Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory

Good estimates for the tails of loss severity distributions are essential for pricing or positioning high-excess loss layers in reinsurance. We describe parametric curve-fitting methods for modelling extreme historical losses. These methods revolve around the generalized Pareto distribution and are supported by extreme value theory. We summarize relevant theoretical results and provide an extensive example of their application to Danish data on large fire insurance losse

Magnetic Anomaly Absolute Positioning for Hypersonic Aircraft

GPS has proven to be an extremely valuable asset for navigation, and timing. GPS has become the standard navigation system for all applications, but GPS has limitations. GPS is susceptible to jamming, spoofing, and in the case of hypersonic aircraft, is likely unavailable. When an aircraft is traveling at hypersonic speeds, there is a plasma sheath that surrounds the aircraft. This plasma sheath blocks electromagnetic waves, and is therefore responsible for a GPS blackout. GPS unavailability for hypersonic aircraft has prompted the research into the viability of alternate navigation systems for these aircraft. This paper seeks to explore the viability of MagNav for hypersonic aircraft. Hypersonic aircraft present new challenges for MagNav including: high altitudes, high speeds, large scale map availability, and new noise sources. This paper explores these challenges to determine if any poses an insurmountable problem. Simulations are conducted to explore the potential performance of MagNav on a hypersonic vehicle. These simulations conclude that MagNav is viable on a hypersonic aircraft

Modelling the liquidity premium on corporate bonds

AbstractThe liquidity premium on corporate bonds has been high on the agenda of Solvency regulators owing to its potential relationship to an additional discount factor on long-dated insurance liabilities. We analyse components of the credit spread as a function of standard bond characteristics during 2003–2014 on a daily basis by regression analyses, after introducing a new liquidity proxy. We derive daily distributions of illiquidity contributions to the credit spread at the individual bond level and find that liquidity premia were close to zero just before the financial crisis. We observe the time-varying nature of liquidity premia as well as a widening in the daily distribution in the years after the credit crunch. We find evidence to support higher liquidity premia, on average, on bonds of lower credit quality. The evolution of model parameters is economically intuitive and brings additional insight into investors’ behaviour. The frequent and bond-level estimation of liquidity premia, combined with few data restrictions makes the approach suitable for ALM modelling, especially when future work is directed towards arriving at forward-looking estimates at both the aggregate and bond-specific level.</jats:p

Developing three dimensional models of breast cancer

BACKGROUND AND AIMS Breast cancer is a leading cause of female mortality in the Western world. It is well established that the spread of breast cancer, first locally and later distally, is the major factor in patient prognosis. Experimental systems of breast cancer rely on cell lines usually derived from primary tumours or pleural effusions. Two major obstacles hinder this research: (i) Some known sub-types of breast cancers are not represented within current cell line collections; (ii) the influence of the tumour microenvironment is not usually taken into account.EXPERIMENTAL DESIGN We developed a three-dimensional assay prepared from freshly harvested breast cancer tissue embedded in soft rat collagen I cushions. Invasive behaviour and tumour response to tamoxifen therapy was measured. Changes in proliferation, apoptosis and tumour volume in response to tamoxifen treatment were quantified using image analysis software and optical projection tomography. Further cell line based experiments and histopathological analysis of resection specimens were subsequently investigated to investigate the role of EGFR signalling pathways in driving invasion.RESULTS We demonstrate a technique to culture primary breast cancer specimens of all sub-types. Within 2-3 weeks, individual and collective invasion of epithelial cells into the surrounding collagen I was observed using phase contrast light microscopy and histopathological methods. Addition of tamoxifen to preparations derived from ER+ tumours demonstrated a range of response as measured by proliferative and apoptotic markers and significant reduction in tumour volume not seen in ER- specimens. Changes in tumour volume allowed stratification into responsive and nonresponsive tumours. EGF within the culture medium appeared to drive a change in phenotype from ER+ to triple negative phenotype and acted as a driver for epithelial invasiveness.CONCLUSION Here, we developed an assay to culture human breast tumours without sub-type bias and to investigate and quantify the spread of these ex vivo. This method could be used to quantify drug sensitivity in primary cancers under conditions closer to real life. This may provide a more predictive model than currently used cell lines

Common Poisson Shock Models: Applications to Insurance and Credit Risk Modelling

The idea of using common Poisson shock processes to model dependent event frequencies is well known in the reliability literature. In this paper we examine these models in the context of insurance loss modelling and credit risk modelling. To do this we set up a very general common shock framework for losses of a number of different types that allows for both dependence in loss frequencies across types and dependence in loss severities. Our aims are threefold: to demonstrate that the common shock model is a very natural way of approaching the modelling of dependent losses in an insurance or risk management context; to provide a summary of some analytical results concerning the nature of the dependence implied by the common shock specification; to examine the aggregate loss distribution that results from the model and its sensitivity to the specification of the model parameter