Data 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. Keywords: Fractional stochastic volatility model, Heston model, Option pricing, Calibration data, Out-of-sample erro
A new method for calibrating the Black-Scholes asset price dynamics model is proposed. The data use...
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...
AbstractData for calibration and out-of-sample error testing of option pricing models are provided a...
Treball fi de màster de: Master's Degree in Economics and FinanceDirectors: Filippo Ippolito ; Eulàl...
In this paper we consider an explicitly solvable multiscale stochastic volatility model that genera...
Parameters of equity pricing models, such as the Heston's stochastic volatility model, have to be ca...
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 establish double Heston model with approximative fractional stochastic volatility in this article...
We study the "real-world" calibration of a partially specified stochastic volatility model, where th...
Stochastic volatility models are used in mathematical finance to describe the dynamics of asset pric...
This paper compares the performance of three methods for pricing vanilla options in models with know...
Parameters of equity pricing models, such as the Heston’s stochastic volatility model, have to be ca...
Abstract Robust calibration of option valuation models to quoted option prices is nontrivial, but as...
A new method for calibrating the Black-Scholes asset price dynamics model is proposed. The data use...
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...
AbstractData for calibration and out-of-sample error testing of option pricing models are provided a...
Treball fi de màster de: Master's Degree in Economics and FinanceDirectors: Filippo Ippolito ; Eulàl...
In this paper we consider an explicitly solvable multiscale stochastic volatility model that genera...
Parameters of equity pricing models, such as the Heston's stochastic volatility model, have to be ca...
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 establish double Heston model with approximative fractional stochastic volatility in this article...
We study the "real-world" calibration of a partially specified stochastic volatility model, where th...
Stochastic volatility models are used in mathematical finance to describe the dynamics of asset pric...
This paper compares the performance of three methods for pricing vanilla options in models with know...
Parameters of equity pricing models, such as the Heston’s stochastic volatility model, have to be ca...
Abstract Robust calibration of option valuation models to quoted option prices is nontrivial, but as...
A new method for calibrating the Black-Scholes asset price dynamics model is proposed. The data use...
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...