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Interest-rate models: an extension to the usage in the energy market and pricing exotic energy derivatives.
File | Description | Size | Format | |
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Wang-D-2009-PhD-Thesis.pdf | 1.78 MB | Adobe PDF | View/Open |
Title: | Interest-rate models: an extension to the usage in the energy market and pricing exotic energy derivatives. |
Authors: | Wang, Dan |
Item Type: | Thesis or dissertation |
Abstract: | In this thesis, we review various popular pricing models in the interest-rate market. Among these pricing models, we choose the LIBOR Market model (LMM) as the benchmark model. Based on market practice experience, we also develop a pricing model named the “Market volatility model”. By pricing vanilla interest-rate options such as interest-rate caps and swaptions, we compare the performance of our Market volatility model to that of the LMM. It is proved that the Market Volatility model produce comparable results to the LMM, while its computing efficiency largely exceeds that of the LMM. Following the recent rapid development in the commodity market, in particular the energy market, we attempt to extend the use of our proposed Market volatility model from the interest-rate market to the energy market. We prove that the Market Volatility model is capable of pricing various energy derivative under the assumption of absence of the convenience yield. In addition, we propose a new type of exotic energy derivative which has a flexible option structure. This energy derivative is named as the Flex-Asian spread options (FASO). We give examples of different option structures within the FASO framework and use the Market volatility model to generate option prices and greeks for each structure. Although the Market volatility model can be used to price various energy derivatives based on oil/gas contracts, it is not compatible with the structure of one of the most advanced derivatives in the energy market, the storage option. We modify the existing pricing model for storage options and use our own 3D-binomial tree approach to price gas storage contracts. By doing these, we improve the performance of the traditional storage model. |
Issue Date: | May-2009 |
Date Awarded: | Mar-2010 |
URI: | http://hdl.handle.net/10044/1/5583 |
DOI: | https://doi.org/10.25560/5583 |
Supervisor: | Meade, Nigel |
Author: | Wang, Dan |
Department: | Imperial College Business School |
Publisher: | Imperial College London |
Qualification Level: | Doctoral |
Qualification Name: | Doctor of Philosophy (PhD) |
Appears in Collections: | Imperial College Business School PhD theses |