In this work we develop a methodology to reduce the variance when applying Monte Carlo simulation to the pricing of a European, American or Barrier option in a stochastic volatility environment. We begin by presenting some applicable concepts in the theory of stochastic differential equations....

The main objective of this thesis is to develop novel Monte Carlo techniques with emphasis on various applications in finance and economics, particularly in the fields of risk management and asset returns modeling. New stochastic algorithms are developed for rare-event probability estimation,...

We present a novel method, called the transform likelihood ratio (TLR) method, for estimation of rare event probabilities with heavy-tailed distributions. Via a simple transformation ( change of variables) technique the TLR method reduces the original rare event probability estimation with heavy...

We consider the problem of efficient estimation of tail probabilities of sums of correlated lognormals via simulation. This problem is motivated by the tail analysis of portfolios of assets driven by correlated Black-Scholes models. We propose two estimators that can be rigorously shown to be...

This dissertation consists of three independent sections: In the first part, focusing on the auto industry we look at the challenges and solution strategies of employing build-to-order (BTO) with global supply. We consider some familiar tools for managing domestic supply and exploit them for...

Of the five finalists, the winning team included Siddharth Coelho-Prabhu, Arpit Dharia, Akshay Kotak, Jason Kumar, Shyam Mehta, and Ranjini Ragunathan with adviser John Vande Vate who worked on a project with Intel titled, Designing Cost-Effective Distribution Strategies for Intel's Proposed...

Exploration and Production (E&P) project costs within the oil industry are continuously increasing reflecting a reality of more harsh environments, remote locations with minimal existing infrastructure and cost increases for materials and skilled resources. The significant capital expenditures...

M.S.

Investment decisions have to be made when there is little information about the scope of the project. New projects have to depend on historical evidences and experiences gained from previous projects of similar nature. However, such projects lack historical data and even if such data are...

The statistical variance of total project cost is usually estimated by means of Monte Carlo simulation on the assumption that exact analytic approaches are too difficult. This paper tests that assumption and shows that, contrary to expectations, the analytic solution is relatively...