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Showing 1 to 4 of 4 for “"least squares optimisation"”.
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Volatility Model Pricing and Calibration with Neural Networks using Bayesian Optimisation
… second step of the indirect method implements a least squares optimisation algorithm to calibrate the parameters. The direct method, on the other hand, uses a deep artificial neural network to calibrate the model parameters using the implied volatility surface as input. Bayesian Optimisation …
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Model Misspecification and the Hedging of Exotic Options
… option prices is performed via the use of a least squares optimisation routine. We find that there is not an asset pricing model which consistently provides a better hedge in World 1. In World 2, however, the Heston model marginally outperforms the Black-Scholes model overall. This can be …
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Simultaneous state and input estimation with applications in vehicle problems
… output and the measured output. A completion of squares approach is used to find the unique optimum in terms of the solution of a Riccati differential equation. The optimal estimate is obtained from a two-stage procedure that is reminiscent of the Kalman filter. The first stage is an …
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Optimal control reformulation for the solution of decision-making problems in chemical engineering
… obviating the need for any form of combinatorial optimisation. Two-Point Boundary Value Problems (TPBVPs) are examined and solved utilising a double shooting approach, where the initial TPBVP is reformulated into a set of Ordinary Differential Equations (ODEs) and is solved as a least-squares …