56 research outputs found
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Pricing of reinsurance contracts in the presence of catastrophe bonds
A methodology for pricing of reinsurance contracts in the presence of a catastrophe bond is developed. An important advantage of this approach is that it allows for the pricing of reinsurance contracts consistent with the observed market prices of catastrophe bonds on the same underlying risk process. Within the proposed methodology, an appropriate financial pricing formula is derived, under a market implied risk neutral probability measure for both a catastrophe bond and an aggregate excess of loss reinsurance contract, using a generalised Fourier transform. Efficient numerical methods for the evaluation of this formula, such as the Fast Fourier transform and Fractional Fast Fourier transform, are considered. The methodology is illustrated on several examples including Pareto and Gamma claim severities
Statistical Modeling of Solar Flare Activity from Empirical Time Series of Soft X-ray Solar Emission
A time series of soft X-ray emission observed on 1974-2007 years (GOES) is
analyzed. We show that in the periods of high solar activity 1977-1981,
1988-1992, 1999-2003 the energy statistics of soft X-ray solar flares for class
M and C is well described by a FARIMA time series with Pareto innovations. The
model is characterized by two effects. One of them is a long-range dependence
(long-term memory), and another corresponds to heavy-tailed distributions.
Their parameters are statistically stable enough during the periods. However,
when the solar activity tends to minimum, they change essentially. We discuss
possible causes of this evolution and suggest a statistical model for
predicting the flare energy statistics.Comment: 21 pages, 7 figure
Mean first-passage times of non-Markovian random walkers in confinement
The first-passage time (FPT), defined as the time a random walker takes to
reach a target point in a confining domain, is a key quantity in the theory of
stochastic processes. Its importance comes from its crucial role to quantify
the efficiency of processes as varied as diffusion-limited reactions, target
search processes or spreading of diseases. Most methods to determine the FPT
properties in confined domains have been limited to Markovian (memoryless)
processes. However, as soon as the random walker interacts with its
environment, memory effects can not be neglected. Examples of non Markovian
dynamics include single-file diffusion in narrow channels or the motion of a
tracer particle either attached to a polymeric chain or diffusing in simple or
complex fluids such as nematics \cite{turiv2013effect}, dense soft colloids or
viscoelastic solution. Here, we introduce an analytical approach to calculate,
in the limit of a large confining volume, the mean FPT of a Gaussian
non-Markovian random walker to a target point. The non-Markovian features of
the dynamics are encompassed by determining the statistical properties of the
trajectory of the random walker in the future of the first-passage event, which
are shown to govern the FPT kinetics.This analysis is applicable to a broad
range of stochastic processes, possibly correlated at long-times. Our
theoretical predictions are confirmed by numerical simulations for several
examples of non-Markovian processes including the emblematic case of the
Fractional Brownian Motion in one or higher dimensions. These results show, on
the basis of Gaussian processes, the importance of memory effects in
first-passage statistics of non-Markovian random walkers in confinement.Comment: Submitted version. Supplementary Information can be found on the
Nature website :
http://www.nature.com/nature/journal/v534/n7607/full/nature18272.htm
Single-molecule imaging reveals receptor-G protein interactions at cell surface hot spots
G-protein-coupled receptors mediate the biological effects of many hormones and neurotransmitters and are important pharmacological targets. They transmit their signals to the cell interior by interacting with G proteins. However, it is unclear how receptors and G proteins meet, interact and couple. Here we analyse the concerted motion of G-protein-coupled receptors and G proteins on the plasma membrane and provide a quantitative model that reveals the key factors that underlie the high spatiotemporal complexity of their interactions. Using two-colour, single-molecule imaging we visualize interactions between individual receptors and G proteins at the surface of living cells. Under basal conditions, receptors and G proteins form activity-dependent complexes that last for around one second. Agonists specifically regulate the kinetics of receptor-G protein interactions, mainly by increasing their association rate. We find hot spots on the plasma membrane, at least partially defined by the cytoskeleton and clathrin-coated pits, in which receptors and G proteins are confined and preferentially couple. Imaging with the nanobody Nb37 suggests that signalling by G-protein-coupled receptors occurs preferentially at these hot spots. These findings shed new light on the dynamic interactions that control G-protein-coupled receptor signalling
Modelling catastrophe claims with left-truncated severity distributions
Natural catastrophe, Property insurance, Loss distribution, Truncated data, Ruin probability,
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