This paper examines the different types of incentives that countries face when deciding to take part in a federal fiscal system. The optimal degree of participation depends on the structural parameters of the economy and on the properties of the federal fiscal system. Firstly, the paper examines...

A dynamic pre-positioning problem is proposed to efficiently respond to victims’ needs for relief supplies under uncertain and dynamic demand in humanitarian relief. The problem is formulated as a multi-stage stochastic programming model that considers pre-positioning with multi-stage...

In this paper, we show that a time-dependent local stochastic volatility (SLV) model can be reduced to a system of autonomous PDEs that can be solved using the heat kernel, by means of the Wei-Norman factorization method and Lie algebraic techniques. Then, we compare the results of traditional...

This papers documents notes on probability distribution and average of asset returns. In summary, I argue that 1) wave function describes probabilities of asset returns, 2) following Cauchy distribution of returns makes diversification conditionally useless in terms of risk management, 3) median...

Properties of a binary choice probability function p defined on multiattributed outcomes are studied to represent p as a transformation of additive difference evaluations of receiving and foregone outcomes into the unit interval. We use an algebraic assumption to obtain an additive difference...

We combine the one-dimensional Monte Carlo simulation and the semi-analytical one-dimensional heat potential method to design an efficient technique for pricing barrier options on assets with correlated stochastic volatility. Our approach to barrier options valuation utilizes two loops. First we...

We propose a new variational approximation of the joint posterior distribution of the log-volatility in the context of large Bayesian VARs. In contrast to existing approaches that are based on local approximations, the new proposal provides a global approximation that takes into account the...

The fundamental connection between stochastic differential equations (SDEs) and partial differential equations (PDEs) has found numerous applications in diverse fields. We explore a similar link between stochastic calculus and combinatorial PDEs on graphs with Hodge structure, by showing that...

We use a novel definition of tail risk for option pricing purposes, based on the concept of almost stochastic dominance (ASD) in order to examine empirical “puzzles” documented in several high profile studies of the market for S&P 500 index options. We find that with one exception these...

We define two new stochastic orders combining probability ratio and likelihood ratio and specify two respective classes of payoff functions, which nest most models in the literature as special cases, such that a risk change satisfies one of the two stochastic orders if and only if given any...