Zobrazeno 1 - 10
of 612
pro vyhledávání: '"Bayer, Christian"'
This work addresses stochastic optimal control problems where the unknown state evolves in continuous time while partial, noisy, and possibly controllable measurements are only available in discrete time. We develop a framework for controlling such s
Externí odkaz:
http://arxiv.org/abs/2407.18018
Autor:
Bayer, Christian, Hammouda, Chiheb Ben, Papapantoleon, Antonis, Samet, Michael, Tempone, Raúl
Efficiently pricing multi-asset options poses a significant challenge in quantitative finance. The Monte Carlo (MC) method remains the prevalent choice for pricing engines; however, its slow convergence rate impedes its practical application. Fourier
Externí odkaz:
http://arxiv.org/abs/2403.02832
We propose two signature-based methods to solve the optimal stopping problem - that is, to price American options - in non-Markovian frameworks. Both methods rely on a global approximation result for $L^p-$functionals on rough path-spaces, using line
Externí odkaz:
http://arxiv.org/abs/2312.03444
Autor:
Bayer, Christian, Breneis, Simon
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 process deri
Externí odkaz:
http://arxiv.org/abs/2310.04146
Autor:
Bayer, Christian, Breneis, Simon
The rough Heston model is a very popular recent model in mathematical finance; however, the lack of Markov and semimartingale properties poses significant challenges in both theory and practice. A way to resolve this problem is to use Markovian appro
Externí odkaz:
http://arxiv.org/abs/2309.07023
We present an adaptive algorithm for effectively solving rough differential equations (RDEs) using the log-ODE method. The algorithm is based on an error representation formula that accurately describes the contribution of local errors to the global
Externí odkaz:
http://arxiv.org/abs/2307.12590
In this work, we introduce a novel pricing methodology in general, possibly non-Markovian local stochastic volatility (LSV) models. We observe that by conditioning the LSV dynamics on the Brownian motion that drives the volatility, one obtains a time
Externí odkaz:
http://arxiv.org/abs/2307.09216
Autor:
Samet, Michael, Bayer, Christian, Hammouda, Chiheb Ben, Papapantoleon, Antonis, Tempone, Raúl
Efficiently pricing multi-asset options is a challenging problem in quantitative finance. When the characteristic function is available, Fourier-based methods are competitive compared to alternative techniques because the integrand in the frequency s
Externí odkaz:
http://arxiv.org/abs/2203.08196
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 linear mode
Externí odkaz:
http://arxiv.org/abs/2203.02943
Motivated by the challenges related to the calibration of financial models, we consider the problem of numerically solving a singular McKean-Vlasov equation $$ d X_t= \sigma(t,X_t) X_t \frac{\sqrt v_t}{\sqrt {E[v_t|X_t]}}dW_t, $$ where $W$ is a Brown
Externí odkaz:
http://arxiv.org/abs/2203.01160