Abdullah, Mimi Hafizah and Harun, Hanani Farhah
(2022)
Extending generalised Leland option pricing models: simulation using Monte Carlo.
In: 3rd International Conference on Applied & Industrial Mathematics and Statistics 2022, 24-26 August 2022, Online (Microsoft Teams).
(Unpublished)
Abstract
To explain option pricing movements, most studies modify the Black-Scholes model by adding other factors. The parametric generalisation, on the other hand, frequently leads to an over-parametrisation problem in the model being constructed. The model's high constraints frequently resulted in considerable underpricing of the option. The nonparametric generalisation of the Black-Scholes-Merton (BSM) model, on the other hand, is prone to both discretisation and truncation issues in pricing options. Thus, this study extends the existing option pricing models by developing Extended Generalised Leland (EGL) models based on the implied adjusted volatility introduced in Leland models. The integrated framework ensures a model-free modelling while conforming to the conventional parametric option pricing. The proposed semiparametric models are developed to incorporate the transaction costs rate factor in the intermediated model-free framework to assure realistic pricing of options. The main focus of this study is to document by simulation that the EGL models deliver option pricing outperformance compared to the benchmark model. The simulation of the EGL models is conducted to investigate whether the proposed models are practical to be applied in a real financial system. Superior option pricing accuracy was observed in the EGL models based on the simulation results. This finding is grounded on the RMSE values as well on pairwise percentage difference values.
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