Utility Maximisation: Non-concave utility and non linear expectation

Since the birth of mathematical nance, portfolio selection has been one of the topics which have attracted a lot of interest, with models formulated in discrete and continuous time and developed in complete and incomplete markets. In conventional or neoclassical finance, many models are based off the assumption that agents make decisions by maximising their expected utility. Deviations between models and market observations have generated a recent field of study, behavioural finance, which incorporates psychology, sociology and finance together to resolve observed phenomenon like bubbles which conventional finance cannot explain. In this thesis, we will be restricting ourselves to the complete continuous market and look at a new formulation of expected utility maximisation with behavioural finance elements incorporated into it, namely S-shaped utilities and probability distortions. We consider the three general cases of expected utility maximisation: utility from terminal wealth, utility from consumption and utility from terminal wealth and consumption. We shall review the neoclassical problems and then explore the cases with behavioural elements installed. \ud \ud Key Words: Portfolio Selection, continuous time, martingale approach, Sshaped function, probability distortion, cumulative prospect theor

Non-linear biases, stochastically-sampled effective Hamiltonians and spectral functions in quantum Monte Carlo methods

In this article we study examples of systematic biases that can occur in quantum Monte Carlo methods due to the accumulation of non-linear expectation values, and approaches by which these errors can be corrected. We begin with a study of the Krylov-projected FCIQMC (KP-FCIQMC) approach, which was recently introduced to allow efficient, stochastic calculation of dynamical properties. This requires the solution of a sampled effective Hamiltonian, resulting in a non-linear operation on these stochastic variables. We investigate the probability distribution of this eigenvalue problem to study both stochastic errors and systematic biases in the approach, and demonstrate that such errors can be significantly corrected by moving to a more appropriate basis. This is lastly expanded to include consideration of the correlation function QMC approach of Ceperley and Bernu, showing how such an approach can be taken in the FCIQMC framework.Comment: 12 pages, 7 figure

The full replica symmetry breaking in the Ising spin glass on random regular graph

In this paper, we extend the full replica symmetry breaking scheme to the Ising spin glass on a random regular graph. We propose a new martingale approach, that overcomes the limits of the Parisi-M\'ezard cavity method, providing a well-defined formulation of the full replica symmetry breaking problem in random regular graphs. Finally, we define the order parameters of the system and get a set of self-consistency equations for the order parameters and the free energy. We face up the problem only from a technical point of view: the physical meaning of this approach and the quantitative evaluation of the solution of the self-consistency equations will be discussed in next works.Comment: 23 page

Malliavin calculus method for asymptotic expansion of dual control problems

We develop a technique based on Malliavin-Bismut calculus ideas, for asymptotic expansion of dual control problems arising in connection with exponential indifference valuation of claims, and with minimisation of relative entropy, in incomplete markets. The problems involve optimisation of a functional of Brownian paths on Wiener space, with the paths perturbed by a drift involving the control. In addition there is a penalty term in which the control features quadratically. The drift perturbation is interpreted as a measure change using the Girsanov theorem, leading to a form of the integration by parts formula in which a directional derivative on Wiener space is computed. This allows for asymptotic analysis of the control problem. Applications to incomplete It\^o process markets are given, in which indifference prices are approximated in the low risk aversion limit. We also give an application to identifying the minimal entropy martingale measure as a perturbation to the minimal martingale measure in stochastic volatility models

Representation Theorems for Quadratic F{\cal F}-Consistent Nonlinear Expectations

In this paper we extend the notion of ``filtration-consistent nonlinear expectation" (or "${\cal F}$-consistent nonlinear expectation") to the case when it is allowed to be dominated by a $g$-expectation that may have a quadratic growth. We show that for such a nonlinear expectation many fundamental properties of a martingale can still make sense, including the Doob-Meyer type decomposition theorem and the optional sampling theorem. More importantly, we show that any quadratic ${\cal F}$-consistent nonlinear expectation with a certain domination property must be a quadratic $g$-expectation. The main contribution of this paper is the finding of the domination condition to replace the one used in all the previous works, which is no longer valid in the quadratic case. We also show that the representation generator must be deterministic, continuous, and actually must be of the simple form