Past Mathematical and Computational Finance Internal Seminar

Traditional diffusion models for random phenomena have paths with Holder

regularity just greater than 1/2 almost surely but there are situations

arising in finance and telecommunications where it is natural to look

for models in which the Holder regularity of the paths can vary.

Such processes are called multifractal and we will construct a class of

such processes on R using ideas from branching processes.

Using connections with multitype branching random walk we will be able

to compute the multifractal spectrum which captures the variability in

the Holder regularity. In addition, if we observe one of our processes

at a fixed resolution then we obtain a finite Markov representation,

which allows efficient simulation.

As an application, we fit the model to some AUD-USD exchange rate data.

Joint work with Geoffrey Decrouez and Ben Hambly

The question of how to derive useful bounds on

arbitrage-free prices of exotic options given only prices of liquidly

traded products like European call und put options has received much

interest in recent years. It also led to new insights about classic

problems in probability theory like the Skorokhod embedding problem. I

will take this as a starting point and show how this progress can be

used to give new results on general Monte-Carlo schemes.

I explore some new ideas on embedding problems for Brownian motion (and other Markov processes). I show how a (forward) Skorokhod embedding problem is transformed into an optimal stopping problem for the time-reversed process (Markov process in duality). This is deduced from the PDE (Variational Inequalities) interpretation of the classical results but then shown using probabilistic techniques and extended to give an n-marginal Root embedding. I also discuss briefly how to extend the approach to other embeddings such as the Azema-Yor embedding.

The aim of this lecture is to give a general introduction to

the interacting particle system and applications in finance, especially

in the pricing of American options. We survey the main techniques and

results on Snell envelope, and provide a general framework to analyse

these numerical methods. New algorithms are introduced and analysed

theoretically and numerically.

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We consider the pricing of American put options in a model-independent setting: that is, we do not assume that asset prices behave according to a given model, but aim to draw conclusions that hold in any model. We incorporate market information by supposing that the prices of European options are known. In this setting, we are able to provide conditions on the American Put prices which are necessary for the absence of arbitrage. Moreover, if we further assume that there are finitely many European and American options traded, then we are able to show that these conditions are also sufficient. To show sufficiency, we construct a model under which both American and European options are correctly priced at all strikes simultaneously. In particular, we need to carefully consider the optimal stopping strategy in the construction of our process. (Joint with Christoph Hoeggerl).

\textbf{Victor Fedyashov} \newline

\textbf{Title:} Ergodic BSDEs with jumps \newline

\textbf{Abstract:} We study ergodic backward stochastic differential equations (EBSDEs) with jumps, where the forward dynamics are given by a non-autonomous (time-periodic coefficients) Ornstein-Uhlenbeck process with Lévy noise on a separable Hilbert space. We use coupling arguments to establish existence of a solution. We also prove uniqueness of the Markovian solution under certain growth conditions using recurrence of the above mentioned forward SDE. We then give applications of this theory to problems of risk-averse ergodic optimal control.

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\textbf{Ruolong Chen} \newline

\textbf{Title:} tba \newline

\textbf{Abstract:}

\textbf{James Newbury} \newline

Title: Heavy traffic diffusion approximation of the limit order book in a one-sided reduced-form model. \newline

Abstract: Motivated by a zero-intelligence approach, we try to capture the

dynamics of the best bid (or best ask) queue in a heavy traffic setting,

i.e when orders and cancellations are submitted at very high frequency.

We first prove the weak convergence of the discrete-space best bid/ask

queue to a jump-diffusion process. We then identify the limiting process

as a regenerative elastic Brownian motion with drift and random jumps to

the origin.

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\textbf{Zhaoxu Hou} \newline

Title: Robust Framework In Finance: Martingale Optimal Transport and

Robust Hedging For Multiple Marginals In Continuous Time

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Abstract: It is proved by Dolinsky and Soner that there is no duality

gap between the robust hedging of path-dependent European Options and a

martingale optimal problem for one marginal case. Motivated by their

work and Mykland's idea of adding a prediction set of paths (i.e.

super-replication of a contingent claim only required for paths falling

in the prediction set), we try to achieve the same type of duality

result in the setting of multiple marginals and a path constraint.

Wei Wei

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Title: "Optimal Switching at Poisson Random Intervention Times"

(joint work with Dr Gechun Liang)

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Abstract: The paper introduces a new class of optimal switching problems, where

the player is allowed to switch at a sequence of exogenous Poisson

arrival times, and the underlying switching system is governed by an

infinite horizon backward stochastic differential equation system. The

value function and the optimal switching strategy are characterized by

the solution of the underlying switching system. In a Markovian setting,

the paper gives a complete description of the structure of switching

regions by means of the comparison principle.

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Julen Rotaetxe

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Title: Applicability of interpolation based finite difference method to problems in finance

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Abstract:

I will present the joint work with Christoph Reisinger on

the applicability of a numerical scheme relying on finite differences

and monotone interpolation to discretize linear and non-linear diffusion

equations. We propose suitable transformations to the process modeling

the underlying variable in order to overcome issues stemming from the

width of the stencil near the boundaries of the discrete spatial domain.

Numerical results would be given for typical diffusion models used in

finance in both the linear and non-linear setting.

More than half of the world's financial markets use a limit order book

mechanism to facilitate trade. For markets where trade is conducted

through a central counterparty, trading platforms disseminate the same

information about the limit order book to all market participants in

real time, and all market participants are able to trade with all

others. By contrast, in markets that operate under bilateral trade

agreements, market participants are only able to view the limit order

book activity from their bilateral trading partners, and are unable to

trade with the market participants with whom they do not possess a

bilateral trade agreement. In this talk, I discuss the implications

of such a market structure for price formation. I then introduce a

simple model of such a market, which is able to reproduce several

important empirical properties of traded price series. By identifying and

matching several robust moment conditions to the empirical data, I make

model-based inference about the network of bilateral trade partnerships

in the market. I discuss the implications of these findings for market

stability and suggest how the regulator might improve market conditions

by implementing simple restrictions on how market participants form their

bilateral trade agreements.

The aim of this lecture is to give a general introduction to

the interacting particle system and applications in finance, especially

in the pricing of American options. We survey the main techniques and

results on Snell envelope, and provide a general framework to analyse

these numerical methods. New algorithms are introduced and analysed

theoretically and numerically.

I will look at a toy model for an index in a large market. The aim is to

consider the pricing of volatility swaps on the index. This is very much

work in progress.

In this talk, We show that both reflected BSDE and its associated penalized BSDE admit both optimal stopping representation and optimal control

representation. We also show that both multidimensional reflected BSDE and its associated multidimensional penalized BSDE admit optimal switching representation. The corresponding optimal stopping problems for penalized BSDE have the feature that one is only allowed to stop at Poisson arrival times.

We consider the problem of optimizing a portfolio of medium to low frequency

quant strategies under heavy tailed distributions. Approaching this problem by modelling

returns through mixture distributions, we derive robust and relative robust methodologies

and discuss conic optimization approaches to solving these models.

The second order sensitivity of a trading position, the so

called gamma, has a very real and intuitive meaning to the traders.

People think that convex payoffs must generate convex prices. Being long

or short of gamma is a strategy used to balance risks in options books.

While the simples models, like Black Scholes, are consistent with this

intuition other popular models used in the industry are not. I will give

examples of simple and popular models which do not always convert a

convex payoff into a convex price. I will also give the necessary and

sufficient conditions under which the convexity is propagated.

We consider a problem of maximising lifetime utility of consumption subject to a drawdown constraint on undiscounted wealth

process. This problem was solved by Elie and Touzi in the case of zero interest rate. We apply methodology of Azema-Yor processes to connect

constrained and unconstrained wealth processes, which allows us to get the results for non-zero interest rate.

General Arrow-Debreu equilibrium can be determined for expected utility maximisers by explicit solutions for individual players. When the expected

utilities are distorted by probability weighting functions, players cannot find explicit optimal decisions. Zhou and Xia studied the existence of equilibrium when the probability weighting functions are the same for all individual players. In this paper, we investigate the same problem but with heterogeneous probability weighting function.

This paper analyzes a generalized class of flat-top realized kernels for

estimation of the quadratic variation spectrum in the presence of a

market microstructure noise component that is allowed to exhibit both

endogenous and exogenous $\alpha$-mixing dependence with polynomially

decaying autocovariances. In the absence of jumps, the class of flat-top

estimators are shown to be consistent, asymptotically unbiased, and

mixed Gaussian with the optimal rate of convergence, $n^{1/4}$. Exact

bounds on lower order terms are obtained using maximal inequalities and

these are used to derive a conservative MSE-optimal flat-top shrinkage.

In a theoretical and/or a numerical comparison with alternative

estimators, including the realized kernel, the two-scale realized

kernel, and a proposed robust pre-averaging estimator, the flat-top

realized kernels are shown to have superior bias reduction properties

with little or no increase in finite sample variance.

No Seminar this week

Our starting point is a recent characterisation of one-dimensional, time-homogeneous diffusion in terms of its distribution at an exponential time. The structure of this characterisation leads naturally to the idea of measuring `how far' a diffusion is away from being a martingale diffusion in terms of expected local time at the starting point. This work in progress has a connection to finance and to

a Skorokhod embedding.

A number of pricing models for electricity and carbon credit pricing involve nonlinear dependencies between two, or more, of the processes involved; for example, the models developed by Schwarz and Howison. The consequences of these nonlinearities are not well understood.

In this talk I will discuss some much simpler models, namely options whose values are defined self-referentially, which have been looked at in order to better understand the effects of these non-linear dependencies.

Market impact, leverage, systemic risk, and the perils of mark-to-market accounting

Market impact is the price change associated with new buy or sell orders entering the market. It provides a useful alternative to thinking in terms of supply and demand for several reasons, the most important being that there is theoretical and empirical evidence that it follows a universal law. Understanding market impact is essential for adjusting investment size, for optimizing execution tactics, and provides a useful tool for understanding market ecology and systemic risk. I will present a new method for impact-adjusted accounting, and show how it can avoid the serious problems of marking-to-market when leverage is used. Then I will discuss how market impact can be combined with network theory to understand the problem of overlapping portfolios and market crowding. Since I am a new faculty member, at the beginning of the talk I will say a bit about my interests and current projects.

We will discuss numerical solutions of Multi-objective Control problems governed by partial differential equations. More precisely, we will look for Nash Equilibria, which are solutions to non-cooperative differential games. First we will study the continuous case. Then, in order to compute solutions, we will combine finite difference schemes for the time discretization, finite element methods for the space discretization and a conjugate gradient algorithm (or other suitable alternative) for the iterative solution of the discrete differential game. Finally, we will apply this methodology to the solution of several test problems.

Speaker: Tigran Atoyan\\

Title: A revised approach to hedging and pricing\\

Abstract:\\

After a brief review of the classical option pricing framework, we present a motivating example on the evaluation of hedging P&L using a simplistic strategy which does very well in practice. We then present preliminary results about a relatively unknown approach called business time hedging. Some applications of the latter approach to pricing certain derivative products as well as future research directions in this topic are discussed.\\

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Speaker: Sean Ledger\\

Title: Stochastic Evolution Equations in Portfolio Credit Modelling\\

Abstract:\\

I shall present an infinite-dimension structural model for a large portfolio of credit risky assets. As the number of assets approaches infinity we obtain a limiting system with a density process. I shall outline the properties of this density process and how one can use the SPDE satisfied by this process to estimate the loss function of the portfolio. Extensions to the model shall be onsidered, including contagion effects and Lévy noise. Finally I shall present some of the numerical testing for these models.\\

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Speaker: Peter Spoida\\

Title: Robust Pricing and Hedging of the Barrier Option with a Finite Number of Intermediate Law Constraints\\

Abstract:\\

We propose a robust superhedging strategy for simple barrier options, consisting of a portfolio of calls with different maturities and a self-financing trading strategy. The superhedging strategy is derived from a pathwise inequality. We illustrate how a stochastic control ansatz can provide a good guess for finding such strategies. By constructing a worst-case model, we demonstrate that this superhedge is the cheapest possible. Our construction generalizes the Skorokhod embedding obtained by Brown, Hobson and Rogers (2001). The talk is based on joint work with Pierre Henry-Labordere, Jan Obloj and Nizar Touzi.

I will discuss methods for spatio-temporal modelling in cellular and molecular biology. Three classes of models will be considered: (i) microscopic (molecular-based, individual-based) models which are based on the simulation of trajectories of individual molecules and their localized interactions (for example, reactions); (ii) mesoscopic (lattice-based) models which divide the computational

domain into a finite number of compartments and simulate the time evolution of the numbers of molecules in each compartment; and (iii) macroscopic (deterministic) models which are written in terms of reaction-diffusion-advection PDEs for spatially varying concentrations. In the first part of my talk, I will discuss connections between the modelling frameworks (i)-(iii). I will consider chemical reactions both at a surface and in the bulk. In the second part of my talk, I will present hybrid (multiscale) algorithms which use models with a different level of detail in different parts of the computational domain. The main goal of this multiscale methodology is to use a detailed modelling approach in localized regions of particular interest (in which accuracy and microscopic detail is important) and a less detailed model in other regions in which accuracy may be traded for simulation efficiency. I will also discuss hybrid modelling of chemotaxis where an individual-based model of cells is coupled with PDEs for extracellular chemical signals.

Min-Max equations, also called Isaacs equations, arise from many applications, eg in game theory or mathematical finance. For their numerical solution, they are often discretised by finite difference

methods, and, in a second step, one is then faced with a non-linear discrete system. We discuss how upper and lower bounds for the solution to the discretised min-max equation can easily be computed.

We find and describe four futures markets where the bid-ask spread is bid down to the fixed price tick size practically all the time, and which match coun- terparties using a pro-rata rule. These four markets’ offered depths at the quotes on average exceed mean market order size by two orders of magnitude, and their order cancellation rates (the probability of any given offered lot being cancelled) are significantly over 96 per cent. We develop a simple theoretical model to explain these facts, where strategic complementarities in the choice of limit order size cause traders to risk overtrading by submitting over-sized limit orders, most of which they expect to cancel.

Joint work with Jonathan Field.

In this talk, I will present reflected backward stochastic differential equations (reflected BSDEs) and their connection with the pricing of American options. Then I will present a simple perturbative method for studying them. Under the appropriate assumptions on the coefficient, the terminal condition and the lower obstacle, similar to those used by Kobylankski, this method allows to prove the existence of a solution. I will also provide the usual comparison theorem and a new proof for a refined comparison theorem, specific to RBSDEs.

Decision making in the presence of uncertainty is a mathematically delicate topic. In this talk, we consider coherent sublinear expectations on a measurable space, without assuming the existence of a dominating probability measure. By considering discrete-time `martingale' processes, we show that the classical results of martingale convergence and the up/downcrossing inqualities hold in a `quasi-sure' sense. We also give conditions, for a general filtration, under which an `aggregation' property holds, generalising an approach of Soner, Touzi and Zhang (2011). From this, we extend various results on the representation of conditional sublinear expectations to general filtrations under uncertainty.

In this seminar, we discuss three questions related to the finite difference computation of early exercise options, one of which has a useful answer, one an interesting one, and one is open.

We begin by showing that a simple iteration of the exercise strategy of a finite difference solution is efficient for practical applications and its convergence can be described very precisely. It is somewhat surprising that the method is largely unknown.

We move on to discuss properties of a so-called penalty method. Here we show by means of numerical experiments and matched asymptotic expansions that the approximation of the value function has a very intricate local structure, which is lost in functional analytic error estimates, which are also derived.

Finally, we describe a gap in the analysis of the grid convergence of finite difference approximations compared to empirical evidence.

This is joint work with Jan Witte and Sam Howison.