Related Experiment Video
Updated: Mar 17, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Test data sets for calibration of stochastic and fractional stochastic volatility models
1NTIS - New Technologies for the Information Society, Faculty of Applied Sciences, University of West Bohemia, Czech Republic.
Abstract:
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.
Related Concept Videos
Calibration Curves: Linear Least Squares
For data that follow a straight line, the standard method for fitting is the linear...
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Calibration Curves: Correlation Coefficient
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Uncertainty in Measurement: Accuracy and Precision

