In this article we address the problem of valuing and hedging American options on baskets and spreads, i.e., on portfolios consisting of both long and short positions. We adopt the main ideas of the Generalized Lognormal (GLN) approach introduced in Borovkova et al. (2007) and extend them to the case of American options. We approximate the basket price process by a suitable Geometric Brownian m...

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level r...

This study aims to evaluate the impact of pavement physical characteristics on the frequency of single-vehicle run-off-road (ROR) crashes in two-lane separated rural highways. In order to achieve this goal and to introduce the most accurate crash prediction model (CPM), authors have tried to develop generalized linear models, including the Poisson regression (PR), negative binomial regression (...

Given the well known convergence difficulties in fitting log binomial regression with standard GLM software, we implement a direct solution via constrained optimization which avoids the circumventions found in the literature. The use of a log binomial model is motivated by our interest in directly estimating relative risks adjusted for confounders. A Bayesian log binomial regression model is al...

Using backward stochastic difference equations (BSDEs), this paper studies dynamic convex risk measures for risky positions in a simple discretetime, binomial tree model. A relationship between BSDEs and dynamic convex risk measures is developed using nonlinear expectations. The time consistency of dynamic convex risk measures is discussed in the binomial tree framework. A relationship between ...

We consider the problem of efficient coloring of the edges of a so-called binomial tree T, i.e. acyclic graph containing two kinds of edges: those which must have a single color and those which are to be colored with L consecutive colors, where L is an arbitrary integer greater than 1. We give an O(n) time algorithm for optimal coloring of such a tree, where n is the number of vertices of T. Al...

San Fermı́n is a system for aggregating large amounts of data from the nodes of large-scale distributed systems. Each San Fermı́n node individually computes the aggregated result by swapping data with other nodes to dynamically create its own binomial tree. Nodes that fall behind abort their trees, thereby reducing overhead. Having each node create its own binomial tree makes San Fermı́n highly re...

The real estate derivatives market allows participants to manage risk and return from exposure to property, without buying or selling directly the underlying asset. Such market is growing very fast hence the need to rely on simple yet effective pricing models is very great. In order to take into account the real estate market sensitivity to the interest rate term structure in this paper is pres...

We propose an efficient fault-tolerant routing algorithm for hypercube networks with a very large number of faulty nodes. The algorithm is distributed and local-information-based in the sense that each node in the network knows only its neighbors’ status and no global information of the network is required by the algorithm. For any two given nonfaulty nodes in a hypercube network that may conta...