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In an optimal variance stopping (O.V.S.) problem one seeks to determine the stopping time that maximizes the variance of an observed process. As originally shown by Pedersen (2011), the variance criterion leads to optimal stopping boundaries that depend explicitly on the initial point of the process. Then, following the lines of Pedersen and Peskir (2016), we introduce the concept of dynamic optimality for an O.V.S. problem, a type of optimality that disregards the starting point of the process. We examine when an O.V.S. problem admits a dynamically optimal stopping time and we illustrate our findings through several examples. [ABSTRACT FROM AUTHOR]

In this paper, we propose a continuous time version of the well-known speculative storage model for commodity prices. But from the mathematical point of view this is not a trivial extension and needs careful consideration of the theory of stochastic stopping time combined with fixed point theory. We formulate the problem in a manner that the main objective of the storage model, known as the stationary rational expectations equilibrium (SREE), becomes a fixed-point of an operator which solves a free boundary problem and show that this operator under some conditions is a contraction. We also demonstrate the benefits of our continuous time model through a numerical algorithm. [ABSTRACT FROM AUTHOR]

In this paper we first prove a general representation theorem for generators of backward stochastic differential equations (BSDEs for short) by utilizing a localization method involved with stopping time tools and approximation techniques, where the generators only need to satisfy a weak monotonicity condition and a general growth condition in y and a Lipschitz condition in z . This result basically solves the problem of representation theorems for generators of BSDEs with general growth generators in y . Then, such representation theorem is adopted to prove a probabilistic formula, in viscosity sense, of semilinear parabolic PDEs of second order. The representation theorem approach seems to be a potential tool to the research of viscosity solutions of PDEs. [ABSTRACT FROM AUTHOR]

Local perturbations of a Brownian motion are considered. As a limit we obtain a non-Markov process that behaves as a reflecting Brownian motion on the positive half line until its local time at zero reaches some exponential level, then changes a sign and behaves as a reflecting Brownian motion on the negative half line until some stopping time, etc. [ABSTRACT FROM AUTHOR]

We provide a point estimate for integrals on R , based on the standard Brownian motion. We prove the consistency of the estimator and limit theorems for the fluctuations. The proof relies on computing the distribution of the local time of a Brownian motion at a specific stopping time. [ABSTRACT FROM AUTHOR]

We establish the Default Barrier Intensity (DBI) model, based on the conditional survival probability (also called hazard function barrier), which allows the pricing of credit derivatives with stochastic parameters. Moreover, the DBI is an analytic model which combines the structural and the reduced form approaches. It deals with the impact of the default barrier intensity on the processes around the firm. Using this model we prove the Doob–Meyer decomposition of the default process associated with the random barrier. In this framework, we present the default barrier process as the sum of its compensator (which is a predictable process) and a martingale related to the smallest filtration making the random barrier a stopping time. Furthermore, the DBI as well as the Shifted Square Root Diffusion (SSRD) Alfonsi’s model emphasizes on the dependence between the stochastic default intensity and the interest rate. This model can be useful since it can be easily generalized to all the credit derivatives products such as Collateralized Debt Obligations (CDO) and Credit Default Swaps (CDS). [ABSTRACT FROM AUTHOR]

This paper investigates a non-autonomous slow–fast system, which is generalized by stochastic differential equations with locally Lipschitz coefficients, subjected to standard Brownian motion and fractional Brownian motion with Hurst parameter 1 / 2 < H < 1. The pathwise approach and the Itô stochastic calculus are combined with the technique of stopping time to establish the averaging principle. Then, we conclude that the slow component of the original slow–fast system converges to the solution of the proposed averaged equation in the mean square sense. [ABSTRACT FROM AUTHOR]

We consider an approach to credit risk in which the information about the time of bankruptcy is modelled using a Brownian bridge that starts at zero and is conditioned to equal zero when the default occurs. This raises the question whether the default can be foreseen by observing the evolution of the bridge process. Unlike in most standard models for credit risk, we allow the distribution of the default time to be singular. Using a well known fact from parabolic potential theory, we provide a sufficient condition for its predictability. [ABSTRACT FROM AUTHOR]

This paper provides a fixed-width confidence interval of a real-valued functional, which involves the comparison between the univariate distribution functions, under a response-adaptive design in which a Stein-type two-stage procedure is carried out. [ABSTRACT FROM AUTHOR]