In this paper we use the property that certainty equivalence, as implied by a first-order approximation to the solution of stochastic discrete-time models, breaks in its equivalent continuous-time version. We study the extent to which a first-order approximated solution built by perturbation...

This paper presents a framework to model correlated default events that can be used to price and hedge standard and exotic credit baskets whose values depend on the realized losses of a default portfolio. The model consists of parametric continuous time Markov chain and aims to accurately...

Reformulating the results of del Baño Rollin, Ferreiro-Castilla, and Utzet (2010), we are able to give necessary and sufficient conditions for the moments of the stock price to exist and extend Theorem 2.1 of Forde and Jacquier (2011). Precisely Forde and Jacquier (2011) provide necessary...

This note identifies a gap in the proof of Corollary 2.4 in [2], which arises because the essential smoothness of the family (Xt/t) can fail for the log-spot process X in the Heston model, and describes how to circumvent the issue by applying a standard argument from large deviation theory

In this paper we study the stochastic area swept by a regular time-homogeneous diffusion till a stopping time. This unifies some recent literature in this area. Through stochastic time change we establish a link between the stochastic area and the stopping time of another associated...

In this paper we use the property that certainty equivalence, as implied by a first-order approximation to the solution of stochastic discrete-time models, breaks in its equivalent continuous-time version. We study the extent to which a first-order approximated solution built by perturbation...

We derive closed-form expressions to price European calls and puts assuming the cash flows of the underlying asset or project are normally distributed. This approach has important advantages in the context of real options applied to infrastructure projects when compared to the Black-Scholes...

In this paper, we introduce and develop the theory of semimartingale optimal transport in a path dependent setting. Instead of the classical constraints on marginal distributions, we consider a general framework of path dependent constraints. Duality results are established, representing the...

In this paper, motivated by the approximation of Martingale Optimal Transport problems, we are interested in sampling methods preserving the convex order for two probability measures µ and ν on ℝ^d, with ν dominating µ. When (X_i)1≤i≤I (resp. (Y_j)1≤j≤J ) are independent and...

In this paper we use the property that certainty equivalence, as implied by a first-order approximation to the solution of stochastic discrete-time models, breaks in its equivalent continuous-time version. We study the extent to which a first-order approximated solution built by perturbation...