Tridiagonal implicit method to evaluate European and American options under infinite activity Lévy models

We propose an efficient implicit method to evaluate European and American options when the underlying asset follows an infinite activity Lévy model. Since the Lévy measure of the infinite activity model has the singularity at the origin, we approximate infinitely many small jumps by samples of a diffusion. The proposed methods to solve partial integro–differential equations for European options and linear complementarity problems for American options via an operator splitting method involve solving linear systems with tridiagonal matrices and so can significantly reduce the computations associated with the discrete integral operators. The numerical experiments verify that the proposed method has the second-order convergence rate under an infinite activity Lévy model.     

Corrigendum to “Prediction for some processes related to a fractional Brownian motion”

This note is a correction for the statement of the results presented in Proposition 2 of Duncan (2006).     

Robust duality for generalized convex programming problems under data uncertainty

In this paper we present a robust duality theory for generalized convex programming problems in the face of data uncertainty within the framework of robust optimization. We establish robust strong duality for an uncertain nonlinear programming primal problem and its uncertain Lagrangian dual by showing strong duality between the deterministic counterparts: robust counterpart of the primal model and the optimistic counterpart of its dual problem. A robust strong duality theorem is given whenever the Lagrangian function is convex. We provide classes of uncertain non-convex programming problems for which robust strong duality holds under a constraint qualification. In particular, we show that robust strong duality is guaranteed for non-convex quadratic programming problems with a single quadratic constraint with the spectral norm uncertainty under a generalized Slater condition. Numerical examples are given to illustrate the nature of robust duality for uncertain nonlinear programming problems. We further show that robust duality continues to hold under a weakened convexity condition.     

Robust network design in telecommunications under polytope demand uncertainty

We consider a model for robust network design in telecommunications, in which we minimize the cost of the maximum mismatch between supply and demand. In the present study, the demand is uncertain and takes its values in a polytope defined by constraints. This problem is hardly tractable, so we limit ourselves to computing lower bounds (by a column-generation mechanism) and upper bounds (using an algorithm due to Falk and Soland for maximizing a separable convex function over a polytope). The experimental gap obtained turns out to be large, and this seems to be mainly due to poor upper bounds. Two possible solutions are suggested for further research aimed at improving them: dc optimization (to minimize the difference of two convex functions) and AARC modeling (affinely adjustable robust counterpart).     

Information,no-arbitrage and completeness for asset price models with a change point

We consider a general class of continuous asset price models where the drift and the volatility functions, as well as the driving Brownian motions, change at a random time τ$\tau$. Under minimal assumptions on the random time and on the driving Brownian motions, we study the behavior of the model in all the filtrations which naturally arise in this setting, establishing martingale representation results and characterizing the validity of the NA1 and NFLVR no-arbitrage conditions.     

Portfolio adjusting optimization under credibility measures

This paper discusses portfolio adjusting problems for an existing portfolio. The returns of risky assets are regarded as fuzzy variables and a class of credibilistic mean-variance adjusting models with transaction costs are proposed on the basis of credibility theory. Under the assumption that the returns of risky assets are triangular fuzzy variables, the optimization models are converted into crisp forms. Furthermore, we employ the sequential quadratic programming method to work out the optimal strategy. Numerical examples illustrate the effectiveness of the proposed models and the influence of the transaction costs in portfolio selection.     

Robust conjugate duality for convex optimization under uncertainty with application to data classification

In this paper we present a robust conjugate duality theory for convex programming problems in the face of data uncertainty within the framework of robust optimization, extending the powerful conjugate duality technique. We first establish robust strong duality between an uncertain primal parameterized convex programming model problem and its uncertain conjugate dual by proving strong duality between the deterministic robust counterpart of the primal model and the optimistic counterpart of its dual problem under a regularity condition. This regularity condition is not only sufficient for robust duality but also necessary for it whenever robust duality holds for every linear perturbation of the objective function of the primal model problem. More importantly, we show that robust strong duality always holds for partially finite convex programming problems under scenario data uncertainty and that the optimistic counterpart of the dual is a tractable finite dimensional problem. As an application, we also derive a robust conjugate duality theorem for support vector machines which are a class of important convex optimization models for classifying two labelled data sets. The support vector machine has emerged as a powerful modelling tool for machine learning problems of data classification that arise in many areas of application in information and computer sciences.     

Sample path Large Deviations and optimal importance sampling for stochastic volatility models

Sample path Large Deviation Principles (LDP) of the Freidlin–Wentzell type are derived for a class of diffusions, which govern the price dynamics in common stochastic volatility models from Mathematical Finance. LDP are obtained by relaxing the non-degeneracy requirement on the diffusion matrix in the standard theory of Freidlin and Wentzell. As an application, a sample path LDP is proved for the price process in the Heston stochastic volatility model.     

Default swap games driven by spectrally negative Lévy processes

This paper studies game-type credit default swaps that allow the protection buyer and seller to raise or reduce their respective positions once prior to default. This leads to the study of an optimal stopping game subject to early default termination. Under a structural credit risk model based on spectrally negative Lévy processes, we apply the principles of smooth and continuous fit to identify the equilibrium exercise strategies for the buyer and the seller. We then rigorously prove the existence of the Nash equilibrium and compute the contract value at equilibrium. Numerical examples are provided to illustrate the impacts of default risk and other contractual features on the players’ exercise timing at equilibrium.     

On Gittins’ index theorem in continuous time

We give a new and comparably short proof of Gittins’ index theorem for dynamic allocation problems of the multi-armed bandit type in continuous time under minimal assumptions. This proof gives a complete characterization of optimal allocation strategies as those policies which follow the current leader among the Gittins indices while ensuring that a Gittins index is at an all-time low whenever the associated project is not worked on exclusively. The main tool is a representation property of Gittins index processes which allows us to show that these processes can be chosen to be pathwise lower semi-continuous from the right and quasi-lower semi-continuous from the left. Both regularity properties turn out to be crucial for our characterization and the construction of optimal allocation policies.     

Minimization of the root of a quadratic functional under an affine equality constraint

We present a way of solving the problem of minimizing the root of quadratic functional subject to an affine constraint. We give an explicit formula for computing the solutions of such a problem. This is of interest for solving significant problems of financial economics as well as some classes of feasibility and optimization problems which frequently occur in tomography and other fields.     

Effective measurement of network vulnerability under random and intentional attacks

The study of the security and stability of complex networks plays a central role in reducing the risk and consequences of attacks or disfunctions of any type. The concept of vulnerability helps to measure the response of complex networks subjected to attacks on vertices and edges and it allows to spot the critical component of a network in order to improve its security. We introduce an accurate and computable definition of network vulnerability which is directly connected with its topology and we analyze its basic properties. We discuss the relationship of the vulnerability with other parameters of the network and we illustrate this with some examples.     

A note on “Extensional PERs”

In the paper “Extensional PERs” by P. Freyd, P. Mulry, G. Rosolini and D. Scott, a category C of “pointed complete extensional PERs” and computable maps is introduced to provide an instance of an algebraically compact category relative to a restricted class of functors. Algebraic compactness is a synthetic condition on a category which ensures solutions of recursive equations involving endofunctors of the category. We extend that result to include all internal functors on C when C is viewed as a full internal category of the effective topos. This is done using two general results: one about internal functors in general, and one about internal functors in the effective topos.     

Erratum and addendum to “Two-point b.v.p. for multivalued equations with weakly regular r.h.s.”

In this paper, we define a topological index for compact multivalued maps in convex metrizable subsets of a locally convex topological vector space in order to correct the proofs of Theorems 4.1 and 4.2 in Benedetti et al. (2011) [1].     

Disjoint paths in a rectilinear grid

We give a good characterization and a good algorithm for a special case of the integral multicommodity flow problem when the graph is defined by a rectangle on a rectilinear grid. The problem was raised by engineers motivated by some basic questions of constructing printed circuit boards.     

An analysis of the greedy algorithm for the submodular set covering problem

We consider the problem: min \(\{ \mathop \Sigma \limits_{j \in s} f_j :z(S) = z(N),S \subseteqq N\} \) wherez is a nondecreasing submodular set function on a finite setN. Whenz is integer-valued andz(Ø)=0, it is shown that the value of a greedy heuristic solution never exceeds the optimal value by more than a factor \(H(\mathop {\max }\limits_j z(\{ j\} ))\) where \(H(d) = \sum\limits_{i = 1}^d {\frac{1}{i}} \) . This generalises earlier results of Dobson and others on the applications of the greedy algorithm to the integer covering problem: min {fy: Ay ≧b, y ε {0, 1}} wherea _ij ,b _i } ≧ 0 are integer, and also includes the problem of finding a minimum weight basis in a matroid.     

On the regularity of American options with regime-switching uncertainty

We study the regularity of the stochastic representation of the solution of a class of initial–boundary value problems related to a regime-switching diffusion. This representation is related to the value function of a finite-horizon optimal stopping problem such as the price of an American-style option in finance. We show continuity and smoothness of the value function using coupling and time-change techniques. As an application, we find the minimal payoff scenario for the holder of an American-style option in the presence of regime-switching uncertainty under the assumption that the transition rates are known to lie within level-dependent compact sets.     

Reliability of a system under two types of failures using a Markovian arrival process

We consider a system subject to external and internal failures. The operational time has a phase-type distribution (PH-distribution). Failures arrive following a Markovian arrival process (MAP). Some failures require the replacement of the system, and others a minimal repair. This model extends previous papers with arrivals governed by PH-renewal processes.