A sunburnt country – storms, surges and sea levels : of insurance and flooding rains

Increasing population pressures and life-style choices are resulting in more people living in areas that are at risk of inundation from rising sea levels and flooding. However, following natural disaster events, such as the 2011 Queensland floods, many Australians discovered they were uninsured. Either their insurance policies did not cover flood; or multiple (and confusing) water-related definitions led them to believe they had cover when they did not. Several theories are analysed to try to explain what is a world-wide underinsurance problem but these do not provide an answer to the problem. This research focuses on uncovering the reasons consumers fail to adequately insure for flood and other water-related events. Recent Australian legislative attempts to overcome insureds’ confusion of water related definitions are examined for this purpose. The authors conclude that Australian and other) legislators should set a maximum premium for a minimum amount of flood and sea related cover; and restrict the building and style of homes in flood prone areas.

Estimating the parameters of stochastic volatility models using option price data

This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.