic approximation replaces regression in the LSM algorithm; Explicit…

Pricing of Securities · Quantitative Finance 2018-04-13 Michael A. Kouritzin

We present a model for direct semi-parametric estimation of the State Price Density (SPD) implied in quoted option prices. We treat the observed prices as expected values of possible pay-offs at maturity, weighted by the unknown probability…

Applications · Statistics 2021-03-29 Gianluca Frasso , Paul H. C. Eilers

In 'A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options', Heston proposes a Stochastic Volatility (SV) model with constant interest rate and derives a semi-explicit valuation formula.…

Computational Finance · Quantitative Finance 2021-03-10 Javier de Frutos , Victor Gaton

We perform a classification of the Lie point symmetries for the Black--Scholes--Merton Model for European options with stochastic volatility, $\sigma$, in which the last is defined by a stochastic differential equation with an…

Analysis of PDEs · Mathematics 2016-05-04 A. Paliathanasis , K. Krishnakumar , K. M. Tamizhmani , P. G. L. Leach

We examine whether model-based spot volatility estimators extracted from traded options data enhance the predictive power of the Heterogeneous Autoregressive (HAR) model for realized volatility. Specifically, we infer spot volatility under…

Risk Management · Quantitative Finance 2026-04-13 Zheqi Fan , Meng Melody Wang , Yifan Ye

The paper builds a Variance-Gamma (VG) model with five parameters: location ($\mu$), symmetry ($\delta$), volatility ($\sigma$), shape ($\alpha$), and scale ($\theta$); and studies its application to the pricing of European options. The…

Pricing of Securities · Quantitative Finance 2023-01-18 A. H. Nzokem

We investigate the pricing of financial options under the 2-hypergeometric stochastic volatility model. This is an analytically tractable model that reproduces the volatility smile and skew effects observed in empirical market data. Using a…

Probability · Mathematics 2017-08-04 Rúben Sousa , Ana Bela Cruzeiro , Manuel Guerra

We provide an efficient and accurate simulation scheme for the rough Heston model in the standard ($H>0$) as well as the hyper-rough regime ($H > -1/2$). The scheme is based on low-dimensional Markovian approximations of the rough Heston…

Computational Finance · Quantitative Finance 2023-10-09 Christian Bayer , Simon Breneis

We consider closed-form approximations for European put option prices within the Heston and GARCH diffusion stochastic volatility models with time-dependent parameters. Our methodology involves writing the put option price as an expectation…

Mathematical Finance · Quantitative Finance 2024-02-06 Kaustav Das , Nicolas Langrené

In this paper an improved Cuckoo Search Algorithm is developed to allow for an efficient and robust calibration of the Heston option pricing model for American options. Calibration of stochastic volatility models like the Heston is…

Neural and Evolutionary Computing · Computer Science 2015-08-03 Stefan Haring , Ronald Hochreiter

We consider arbitrage free valuation of European options in Black-Scholes and Merton markets, where the general structure of the market is known, however the specific parameters are not known. In order to reflect this subjective uncertainty…

Mathematical Finance · Quantitative Finance 2017-01-13 Hanno Gottschalk , Elpida Nizami , Marius Schubert

We examine optimal quadratic hedging of barrier options in a discretely sampled exponential L\'{e}vy model that has been realistically calibrated to reflect the leptokurtic nature of equity returns. Our main finding is that the impact of…

Mathematical Finance · Quantitative Finance 2018-08-10 Aleš Černý

The Heston model stands out from the class of stochastic volatility (SV) models mainly for two reasons. Firstly, the process for the volatility is non-negative and mean-reverting, which is what we observe in the markets. Secondly, there…

Computational Finance · Quantitative Finance 2010-10-11 Agnieszka Janek , Tino Kluge , Rafal Weron , Uwe Wystup
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