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Option Pricing and Hedging under Realistic Market Conditions


Denzel Voesenek

Master Thesis, FS 12 (10154)

An innovative option pricing and hedging framework is presented in this master thesis. This Model Predictive Control (MPC) based framework relies on the well known risk measure Conditional Value at Risk (CVaR) and data modelling techniques such as Threshold Autore- gressive Conditional Heteroskedasticity (TARCH) and Filtered Historical Simulations (FHS). This framework is applied in order to price and hedge not only simple European Call op- tions, but also more complicated exotic options such as Barrier options. Extentions which include transaction costs and terminal weight conditions are also proposed. Futhermore, the flexibility of the proposed framework is shown by solving the problem of Portfolio Insurance, in which an investor aims at limiting his downside risk. Both applications are thoroughly benchmarked against peers used by practitioners. This thesis suggests that the proposed MPC based framework with seperated asset scenario generation for pricing and hedging of derivatives and structured products gives consistent performance when compared against peers, while additionally allowing the pricing and hedging of far more complex financial prod- ucts. Furthermore, assumptions on trading costs, continious trading, Brownian motion data and constant volatility can be relaxed. Key words: option pricing, option hedging, Threshold Autoregressive Conditional Heteroskedastic- ity (TARCH), Filtered Historical Simulations (FHS), Conditional Value at Risk (CVaR), Portfolio Insurance, Model Predictive Control (MPC) Master


Type of Publication:

(12)Diploma/Master Thesis

J. Lygeros

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2013:IFA_4361
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