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Developments in finance industry and academic research has led to innovative financial products. This paper presents an alternative approach to price American options. Our approach utilizes famous \cite{heath1992bond} ("HJM") technique to…

Mathematical Finance · Quantitative Finance 2021-09-13 Kushantha Fernando , Vajira Manathunga

When the underlying asset displays oscillations, spikes or heavy-tailed distributions, the lognormal diffusion process (for which Black and Scholes developed their momentous option pricing formula) is inadequate: in order to overcome these…

Computational Finance · Quantitative Finance 2017-12-22 Marcellino Gaudenzi , Alice Spangaro , Patrizia Stucchi

This report investigates the computation of option Greeks for European and Asian options under the Heston stochastic volatility model on GPU. We first implemented the exact simulation method proposed by Broadie and Kaya and used it as a…

Computational Finance · Quantitative Finance 2023-09-20 Pierre-Antoine Arsaguet , Paul Bilokon

In this article we propose a novel approach to reduce the computational complexity of various approximation methods for pricing discrete time American options. Given a sequence of continuation values estimates corresponding to different…

Computational Finance · Quantitative Finance 2013-12-30 Denis Belomestny , Fabian Dickmann , Tigran Nagapetyan

We apply the concepts of utility based pricing and hedging of derivatives in stochastic volatility markets and introduce a new class of "reciprocal affine" models for which the indifference price and optimal hedge portfolio for pure…

Probability · Mathematics 2008-12-02 M. R. Grasselli , T. R. Hurd

This paper investigates the use of multiple directions of stratification as a variance reduction technique for Monte Carlo simulations of path-dependent options driven by Gaussian vectors. The precision of the method depends on the choice…

Computational Finance · Quantitative Finance 2010-04-29 Benjamin Jourdain , Bernard Lapeyre , Piergiacomo Sabino

The pricing of financial derivatives, which requires massive calculations and close-to-real-time operations under many trading and arbitrage scenarios, were largely infeasible in the past. However, with the advancement of modern computing,…

Pricing of Securities · Quantitative Finance 2019-06-18 Wei-Cheng Chen , Wei-Ho Chung

We generalize the Hamiltonian Monte Carlo algorithm with a stack of neural network layers and evaluate its ability to sample from different topologies in a two dimensional lattice gauge theory. We demonstrate that our model is able to…

High Energy Physics - Lattice · Physics 2021-05-10 Sam Foreman , Xiao-Yong Jin , James C. Osborn

We consider stochastic volatility models under parameter uncertainty and investigate how model derived prices of European options are affected. We let the pricing parameters evolve dynamically in time within a specified region, and…

Mathematical Finance · Quantitative Finance 2018-07-12 Samuel N. Cohen , Martin Tegnér

Characteristic functions of several popular classes of distributions and processes admit analytic continuation into unions of strips and open coni around $\mathbb{R}\subset \mathbb{C}$. The Fourier transform techniques reduces calculation…

Computational Finance · Quantitative Finance 2018-08-17 Svetlana Boyarchenko , Sergei Levendorskiĭ

The value of an American option is the maximized value of the discounted cash flows from the option. At each time step, one needs to compare the immediate exercise value with the continuation value and decide to exercise as soon as the…

Computational Finance · Quantitative Finance 2023-06-27 Zineb El Filali Ech-Chafiq , Pierre Henry-Labordere , Jérôme Lelong

A parsimonious generalization of the Heston model is proposed where the volatility-of-volatility is assumed to be stochastic. We follow the perturbation technique of Fouque et al (2011, CUP) to derive a first order approximation of the…

Pricing of Securities · Quantitative Finance 2017-06-06 Jean-Pierre Fouque , Yuri F. Saporito

We propose a hybrid Monte Carlo (HMC) technique applicable to high-dimensional multivariate normal distributions that effectively samples along chaotic trajectories. The method is predicated on the freedom of choice of the HMC momentum…

Data Analysis, Statistics and Probability · Physics 2016-04-26 Nirag Kadakia

Given a data set with many features observed in a large number of conditions, it is desirable to fuse and aggregate conditions which are similar to ease the interpretation and extract the main characteristics of the data. This paper…

Computation · Statistics 2015-05-29 Julien Chiquet , Pierre Gutierrez , Guillem Rigaill

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

The quadratic rough Heston model provides a natural way to encode Zumbach effect in the rough volatility paradigm. We apply multi-factor approximation and use deep learning methods to build an efficient calibration procedure for this model.…

Computational Finance · Quantitative Finance 2022-05-31 Mathieu Rosenbaum , Jianfei Zhang

We propose a robust and stable lattice method which permits to obtain very accurate American option prices in presence of CIR stochastic interest rate without any numerical restriction on its parameters. Numerical results show the…

Computational Finance · Quantitative Finance 2016-04-07 Elisa Appolloni , Lucia Caramellino , Antonino Zanette

There is a great number of factors to take into account when building and managing an investment portfolio. It is widely believed that a proper set-up of the portfolio combined with a good, robust management strategy is the key to…

Portfolio Management · Quantitative Finance 2021-04-28 Jarosław Gruszka , Janusz Szwabiński

We present a new approach to the following meta-problem: given a quantitative property of trees, design a type system such that the desired property for the tree generated by an infinitary ground lambda-term corresponds to some property of…

Logic in Computer Science · Computer Science 2017-03-31 Paweł Parys

In recent years there has been much interest in the Monte Carlo tree search algorithm, a new, adaptive, randomized optimization algorithm. In fields as diverse as Artificial Intelligence, Operations Research, and High Energy Physics,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-17 S. Ali Mirsoleimani , Aske Plaat , Jaap van den Herik , Jos Vermaseren
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