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Visual Quantitative Finance: A New Look at Option Pricing, Risk Management, and Structured Securities

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Visual Quantitative Finance: A New Look at Option Pricing, Risk Management, and Structured Securities


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Finally, the key concepts of modern quantitative finance made easier and visual: a breakthrough for investors, financial pros, and students.

  • Introduces a powerful visual approach to option pricing that eliminates much of its complexity
  • Presents a unique step-by-step approach to visualizing and evaluating structured securities in the context of investment theory and practical risk management
  • Offers a "time-lapse" view of changing volatility, prices, probability distributions and performance metrics
  • Supports advanced applications far beyond Black-Scholes, including fat tails


  • Copyright 2013
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-292919-8
  • ISBN-13: 978-0-13-292919-6

This book makes quantitative finance (almost) easy! Its new visual approach makes quantitative finance accessible to a broad audience, including those without strong backgrounds in math or finance. Michael Lovelady introduces a simplified but powerful technique for calculating profit probabilities and graphically representing the outcomes. Lovelady's "pictures" highlight key characteristics of structured securities such as the increased likelihood of profits, the level of virtual dividends being generated, and market risk exposures. After explaining his visual approach, he applies it to one of today's hottest investing trends: lower-volatility, higher-income strategies. Because of today's intense interest in alternative investments and structured securities, this book reviews their unique advantages to investors, managers and advisors of retail and institutional portfolios. Visual Quantitative Finance focuses on key topics directly related to the design, pricing and communication of structured securities, including stochastic price projections and the framework underlying options pricing formulas. The key is Lovelady's explicit use of probabilities in a spreadsheet format. By working directly with the underlying assumptions, he transforms the Black-Scholes framework into five columns of a simple Excel spreadsheet, with no complicated formulas -- making structured securities far more intuitive to design, evaluate and manage. For all investors, students, and financial professionals who are interested in quantitative finance, risk measurement, options pricing, structured securities, or financial model building - and for everyone who needs to explain these topics to someone else. For those with quantitative backgrounds, this guide offers powerful new tools for design and risk management, simplifying the design and evaluation of innovative instruments. For everyone else, Lovelady makes the subject comprehensible for the first time.

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Introduction to Visual Quantitative Finance

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Table of Contents

Preface     xi
Chapter 1  Introduction     1
Growth in Structured Securities     2
Growing Emphasis on Low Volatility and Dividends     3
Criticisms of Structured Securities     4
Demand for Quantitative Skills     5
Direction of Quantitative Finance     6
When I Realized It Might Be Easier     8
Try Again     10
The Spreadsheet     10
Visualizing the Result     14
What It Means and Why It Works: A Nontechnical Overview     17
It Doesn’t Get Too Complicated     18
An Integrated View of Risk Management     18
Endnotes     19

Chapter 2  Random Variables and Option Pricing     21
Random Variables     22
Building the Spreadsheet     28
Correcting the Mistake     36
Optional: Additional Resources     41

Chapter 3  An Overview of Option Pricing Methods     43
The Black-Scholes Formula     43
Black-Scholes Assumptions     48
The Binomial Option Pricing Method     49
Monte Carlo Methods     51
Putting Visual Quant in Context     52
Additional Reading, Advanced Topics, and Resources     57
Endnotes     60

Chapter 4  Value-at-Risk and Conditional Value-at-Risk     61
How Likely Is Something?     62
Value-at-Risk     66
Multiple Stock VaR     68
Stock and Option VaR     68
Conditional Value-at-Risk     69

Chapter 5  Full Black-Scholes Model     77
Adding Functionality to the Model     79
Stock Return Mean (Cell G3)     79
Stock Return Standard Deviation (Cell G4)     82
Discount Factor     84
Stock Price Median     85
Summary of New Formulas     88
Pricing Put Options     88
Effects of Assumption Changes     93
Endnote     96

Chapter 6  The Lognormal Distribution and Calc Engine     97
Definition of the Lognormal Distribution     98
The Forward Equation     99
Cross Reference: Stochastic Differential Equations     100
The Backward Equation     102
The Calc Engine     104
Assigning Probabilities     107
Setting the Stock Price Range     110
Visualizing Option Pricing As Normal or Lognormal     112

Chapter 7  Investment Profiles and Synthetic Annuities     115
What Is a Synthetic Annuity, and How Does It Work?     117
The Investment Profile     119
Assigning Probabilities Using Implied Volatility     120
Using Options to Reshape the Investment Profile     123
Adjusting the Profile for Behavioral Finance     125
Concentrated Stock Example     128
The Synthetic Annuity in Turbulent Markets     138

Chapter 8  Stock-Only Investment Profile     145
The Purpose and Context of the Model     145
The Stock-Only Investment Profile     146
The Calc Engine     151
The Stock-Only Profit Calculation     157
Adding the Chart     159
Test: Stock-Only Investment Profile     162

Chapter 9  Adding Options to the Model     167
Long Put Profit     168
Short Put     169
Expected Values     170
Black-Scholes Add-In     173
The Heading Formulas     175
Delta Formulas     176
Time Value and Total Premium Formulas     176

Chapter 10  Option Investment Profiles     179
Long Call Option Investment Profile     179
Short Call Option     190
Long Put Option     192
Short Put Option     194

Chapter 11  Covered Calls, Condors, and SynAs     197
Covered Call Investment Profile     198
Put–Call Parity     200
Iron Condor Investment Profile     205
Synthetic Annuity (SynA) Investment Profile     209
Adding a Customized Utility Function     223
Endnotes     225

Chapter 12  Understanding Price Changes     227
Investing in XYZ     227
Attribution: Explaining Why the Option Price Changed     238
Endnote     245

Chapter 13  The Greeks     247
The Option Greeks     248
Calculating Greeks: Formulas, Models, and Platforms     249
Delta     252
Theta     257
Vega     262

Introduction to Chapters 14, “Tracking Performance,” and 15, “Covered Synthetic Annuities”     265
Chapter 14  Tracking Performance     269
Tracking Template     270
TradeStation Platform     274
Putting It All Together: Synthetic Annuity Overview     282

Chapter 15  Covered Synthetic Annuities     285
Covered Synthetic Annuity (CSynA)     286
Example: Deere & Company     289
The Standard CSynA     304
Supplemental Material: The CBOE S&P 500 BuyWrite Index     311
BXM Study by Callan Associates     312

Index     315

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