Multicurve LIBOR market models and drift-free simulation

Fernández, José Luis Fernández; Nogueiras, María R.; Pou, Marta; Vázquez, Carlos

doi:10.1080/00207160.2016.1247440

Cited by 2 publications

(3 citation statements)

References 3 publications

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“…The choice of LIBOR Market Model provides an additional computational complexity and cost in the simulation of the risk factor which enters in the evaluation of the risk functional. Although we are aware of the evolution of this model and the difficulties to cope with the practical presence of a multicurve setting (see [9][10][11], for example), we have chosen its classical version as described in [7].…”

Section: Model Setup Libor Market Modelmentioning

confidence: 99%

Global Optimization for Automatic Model Points Selection in Life Insurance Portfolios

et al. 2021

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Starting from an original portfolio of life insurance policies, in this article we propose a methodology to select model points portfolios that reproduce the original one, preserving its market risk under a certain measure. In order to achieve this goal, we first define an appropriate risk functional that measures the market risk associated to the interest rates evolution. Although other alternative interest rate models could be considered, we have chosen the LIBOR (London Interbank Offered Rate) market model. Once we have selected the proper risk functional, the problem of finding the model points of the replicating portfolio is formulated as a problem of minimizing the distance between the original and the target model points portfolios, under the measure given by the proposed risk functional. In this way, a high-dimensional global optimization problem arises and a suitable hybrid global optimization algorithm is proposed for the efficient solution of this problem. Some examples illustrate the performance of a parallel multi-CPU implementation for the evaluation of the risk functional, as well as the efficiency of the hybrid Basin Hopping optimization algorithm to obtain the model points portfolio.

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Section: Model Setup Libor Market Modelmentioning

confidence: 99%

Global Optimization for Automatic Model Points Selection in Life Insurance Portfolios

et al. 2021

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“…The main menu of this interface includes four functions: raw data, membership degree, optimisation result and exit. Among them, the original data menu mainly realises the modification, saving and printing of the athlete's body measurement data and strength data; the membership degree menu completes the selection of the membership curve; the optimisation result menu realises the display of the fuzzy optimisation results of the athlete's throwing process [10]. The structure diagram of the menu is shown in Figure 4.…”

Section: The User Interface Of Shot-put Optimisation Softwarementioning

confidence: 99%

“…Figure 4 shows the window corresponding to the optimisation results menu, showing the athlete's anthropometric data and strength data membership (i.e. changes), as well as the athlete's best throwing mode and the possibility of throwing distance under this fuzzy data distribution, and the range of changes in the flight trajectory of the shot-put in the air (where the thicker the line, the greater the probability of the flight trajectory, and the thinner the line, the less likely the flight trajectory is) [10].…”

Section: The User Interface Of Shot-put Optimisation Softwarementioning

confidence: 99%

Mathematical simulation analysis of optimal detection of shot-putters’ best path

Sun

2021

Applied Mathematics and Nonlinear Sciences

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In order to consider many uncertain factors in the process of shot-put, a fuzzy optimisation model of shot-put is proposed. With the help of fuzzy anthropometric data and strength data, the model calculates the fuzzy solution set of the athlete's best throwing mode and throwing distance with a known probability distribution, which reflects the actual process of shot throwing better than the non-fuzzy optimisation model. Then, using MATLAB6 software, the program design of the model solving and the user interface of optimisation software are developed, which realises fast calculation and good user interaction function. Finally, the actual measurement data of university shot-putters are used to verify the feasibility and effectiveness of the fuzzy optimisation model.

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Multicurve LIBOR market models and drift-free simulation

Cited by 2 publications

References 3 publications

Global Optimization for Automatic Model Points Selection in Life Insurance Portfolios

Global Optimization for Automatic Model Points Selection in Life Insurance Portfolios

Mathematical simulation analysis of optimal detection of shot-putters’ best path

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