Molecular and biological characterisation of orthobunyaviruses

Orthobunyaviruses are the largest genus within the Bunyaviridae family, with over 170 named viruses classified into 18 serogroups (Elliott and Blakqori, 2001; Plyusnin et al., 2012). Orthobunyaviruses are transmitted by arthropods and have a tripartite negative sense RNA genome, which encodes 4 structural proteins and 2 non-structural proteins. The non-structural protein NSs is the primary virulence factor of orthobunyaviruses and potent antagonist of the type I interferon (IFN) response. However, sequencing studies have identified pathogenic viruses that lack the NSs protein (Mohamed et al., 2009; Gauci et al., 2010). The work presented in this thesis describes the molecular and biological characterisation of divergent orthobunyaviruses. Data on plaque morphology, growth kinetics, protein profiles, sensitivity to IFN and activation of the type I IFN system are presented for viruses in the Anopheles A, Anopheles B, Capim, Gamboa, Guama, Minatitlan, Nyando, Tete and Turlock serogroups. These are complemented with complete genome sequencing and phylogenetic analysis. Low activation of IFN by Tete serogroup viruses, which naturally lack an NSs protein, was also further investigated by the development of a reverse genetics system for Batama virus (BMAV). Recombinant viruses with mutations in the virus nucleocapsid protein amino terminus showed higher activation of type I IFN in vitro and data suggests that low levels of IFN are due to lower activation rather than active antagonism. The anti-orthobunyavirus activity of IFN-stimulated genes IFI44, IFITMs and human and ovine BST2 were also studied, revealing that activity varies not only within the orthobunyavirus genus and virus serogroups but also within virus species. Furthermore, there was evidence of active antagonism of the type I IFN response and ISGs by non-NSs viruses. In summary, the results show that pathogenicity in man and antagonism of the type I IFN response in vitro cannot be predicted by the presence, or absence, of an NSs ORF. They also highlight problems in orthobunyavirus classification with discordance between classical antigen based data and phylogenetic analysis.

Pricing derivatives with stochastic volatility

This Ph.D. thesis contains 4 essays in mathematical finance with a focus on pricing Asian option (Chapter 4), pricing futures and futures option (Chapter 5 and Chapter 6) and time dependent volatility in futures option (Chapter 7). In Chapter 4, the applicability of the Albrecher et al.(2005)'s comonotonicity approach was investigated in the context of various benchmark models for equities and com- modities. Instead of classical Levy models as in Albrecher et al.(2005), the focus is the Heston stochastic volatility model, the constant elasticity of variance (CEV) model and the Schwartz (1997) two-factor model. It is shown that the method delivers rather tight upper bounds for the prices of Asian Options in these models and as a by-product delivers super-hedging strategies which can be easily implemented. In Chapter 5, two types of three-factor models were studied to give the value of com- modities futures contracts, which allow volatility to be stochastic. Both these two models have closed-form solutions for futures contracts price. However, it is shown that Model 2 is better than Model 1 theoretically and also performs very well empiri- cally. Moreover, Model 2 can easily be implemented in practice. In comparison to the Schwartz (1997) two-factor model, it is shown that Model 2 has its unique advantages; hence, it is also a good choice to price the value of commodity futures contracts. Fur- thermore, if these two models are used at the same time, a more accurate price for commodity futures contracts can be obtained in most situations. In Chapter 6, the applicability of the asymptotic approach developed in Fouque et al.(2000b) was investigated for pricing commodity futures options in a Schwartz (1997) multi-factor model, featuring both stochastic convenience yield and stochastic volatility. It is shown that the zero-order term in the expansion coincides with the Schwartz (1997) two-factor term, with averaged volatility, and an explicit expression for the first-order correction term is provided. With empirical data from the natural gas futures market, it is also demonstrated that a significantly better calibration can be achieved by using the correction term as compared to the standard Schwartz (1997) two-factor expression, at virtually no extra effort. In Chapter 7, a new pricing formula is derived for futures options in the Schwartz (1997) two-factor model with time dependent spot volatility. The pricing formula can also be used to find the result of the time dependent spot volatility with futures options prices in the market. Furthermore, the limitations of the method that is used to find the time dependent spot volatility will be explained, and it is also shown how to make sure of its accuracy.