* Working on implementing GARCH in QuantLib based on chapter 21 in Options Futures and Other Derivatives * First attempt to maximize the 2 variable function based on sample data in YenDataforGARCH.csv * To help this, some python was written using mplot3d, matplotlib and numpy to graph the function and solve the maximum numerically. * GARCH(1,1) is implemented within QuantLib::Garch11 but the estimation of the 3 input factors to the model is not optimised using MLE. * QuantLib has some multi-dimension minimisation algorithms implemented in QuantLib::Math. * QuantLib::CostFunction is the base class minimisation function that QuantLib::Garch11 has to implement. * Numerical Recipes has several optimisation algorithms, single and multi variate. * Introduction to Algorithms also discusses minimisation algorithms, and uses the simplex algorithm exclusively |

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