AbstractData for calibration and out-of-sample error testing of option pricing models are provided alongside data obtained from optimization procedures in "On calibration of stochastic and fractional stochastic volatility models" [1]. Firstly we describe testing data sets, further calibration data obtained from combined optimizers is visually depicted – interactive 3d bar plots are provided. The data is suitable for a further comparison of other optimization routines and also to benchmark different pricing models
This paper compares the performance of three methods for pricing vanilla options in models with know...
Stochastic volatility models are used in mathematical finance to describe the dynamics of asset pric...
We investigate the idea of solving calibration problems for stochastic dynamical systems using stati...
Data for calibration and out-of-sample error testing of option pricing models are provided alongside...
AbstractData for calibration and out-of-sample error testing of option pricing models are provided a...
Abstract In spite of the popularity of model calibration in …nance, empirical researchers have put m...
Many numerical aspects are involved in parameter estimation of stochastic volatility models. We inve...
We consider stochastic volatility models using piecewise constant parameters. We suggest a hybrid op...
In this paper we consider an explicitly solvable multiscale stochastic volatility model that genera...
For the pricing of interest rate derivatives various stochastic interest rate models are used. The s...
A new method for calibrating the Black-Scholes asset price dynamics model is proposed. The data use...
We consider calibration problems for models of pricing derivatives which occur in mathematical finan...
A new method for calibrating the Black-Scholes asset price dynamics model is proposed. The data use...
This paper compares the performance of three methods for pricing vanilla options in models with know...
This dissertation is devoted to high performance numerical methods for option valuation and model ca...
This paper compares the performance of three methods for pricing vanilla options in models with know...
Stochastic volatility models are used in mathematical finance to describe the dynamics of asset pric...
We investigate the idea of solving calibration problems for stochastic dynamical systems using stati...
Data for calibration and out-of-sample error testing of option pricing models are provided alongside...
AbstractData for calibration and out-of-sample error testing of option pricing models are provided a...
Abstract In spite of the popularity of model calibration in …nance, empirical researchers have put m...
Many numerical aspects are involved in parameter estimation of stochastic volatility models. We inve...
We consider stochastic volatility models using piecewise constant parameters. We suggest a hybrid op...
In this paper we consider an explicitly solvable multiscale stochastic volatility model that genera...
For the pricing of interest rate derivatives various stochastic interest rate models are used. The s...
A new method for calibrating the Black-Scholes asset price dynamics model is proposed. The data use...
We consider calibration problems for models of pricing derivatives which occur in mathematical finan...
A new method for calibrating the Black-Scholes asset price dynamics model is proposed. The data use...
This paper compares the performance of three methods for pricing vanilla options in models with know...
This dissertation is devoted to high performance numerical methods for option valuation and model ca...
This paper compares the performance of three methods for pricing vanilla options in models with know...
Stochastic volatility models are used in mathematical finance to describe the dynamics of asset pric...
We investigate the idea of solving calibration problems for stochastic dynamical systems using stati...