This paper introduces recent developments in the analysis of inventory systems with partial observations. The states of these systems are typically conditional distributions, which evolve in infinite dimensional spaces over time. Our analysis involves introducing unnormalized probabilities to...

This paper introduces a flexible method based on dynamic programming to calculate the quantitative value of any approach to managing the innovation process. The quantification lets managers precisely compare the values of different approaches, and so identify those that are optimised for their...

The goal programming (GP) is a well-known approach applied to multi-criteria decision making (M-DM). It has been used in many domains and the literature offers diverse extensions of this procedure. On the other hand, so far, some evident analogies between M-DM under certainty and scenario-based...

In this contribution we propose an approach to solve a multistage stochastic programming problem which allows us to obtain a time and nodal decomposition of the original problem. This double decomposition is achieved applying a discrete time optimal control formulation to the original stochastic...

We derive a general formula for the time decay, theta, for out-of-the-money European options on stocks and bonds at expiry, in terms of the density of jumps and payoff. Explicit formulas are derived for the standard put and call options, exchange options in stochastic volatility and local...

We introduce a generic solver for dynamic portfolio allocation problems when the market exhibits return predictability, price impact and partial observability. We assume that the price modeling can be encoded into a linear state-space and we demonstrate how the problem then falls into the LQG...

We propose a novel linear approximation of expected utility. The approximation guides us as we transfer the traditional quadratic dependence of third-order stochastic dominance (TSD) into an equivalent linear system. The finding also shows a dual relationship between traditional low partial...

Dynamic programming is the essential tool in dynamic economic analysis. Problems such as portfolio allocation for individuals and optimal economic growth are typical examples. Numerical methods typically approximate the value function. Recent work has focused on making numerical methods more...

A key firm in the recent crisis has been AIG. Its CDS financial intermediation tried to function on too thin layer of capital – high leverage – owing to a misreading of the degree of risk embodied in ever more complex financial products and markets. I explain why the application of...

The importance of portfolio optimization in finance field has been increasing significantly. Although, portfolio optimization problems over a single period or multiple periods are studied extensively, the problem with an option to rebalance over multiple periods is not considered significantly....