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Advanced Option Pricing Models-An Empirical Approach to Valuing Options
JEFFREY OWEN KATZ, Ph.D.
DONNA L. MCCORMICK
Copyright © 2005 by Scientific Consultant Services, Inc. All rights reserved. Manufactured in the
United States of America. Except as permitted under the United States Copyright Act of 1976, no
part of this publication may be reproduced or distributed in any form or by any means, or stored in
a database or retrieval system, without the prior written permission of the publisher.
Introduction
Thinking Out of the Box • Improving Option Pricing Strategies: A Scientific
Investigation • Assumptions Made by Popular Models: Are They Correct? •
Optimal Model Inputs • What Is Covered in the Chapters? • Who Will
Benefit? • Tools and Materials Used in the Investigation • An Invitation
Chapter 1
A Review of Options Basics 19
Basic Options: Calls and Puts • Naked and Covered • Additional Option
Terminology • Factors Influencing Option Premium (well-known factors such
as volatility, time, strike, stock price, and interest rate; lesser-known factors
such as skew, kurtosis, and cycles) • Uses of Options • Option Pricing Models
(the Greeks, Black-Scholes, why use a pricing model?) • Graphic Illustrations
(the influence of various factors on option premium) • Put-Call Parity,
Conversions, and Reversals • Synthetics and Equivalent Positions •
Summary • Suggested Reading
Chapter 2
Fair Value and Efficient Price 51
Defining Fair Value • Fair Value and the Efficient Market • The Context
Dependence of Fair Value • Understanding and Estimating Fair Value • Fair
Value and Arbitrage • Fair Value and Speculation • Estimating Speculative
Fair Value (modeling the underlying stock, pricing the option) • Summary •
Suggested Reading
Chapter 3
Popular Option Pricing Models 71
The Cox-Ross-Rubinstein Binomial Model (specifying growth and volatility,
……
……
Chapter 9
Option Prices in the Marketplace 383
Data and Software • Study 1: Standard Volatility, No Detrending • Method •
Results (calls on stocks with 30% historical volatility and with 90% historical
volatility, puts on stocks with 30% historical volatility and with 90% historical
volatility) • Summary (discussion of issues, suggestions for further study)
Conclusion
Defining Fair Value • Popular Models and Their Assumptions (the assumptions
themselves, strengths and weaknesses of popular models) • Volatility Payoffs
and Distributions • Mathematical Moments (moments and holding periods,
moments and distributions, moments and day of the week, moments and
seasonality, moments and expiration date) • Volatility (standard historical
volatility as an estimator of future volatility, the reliability of different measures
of volatility, developing a better estimator of future volatility, implied volatility)
• Conditional Distributions (raw historical volatility: conditional distributions
vs. Black-Scholes; regression-estimated volatility: conditional distributions vs.
Black-Scholes; detrended distributions: conditional distributions vs. Black-
Scholes; distributions and the volatility payoff; skew and kurtosis as variables
in a conditional distribution; conditional distributions and venue; technical
indicators as conditioning variables) • Using Nonlinear Modeling Techniques
to Price Options (neural networks vs. polynomial regressions vs. Black-Scholes,
strengths and weaknesses of nonlinear modeling techniques, hybrid models) •
Volatility Revisited (the impact of historical skew, kurtosis, and historical
volatility on future volatility; using technical indicators in the prediction of
future volatility) • Option Prices in the Marketplace • Summary
Notice: Companion Software Available 423
Bibliography 425
Index 429