• Corpus ID: 117304431

Quasi-Monte Carlo methods for the Heston model

  title={Quasi-Monte Carlo methods for the Heston model},
  author={Jan Baldeaux and Dale O. Roberts},
In this paper, we discuss the application of quasi-Monte Carlo methods to the Heston model. We base our algorithms on the Broadie-Kaya algorithm, an exact simulation scheme for the Heston model. As the joint transition densities are not available in closed-form, the Linear Transformation method due to Imai and Tan, a popular and widely applicable method to improve the effectiveness of quasi-Monte Carlo methods, cannot be employed in the context of path-dependent options when the underlying… 
Backward simulation methods for pricing American options under the CIR process
This paper proposes forward–backward simulation approaches for Alfonsi’s two implicit schemes, the fixed Euler schemes and the exact scheme to solve the memory requirement issue of the Least Squares Monte Carlo method when pricing American options by simulation.
Enhancing Least Squares Monte Carlo with Diffusion Bridges: An Application to Energy Facilities
The aim of this study is to present an efficient and easy framework for the application of the Least Squares Monte Carlo methodology to the pricing of gas or power facilities as detailed in Boogert
Enhancing Least Squares Monte Carlo with diffusion bridges: an application to energy facilities
The aim of this study is to present an efficient and easy framework for the application of the Least Squares Monte Carlo methodology to the pricing of gas or power facilities as detailed in Boogert
Numerical approximation for options pricing of a stochastic volatility jump-diffusion model
In this paper, we are interested in pricing options (European and Quanto) by a model in which the asset prices follow a jump-diffusion model with a stochastic volatility in n dimensions. The
Computing Functionals of Multidimensional Diffusions via Monte Carlo Methods
We discuss suitable classes of diffusion processes, for which functionals relevant to finance can be computed via Monte Carlo methods. In particular, we construct exact simulation schemes for
Dynamic Forces behind the Common Currency Risk Factors' Expected Moments
This paper examines the association between option-implied distributions of common currency risk factors (dollar ($RX$) and carry ($HML_{FX}$) ) and macroeconomic expectations in form of spread yield
Métodos Monte Carlo y Productos Estructurados


Quasi-Monte Carlo for finance beyond Black-Scholes
Quasi-Monte Carlo methods are used to approximate integrals of high dimensionality. However, if the problem under consideration is of unbounded dimensionality, it is not obvious if one can apply
We propose a quasi-Monte Carlo (qMC) algorithm to simulate variates from the normal inverse Gaussian (NIG) distribution. The algorithm is based on a Monte Carlo technique found in Rydberg [13], and
Efficient Monte Carlo and Quasi - Monte Carlo Option Pricing Under the Variance Gamma Model
This work develops and study efficient Monte Carlo algorithms for pricing path-dependent options with the variance gamma model, and combines the gamma bridge sampling with randomized quasi--Monte Carlo to reduce the variance and thus further improve the efficiency.
Quasi-Monte Carlo methods for the Kou model
  • Jan Baldeaux
  • Computer Science, Mathematics
    Monte Carlo Methods Appl.
  • 2008
QMC approaches are introduced for the integration problems pertaining to the Poisson processes, compoundPoisson processes and jump-diffusion processes underlying the Kou model as opposed to increment-by-increment approaches.
An Accelerating Quasi-Monte Carlo Method for Option Pricing Under the Generalized Hyperbolic L[e-acute]vy Process
This paper develops a simple and yet practically efficient algorithm for simulating high-dimensional exotic options based on an extension of Imai and Tan's linear transformation method that can be used to enhance quasi-Monte Carlo method in a wide range of applications.
Monte Carlo Methods and Models in Finance and Insurance
Introduction and User Guide Introduction and concept Contents How to use this book? Further literature Acknowledgements Generating Random Numbers Introduction Examples of random number generators
Quasi-Monte Carlo Methods in Financial Engineering: An Equivalence Principle and Dimension Reduction
Whereas in QMC all the common methods may lose their power in some situations, the new method behaves very well in all cases, and can be interpreted as a practical way of reducing the effective dimension for some class of functions.
Stratified sampling and quasi-Monte Carlo simulation of Lévy processes
  • G. Leobacher
  • Mathematics, Computer Science
    Monte Carlo Methods Appl.
  • 2006
We provide a method for the generation of paths of Lévy processes which allows for more efficient simulation than crude step-by-step generation. We show how, using our method, one can apply
Exact simulation of option Greeks under stochastic volatility and jump diffusion models
  • M. Broadie, Ö. Kaya
  • Computer Science, Mathematics
    Proceedings of the 2004 Winter Simulation Conference, 2004.
  • 2004
Monte Carlo simulation estimators are derived to compute Greeks under Heston's stochastic volatility model and some variants of it which include jumps in the price and variance processes to generate unbiased estimates of option price derivatives in these models.
Specification Analysis of Affine Term Structure Models
In this paper, we explore the features of affine term structure models that are empirically important for explaining the joint distribution of yields on short and long-term interest rate swaps. We