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Title: Disruption risks and robust investment strategies in petroleum markets
Author: Katata, Kabir
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2011
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This thesis is concerned with supply disruption risks and robust investment strategies in petroleum markets. We study two research areas: modelling oil and gas supply disruption risks, and robust portfolio management in financial and petroleum markets under supply disruption. Petroleum supply disruptions are persistent and financially catastrophic. Quantitative modelling of supply disruption risks is essential for energy market participants. We model petroleum supply disruptions using extreme value theory (EVT) and copula. Using EVT, we describe univariate oil and gas supply disruptions in terms of volumetric and financial losses. Copula functions are used to model the multivariate dependence between the supply disruptions. Our empirical results indicate that multivariate financial losses exhibit stronger positive dependence than multivariate volumetric losses. Portfolio management under uncertainty has been the central topic of extensive research in finance. Single and multi-period asset allocation models have been developed under several assumptions on the underlying price dynamics. It is well known that statistical measurements do not unfold the complete dynamics of the market, and inherently involve estimation errors. Robust optimization has been introduced to reduce perturbations arising in estimations of random parameters. Within the robust optimization framework, we first study the single period Markowitz mean-variance portfolio allocation problem under discrete assets choice constraints. Special emphasis is placed on worst-case robust optimal strategies which yield reduction on discontinuity with guaranteed performance. We are also concerned with robust investment strategies in petroleum markets. We formulate three different but related problems in context of portfolio management within energy markets. The first model considers standard energy trading strategies using futures contracts under price and demand uncertainty while the second one uses swap contracts under price uncertainty for hedging purposes. The last model integrates energy and weather derivatives for hedging price and weather uncertainties in petroleum markets. A tractable robust approach to the portfolio allocation problems is proposed to reduce parameter estimation errors arising in stochastic price and demand processes as well as supply disruption and weather uncertainties. The robust counterpart of the underlying problem involves worst-case outcome of the stochastic data in terms of spot price, demand or temperature within the uncertainty sets. We investigate modelling implications of symmetric and asymmetric uncertainty sets and analyze the impact of parameter estimation error within the portfolio allocation problems.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: HD Industries. Land use. Labor ; HG Finance