Singular Ergodic Control for Multidimensional Gaussian Processes

A multidimensional Wiener process is controlled by an additive process of bounded variation. A convex nonnegative function measures the cost associated with the position of the state process, and the cost of controlling is proportional to the displacement induced. We minimize a limiting time-average expected (ergodic) criterion. Under reasonable assumptions, we prove that the optimal discounted cost converges to the optimal ergodic cost. Moreover, under some additional conditions there exists a convex Lipschitz continuous function solution to the corresponding Hamilton-Jacobi-Bellman equation which provides an optimal stationary feedback control

The RTU Graduate School Executive Master's Program for school year 2011-2012 as viewed by its respondents

This study was conducted to ascertain the views and opinions of the faculty and personnel as recipients of the Rizal Technological University (RTU) Graduate School Executive Master's program as to its reasons for availment, importance of the core and major subjects of the curriculum, lecturers' professional skills, duration/time allotment, level of satisfaction, significant difference of the two programs, problem encountered and gathered possible solutions to the problems; determine whether the Executive Master's Program was able to realize its goals and objectives and find out the overall impression of the recipients about the Executive Master's Program. A total of fifty (50) RTU faculty and personnel graduated from this Executive Master's program, twenty six (26) Master of Arts in Education (MAEd) and twenty four (24) Master of Arts in Engineering (MAE)

Robust Control of Linear Stochastic Systems with Fully Observable State

We consider a multidimensional linear system with additive inputs (control) and Brownian noise. There is a cost associated with each control. The aim is to minimize the cost. However, we work with the model in which the parameters of the system may change in time and in addition the exact form of these parameters is not known, only intervals within which they vary are given. In the situation where minimization of a functional over the class of admissible controls makes no sense since the value of such a functional is different for different systems within the class, we should deal not with a single problem but with a family of problems. The objective in such a setting is twofold. First, we intend to establish existence of a state feedback linear robust control which stabilizes any system within the class. Then among all robust controls we find the one which yields the lowest bound on the cost within the class of all systems under consideration. We give the answer in terms of a solution to a matrix Riccati equation and we present necessary and sufficient conditions for such a solution to exist. We also state a criterion when the obtained bound on the cost is sharp, that is, the control we construct is actually a solution to the minimax problem

Asset Pricing and Hedging in Financial Markets with Transaction Costs: An Approach Based on the Von Neumann–Gale Model

Asset pricing, Hedging, Transaction costs, Trading constraints, Von Neumann–Gale model, Consistent valuation systems, G12, G13, C61, C67,