DH 1st floor SR

Large-scale zonal jets are observed in a wide range of geophysical and astrophysical flows; most strikingly in the atmospheres of the Jovian gas giant planets. Jupiter's upper atmosphere is highly turbulent, with many small vortices, and strong westerly winds at the equator. We consider the thermal shallow water equations as a model for Jupiter's upper atmosphere. Originally proposed for the terrestrial atmosphere and tropical oceans, this model extends the conventional shallow water equations by allowing horizontal temperature variations with a modified Newtonian cooling for the temperature field. We perform numerical simulations that reproduce many of the key features of Jupiter’s upper atmosphere. However, the simulations take a long time to run because their time step is severely constrained by the inertia-gravity wave speed. We filter out the inertia-gravity waves by forming the quasigeostrophic limit, which describes the rapidly rotating (small Rossby number) regime. We also show that the quasigeostrophic energy equation is the quasigeostrophic limit of the thermal shallow water pseudo-energy equation, analogous to the derivation of the acoustic energy equation from gas dynamics. We perform numerical simulations of the quasigeostrophic equations, which again reproduce many of the key features of Jupiter’s upper atmosphere. We gain substantial performance increases by running these simulations on graphical processing units (GPUs).

 Determining the price at which to conduct a trade is an age-old problem. The first (albeit primitive) pricing mechanism dates back to the Neolithic era, when people met in physical proximity in order to agree upon mutually beneficial exchanges of goods and services, and over time increasingly complex mechanisms have played a role in determining prices. In the highly competitive and relentlessly fast-paced markets of today’s financial world, it is the limit order book that matches buyers and sellers to trade at an agreed price in more than half of the world’s markets.  In this talk I will describe the limit order book trade-matching mechanism, and explain how the extra flexibility it provides has vastly impacted the problem of how a market participant should optimally behave in a given set of circumstances.

Quantile forecasting of wind power using variability indices
Abstract: Wind power forecasting techniques have received substantial attention recently due to the increasing penetration of wind energy in national power systems.  While the initial focus has been on point forecasts, the need to quantify forecast uncertainty and communicate the risk of extreme ramp events has led to an interest in producing probabilistic forecasts. Using four years of wind power data from three wind farms in Denmark, we develop quantile regression models to generate short-term probabilistic forecasts from 15 minutes up to six hours ahead. More specifically, we investigate the potential of using various variability indices as explanatory variables in order to include the influence of changing weather regimes. These indices are extracted from the same  wind power series and optimized specifically for each quantile. The forecasting performance of this approach is compared with that of some benchmark models. Our results demonstrate that variability indices can increase the overall skill of the forecasts and that the level of improvement depends on the specific quantile.

The displacement of a liquid by an air finger is a generic two-phase flow that

underpins applications as diverse as microfluidics, thin-film coating, enhanced

oil recovery, and biomechanics of the lungs. I will present two intriguing

examples of such flows where, firstly, oscillations in the shape of propagating

bubbles are induced by a simple change in tube geometry, and secondly, flexible

vessel boundaries suppress viscous fingering instability.

1) A simple change in pore geometry can radically alter the behaviour of a

fluid displacing air finger, indicating that models based on idealized pore

geometries fail to capture key features of complex practical flows. In

particular, partial occlusion of a rectangular cross-section can force a

transition from a steadily-propagating centred finger to a state that exhibits

spatial oscillations via periodic sideways motion of the interface at a fixed

location behind the finger tip. We characterize the dynamics of the

oscillations and show that they arise from a global homoclinic connection

between the stable and unstable manifolds of a steady, symmetry-broken

solution.

2) Growth of complex dendritic fingers at the interface of air and a viscous

fluid in the narrow gap between two parallel plates is an archetypical problem

of pattern formation. We find a surprisingly effective means of suppressing

this instability by replacing one of the plates with an elastic membrane. The

resulting fluid-structure interaction fundamentally alters the interfacial

patterns that develop and considerably delays the onset of fingering. We

analyse the dependence of the instability on the parameters of the system and

present scaling arguments to explain the experimentally observed behaviour.

We provide a general construction of time-consistent sublinear expectations on the space of continuous paths. In particular, we construct the conditional G-expectation of a Borel-measurable (rather than quasi-continuous) random variable.

The use of gain-loss ratio as a measure of attractiveness has been

introduced by Bernardo and Ledoit. In their well-known paper, they

show that gain-loss ratio restrictions have a dual representation in

terms of restricted pricing kernels.

In spite of its clear financial significance, gain-loss ratio has

been largely ignored in the mathematical finance literature, with few

exceptions (Cherny and Madan, Pinar). The main reason is intrinsic

lack of good mathematical properties. This paper aims to be a

rigorous study of gain-loss ratio and its dual representations

in a continuous-time market setting, placing it in the context of

risk measures and acceptability indexes. We also point out (and

correctly reformulate) an erroneous statement made by Bernardo and

Ledoit in their main result. This is joint work with M. Pinar.

Algorithmic trade execution has become a standard technique

for institutional market players in recent years,

particularly in the equity market where electronic

trading is most prevalent. A trade execution algorithm

typically seeks to execute a trade decision optimally

upon receiving inputs from a human trader.

A common form of optimality criterion seeks to

strike a balance between minimizing pricing impact and

minimizing timing risk. For example, in the case of

selling a large number of shares, a fast liquidation will

cause the share price to drop, whereas a slow liquidation

will expose the seller to timing risk due to the

stochastic nature of the share price.

We compare optimal liquidation policies in continuous time in

the presence of trading impact using numerical solutions of

Hamilton Jacobi Bellman (HJB)partial differential equations

(PDE). In particular, we compare the time-consistent

mean-quadratic-variation strategy (Almgren and Chriss) with the

time-inconsistent (pre-commitment) mean-variance strategy.

The Almgren and Chriss strategy should be viewed as the

industry standard.

We show that the two different risk measures lead to very different

strategies and liquidation profiles.

In terms of the mean variance efficient frontier, the

original Almgren/Chriss strategy is signficently sub-optimal

compared to the (pre-commitment) mean-variance strategy.

This is joint work with Stephen Tse, Heath Windcliff and

Shannon Kennedy.

We will first motivate and review some implicit schemes that arises from the discretization of non linear PDEs in finance or in optimal control problems - when using finite differences methods or finite element methods.

For the american option problem, we are led to compute the solution of a discrete obstacle problem, and will give some results for the convergence of nonsmooth Newton's method for solving such problems.

Implicit schemes are interesting for their stability properties, however they can be too costly in practice.

We will then present some novel schemes and ideas, based on the semi-lagrangian approach and on discontinuous galerkin methods, trying to be as much explicit as possible in order to gain practical efficiency.

We consider the pricing of a maturity guarantee, which is equivalent to the pricing of a European put option, in a regime-switching market model. Regime-switching market models have been empirically shown to fit long-term stockmarket data better than many other models. However, since a regime-switching market is incomplete, there is no unique price for the maturity guarantee. We extend the good-deal pricing bounds idea to the regime-switching market model. This allows us to obtain a reasonable range of prices for the maturity guarantee, by excluding those prices which imply a Sharpe Ratio which is too high. The range of prices can be used as a plausibility check on the chosen price of a maturity guarantee.