N. K. Chidambaran

Credit Enhancement Through Financial Engineering: Freeport-Mcmoran's Gold-Denominated Depositary Shares

In 1993 and early 1994, Freeport McMoRan Copper and Gold (FCX), a mining company, issued two series of gold-denominated depositary shares to raise 430 million dollars expanding their mining capacity in Indonesia. We price the depositary shares using a term structure model for the forward rates implied by gold futures and we show that FCX successfully enhanced the credit quality of the issue. This credit enhancement is achieved because the effect of linking the payoff of the depositary shares to gold reduces default risk and is similar to conventional risk management. However, the bundling of financing and risk management allows the firm to target hedging benefits only to the newly issued securities. The design of the security also overcomes the asset substitution problem. The depositary shares issued by FCX illustrate how firms can enhance credit quality through financial engineering without changing the existing priority ordering of their capital structure.

Liquidity, Leverage, and Lehman: A Structural Analysis of Financial Institutions in Crisis

This paper presents a flexible, lattice-based structural credit risk model that uses equity market information and a detailed depiction of a financial institution’s liability structure to analyze default risk. The model is applied to examine the term structure of default probabilities for Lehman Brothers prior to its demise. The results indicate, as early as March, that the firm would likely lose access to external capital within two years. The model can be used as both a diagnostic tool for the early detection of financial distress and a prescriptive tool for addressing the sources of risk in large, complex financial institutions.

Genetic Programming for Option Pricing

This chapter describes the Genetic Programming methodology and illustrates its application for the pricing of options. I describe the various critical elements of a Genetic Program – population size, the complexity of individual formulas in a population, and the fitness and selection criterion. As an example, I implement the Genetic Programming methodology for developing an option pricing model. Using Monte Carlo simulations, I generate a data set of stock prices that follow a Geometric Brownian motion and use the Black–Scholes model to price options off the simulated prices. The Black–Scholes model is a known solution and serves as the benchmark for measuring the accuracy of the Genetic Program. The Genetic Program developed for pricing options well captures the relationship between option prices, the terms of the option contract, and properties of the underlying stock price.