This tutorial explains the basics of linear regression models. especially low-order polynomials. and the corresponding statistical designs. namely, designs of resolution III, IV, V, and Central Composite Designs (CCDs).This tutorial assumes 'white noise', which means that the residuals of the...

We consider consistent tests for stochastic dominance efficiency at any order of a given portfolio with respect to all possible portfolios constructed from a set of assets. We propose and justify approaches based on simulation and the block bootstrap to achieve valid inference in a time series...

Quasi-Monte Carlo sequences have been shown to provide accurate option price approximations for a variety of options. In this paper, we apply quasi-Monte Carlo sequences in a duality approach to value American options. We compare the results using different low discrepancy sequences and estimate...

The classic error bounds for quasi-Monte Carlo approximation follow the Koksma-Hlawka inequality based on the assumption that the integrand has finite variation. Unfortunately, not all functions have this property. In particular, integrands for common applications in finance, such as option...

Black-Scholes is useful for valuing real options, but not in the way often used for new ventures. The use rests on an apparent analogy between real and stock options. Although conceptually helpful, a direct analogy is flawed for most real ventures. The most critical flaw is the assumption that...

We used advances in data envelopment analysis (DEA) techniques to examine efficiency scores and investigate the issue of convergence and divergence in a cross-country analysis. Specifically, we used bootstrapping techniques to examine a data set of 52 developed and developing countries. We found...

Modeling the unconditional distribution of returns on exchange rate and measuring its tails area are issues in the finance literature that have been studied extensively by parametric and non-parametric estimation procedures. However, a conflict of robustness is derived from them because the time...

We consider four utility functions, each of which incorporates a benchmark to better capture the motivations of today's portfolio managers. Assuming instrument returns are normally distributed, we establish conditions undr which optimal portfolios for these utilities are mean-variance efficient...

This chapter surveys two methods for the optimization of real-world systems that are modelled through simulation. These methods use either linear regression metamodels, or Kriging (Gaussian processes). The metamodel type guides the design of the experiment; this design fixes the input...

This tutorial reviews the design and analysis of simulation experiments. These experiments may have various goals: validation, prediction, sensitivity analysis, optimization (possibly robust), and risk or uncertainty analysis. These goals may be realized through metamodels. Two types of...