Antoon Pelsser - Profile on Academia.edu (original) (raw)
Papers by Antoon Pelsser
Pricing long-maturity equity and FX derivatives with stochastic interest rates and stochastic equity
In this paper we extend the stochastic volatility model of Schoebel and Zhu (1999) by including s... more In this paper we extend the stochastic volatility model of Schoebel and Zhu (1999) by including stochastic interest rates. Furthermore we allow all driving model factors to be instantaneously correlated with each other, i.e. we allow for a correlation between the instantaneous interest rates, the volatilities and the underlying stock returns. By deriving the characteristic function of the log-asset price
An Empirical Comparison of One-Factor Models
Springer Finance, 2000
Efficient Methods for Valuing Interest Rate Derivatives
Springer Finance, 2000
... The models discussed here are not a reflection of the models in use by ABN-Amro Bank NV at th... more ... The models discussed here are not a reflection of the models in use by ABN-Amro Bank NV at the time of writing this manuscript. ... Page 10. Page 11. Preface This book aims to give an overview of models that can be used for efficient valuation of (exotic) interest rate derivatives. ...
Herziening financieel toetsingskader
Pricing Double Barrier Options: An Analytical Approach
A Tractable Interest Rate Model with Positive Interest Rates
A tractable yield-curve model that guarantees positive interest rates
Review of Derivatives Research, 1996
An Efficient Algorithm for Calculating Prices in the Hull-White Model
Pricing double barrier options using Laplace transforms
Finance and Stochastics, 2000
. In this paper we address the pricing of double barrier options. To derive the density functio... more . In this paper we address the pricing of double barrier options. To derive the density function of the first-hit times of the barriers, we analytically invert the Laplace transform by contour integration. With these barrier densities, we derive pricing formulæfor new types of barrier options: knock-out barrier options which pay a rebate when either one of the barriers is hit. Furthermore we discuss more complicated types of barrier options like double knock-in options.
On the Applicability of the Wang Transform for Pricing Financial Risks
ASTIN Bulletin, 2008
Pricing of Flexible and Limit Caps
Modelonzekerheid en waardering
Time-Consistent Actuarial Valuations
Professie en praktijk-Een Europees toezichtkader via innovatie en harmonisatie
Option Pricing, Arbitrage and Martingales
Robustness, Model Uncertainty and Pricing
Instantaneous Mean-Variance Hedging and Sharpe Ratio Pricing in a Regime-Switching Financial Model
Stochastic Models, 2015
SSRN Electronic Journal, 2000
The Least Squares Monte Carlo (LSMC) method is widely applied to solve stochastic optimal control... more The Least Squares Monte Carlo (LSMC) method is widely applied to solve stochastic optimal control problems, such as pricing American-style options. A central part of LSMC is the approximation of conditional expectations across each time-step. Conventional algorithms regress the value function at the end of the time-step on a set of basis functions, which are measurable with respect to the information available at the beginning of the time-step. The corresponding regression error has two sources: an approximation error due to the finite number of basis functions, and a projection error due to the projection onto the coarser filtration at the beginning of the interval. The convergence speed for the conventional algorithms is determined by the projection error component, which converges relatively slowly. Glasserman and Yu propose the Regress-Later method, wherein the value function at the end of the time-step is regressed on a set of basis functions, which are measurable with respect to the information available at the end of the time-step. The conditional expectation across the time-step is then computed analytically for each basis function. We show in this paper that by using Regress-Later the projection error component is removed. This implies that the Regress Later method has the potential of converging significantly faster than the conventional algorithms. We provide sufficient conditions for achieving fast convergence on compact and non-compact sets and we give an explicit example.
Pricing long-maturity equity and FX derivatives with stochastic interest rates and stochastic equity
In this paper we extend the stochastic volatility model of Schoebel and Zhu (1999) by including s... more In this paper we extend the stochastic volatility model of Schoebel and Zhu (1999) by including stochastic interest rates. Furthermore we allow all driving model factors to be instantaneously correlated with each other, i.e. we allow for a correlation between the instantaneous interest rates, the volatilities and the underlying stock returns. By deriving the characteristic function of the log-asset price
An Empirical Comparison of One-Factor Models
Springer Finance, 2000
Efficient Methods for Valuing Interest Rate Derivatives
Springer Finance, 2000
... The models discussed here are not a reflection of the models in use by ABN-Amro Bank NV at th... more ... The models discussed here are not a reflection of the models in use by ABN-Amro Bank NV at the time of writing this manuscript. ... Page 10. Page 11. Preface This book aims to give an overview of models that can be used for efficient valuation of (exotic) interest rate derivatives. ...
Herziening financieel toetsingskader
Pricing Double Barrier Options: An Analytical Approach
A Tractable Interest Rate Model with Positive Interest Rates
A tractable yield-curve model that guarantees positive interest rates
Review of Derivatives Research, 1996
An Efficient Algorithm for Calculating Prices in the Hull-White Model
Pricing double barrier options using Laplace transforms
Finance and Stochastics, 2000
. In this paper we address the pricing of double barrier options. To derive the density functio... more . In this paper we address the pricing of double barrier options. To derive the density function of the first-hit times of the barriers, we analytically invert the Laplace transform by contour integration. With these barrier densities, we derive pricing formulæfor new types of barrier options: knock-out barrier options which pay a rebate when either one of the barriers is hit. Furthermore we discuss more complicated types of barrier options like double knock-in options.
On the Applicability of the Wang Transform for Pricing Financial Risks
ASTIN Bulletin, 2008
Pricing of Flexible and Limit Caps
Modelonzekerheid en waardering
Time-Consistent Actuarial Valuations
Professie en praktijk-Een Europees toezichtkader via innovatie en harmonisatie
Option Pricing, Arbitrage and Martingales
Robustness, Model Uncertainty and Pricing
Instantaneous Mean-Variance Hedging and Sharpe Ratio Pricing in a Regime-Switching Financial Model
Stochastic Models, 2015
SSRN Electronic Journal, 2000
The Least Squares Monte Carlo (LSMC) method is widely applied to solve stochastic optimal control... more The Least Squares Monte Carlo (LSMC) method is widely applied to solve stochastic optimal control problems, such as pricing American-style options. A central part of LSMC is the approximation of conditional expectations across each time-step. Conventional algorithms regress the value function at the end of the time-step on a set of basis functions, which are measurable with respect to the information available at the beginning of the time-step. The corresponding regression error has two sources: an approximation error due to the finite number of basis functions, and a projection error due to the projection onto the coarser filtration at the beginning of the interval. The convergence speed for the conventional algorithms is determined by the projection error component, which converges relatively slowly. Glasserman and Yu propose the Regress-Later method, wherein the value function at the end of the time-step is regressed on a set of basis functions, which are measurable with respect to the information available at the end of the time-step. The conditional expectation across the time-step is then computed analytically for each basis function. We show in this paper that by using Regress-Later the projection error component is removed. This implies that the Regress Later method has the potential of converging significantly faster than the conventional algorithms. We provide sufficient conditions for achieving fast convergence on compact and non-compact sets and we give an explicit example.