% Implementation of the analytical approach for valuation of vanilla options under the log-normal stochastic volatility model
% 1) LogNormalBetaSVPricingMain for computing option prices and comparision to MC simulations
% 2) LogNormalBetaSVCalibrationMain for model calibration to market implied volatilities
% Implemented functionality in this file LogNormalBetaSVPricingMain:
%  Compute option prices in the lognormal beta SV model
% using Fourier inversion formulas with the moment generating function (MGF)
% computed by solving the system of ODE-s using:
% 1 - 4th order Runge-Kutta method (see the paper for analytical details) - preferable default method
% 2 - Rosenbrock stiff method
% 3 - Using Matlab ODE solver - slow and innacurate
%  Compute options prices by Monte-Carlo simulation of the log-normal SV model
%  Compare option prices between the analytic approach and MC simulation, and also implied volatilities from this prices
%  Supported are options on the equity and quadratic variance (QV)
%  Implemented jump size distributions: deterministic jumps in log-return and volatility
% Based on the paper:
% Sepp, A. (2016), Log-Normal Stochastic Volatility Model: Affine Decomposition of Moment Generating Function and Pricing of Vanilla Options
% Working paper available at SSRN: http://ssrn.com/abstract=2522425
% by Artur Sepp
% Last Update: March 7, 2016
% This code is distributed via the mathworks file-exchange and it is covered by the BSD license
% This code is being provided solely for information and general illustrative purposes.
% The author will not be responsible for numbers produced from using the code.
Artur Sepp (2021). Log-Normal Stochastic Volatility Model: Moment Generating Function and Pricing of Vanilla Options (https://www.mathworks.com/matlabcentral/fileexchange/48408-log-normal-stochastic-volatility-model-moment-generating-function-and-pricing-of-vanilla-options), MATLAB Central File Exchange. Retrieved .
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