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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Alpha(c)E Et Ara(c)Thuse, Interma]de En Musique Paroles Du Feu Sieur Danchet

Musique Du Sr Dauvergne. Choisy-Le-Roi, 15 Da(c)Cembre 1762.

Michael Lynn Lovelady, 1957-

Antoine Danchet

Globe Fearon Educational Publishing

Hachette jeunesse - Disney

Hachette collections

Longman Publishing

Cengage Gale

FT Press

Pluriel

United States, United States of America

Upper Saddle River, New Jersey :, 2013

France, France

Apr 19, 2013

2, 2013

2000

lg2657217

producers:
Acrobat Distiller 7.0.5 for Macintosh

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

Contents 6
Preface 12
Chapter 1 Introduction 14
Growth in Structured Securities 15
Growing Emphasis on Low Volatility and Dividends 16
Criticisms of Structured Securities 17
Demand for Quantitative Skills 18
Direction of Quantitative Finance 19
When I Realized It Might Be Easier 21
Try Again 23
The Spreadsheet 23
Visualizing the Result 27
What It Means and Why It Works: A Nontechnical Overview 30
It Doesn’t Get Too Complicated 31
An Integrated View of Risk Management 31
Endnotes 32
Chapter 2 Random Variables and Option Pricing 34
Random Variables 35
Building the Spreadsheet 41
Correcting the Mistake 49
Optional: Additional Resources 54
Chapter 3 An Overview of Option Pricing Methods 56
The Black-Scholes Formula 56
Black-Scholes Assumptions 61
The Binomial Option Pricing Method 62
Monte Carlo Methods 64
Putting Visual Quant in Context 65
Additional Reading, Advanced Topics, and Resources 70
Endnotes 73
Chapter 4 Value-at-Risk and Conditional Value-at-Risk 74
How Likely Is Something? 75
Value-at-Risk 79
Multiple Stock VaR 81
Stock and Option VaR 81
Conditional Value-at-Risk 82
Chapter 5 Full Black-Scholes Model 90
Adding Functionality to the Model 92
Stock Return Mean (Cell G3) 92
Stock Return Standard Deviation (Cell G4) 95
Discount Factor 97
Stock Price Median 98
Summary of New Formulas 101
Pricing Put Options 101
Effects of Assumption Changes 106
Endnote 109
Chapter 6 The Lognormal Distribution and Calc Engine 110
Definition of the Lognormal Distribution 111
The Forward Equation 112
Cross Reference: Stochastic Differential Equations 113
The Backward Equation 115
The Calc Engine 117
Assigning Probabilities 120
Setting the Stock Price Range 123
Visualizing Option Pricing As Normal or Lognormal 125
Chapter 7 Investment Profiles and Synthetic Annuities 128
What Is a Synthetic Annuity, and How Does It Work? 130
The Investment Profile 132
Assigning Probabilities Using Implied Volatility 133
Using Options to Reshape the Investment Profile 136
Adjusting the Profile for Behavioral Finance 138
Concentrated Stock Example 141
The Synthetic Annuity in Turbulent Markets 151
Chapter 8 Stock-Only Investment Profile 158
The Purpose and Context of the Model 158
The Stock-Only Investment Profile 159
The Calc Engine 164
The Stock-Only Profit Calculation 170
Adding the Chart 172
Test: Stock-Only Investment Profile 175
Chapter 9 Adding Options to the Model 180
Long Put Profit 181
Short Put 182
Expected Values 183
Black-Scholes Add-In 186
The Heading Formulas 188
Delta Formulas 189
Time Value and Total Premium Formulas 189
Chapter 10 Option Investment Profiles 192
Long Call Option Investment Profile 192
Short Call Option 203
Long Put Option 205
Short Put Option 207
Chapter 11 Covered Calls, Condors, and SynAs 210
Covered Call Investment Profile 211
Put–Call Parity 213
Iron Condor Investment Profile 218
Synthetic Annuity (SynA) Investment Profile 222
Adding a Customized Utility Function 236
Endnotes 238
Chapter 12 Understanding Price Changes 240
Investing in XYZ 240
Attribution: Explaining Why the Option Price Changed 251
Endnote 258
Chapter 13 The Greeks 260
The Option Greeks 261
Calculating Greeks: Formulas, Models, and Platforms 262
Delta 265
Theta 270
Vega 275
Introduction to Chapters 14, “Tracking Performance,” and 15, “Covered Synthetic Annuities” 278
Chapter 14 Tracking Performance 282
Tracking Template 283
TradeStation Platform 287
Putting It All Together: Synthetic Annuity Overview 295
Chapter 15 Covered Synthetic Annuities 298
Covered Synthetic Annuity (CSynA) 299
Example: Deere & Company 302
The Standard CSynA 317
Supplemental Material: The CBOE S&P 500 BuyWrite Index 324
BXM Study by Callan Associates 325
Index 328
A 328
B 328
C 328
D 329
E 330
F 330
G-H 331
I 331
J-K-L 331
M 332
N 332
O 332
P 333
Q-R 334
S 335
T 336
U-V 337
W-Z 337
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Contents 6
Preface 12
Chapter 1 Introduction 14
Growth in Structured Securities 15
Growing Emphasis on Low Volatility and Dividends 16
Criticisms of Structured Securities 17
Demand for Quantitative Skills 18
Direction of Quantitative Finance 19
When I Realized It Might Be Easier 21
Try Again 23
The Spreadsheet 23
Visualizing the Result 27
What It Means and Why It Works: A Nontechnical Overview 30
It Doesn’t Get Too Complicated 31
An Integrated View of Risk Management 31
Endnotes 32
Chapter 2 Random Variables and Option Pricing 34
Random Variables 35
Building the Spreadsheet 41
Correcting the Mistake 49
Optional: Additional Resources 54
Chapter 3 An Overview of Option Pricing Methods 56
The Black-Scholes Formula 56
Black-Scholes Assumptions 61
The Binomial Option Pricing Method 62
Monte Carlo Methods 64
Putting Visual Quant in Context 65
Additional Reading, Advanced Topics, and Resources 70
Endnotes 73
Chapter 4 Value-at-Risk and Conditional Value-at-Risk 74
How Likely Is Something? 75
Value-at-Risk 79
Multiple Stock VaR 81
Stock and Option VaR 81
Conditional Value-at-Risk 82
Chapter 5 Full Black-Scholes Model 90
Adding Functionality to the Model 92
Stock Return Mean (Cell G3) 92
Stock Return Standard Deviation (Cell G4) 95
Discount Factor 97
Stock Price Median 98
Summary of New Formulas 101
Pricing Put Options 101
Effects of Assumption Changes 106
Endnote 109
Chapter 6 The Lognormal Distribution and Calc Engine 110
Definition of the Lognormal Distribution 111
The Forward Equation 112
Cross Reference: Stochastic Differential Equations 113
The Backward Equation 115
The Calc Engine 117
Assigning Probabilities 120
Setting the Stock Price Range 123
Visualizing Option Pricing As Normal or Lognormal 125
Chapter 7 Investment Profiles and Synthetic Annuities 128
What Is a Synthetic Annuity, and How Does It Work? 130
The Investment Profile 132
Assigning Probabilities Using Implied Volatility 133
Using Options to Reshape the Investment Profile 136
Adjusting the Profile for Behavioral Finance 138
Concentrated Stock Example 141
The Synthetic Annuity in Turbulent Markets 151
Chapter 8 Stock-Only Investment Profile 158
The Purpose and Context of the Model 158
The Stock-Only Investment Profile 159
The Calc Engine 164
The Stock-Only Profit Calculation 170
Adding the Chart 172
Test: Stock-Only Investment Profile 175
Chapter 9 Adding Options to the Model 180
Long Put Profit 181
Short Put 182
Expected Values 183
Black-Scholes Add-In 186
The Heading Formulas 188
Delta Formulas 189
Time Value and Total Premium Formulas 189
Chapter 10 Option Investment Profiles 192
Long Call Option Investment Profile 192
Short Call Option 203
Long Put Option 205
Short Put Option 207
Chapter 11 Covered Calls, Condors, and SynAs 210
Covered Call Investment Profile 211
Put–Call Parity 213
Iron Condor Investment Profile 218
Synthetic Annuity (SynA) Investment Profile 222
Adding a Customized Utility Function 236
Endnotes 238
Chapter 12 Understanding Price Changes 240
Investing in XYZ 240
Attribution: Explaining Why the Option Price Changed 251
Endnote 258
Chapter 13 The Greeks 260
The Option Greeks 261
Calculating Greeks: Formulas, Models, and Platforms 262
Delta 265
Theta 270
Vega 275
Introduction to Chapters 14, “Tracking Performance,” and 15, “Covered Synthetic Annuities” 278
Chapter 14 Tracking Performance 282
Tracking Template 283
TradeStation Platform 287
Putting It All Together: Synthetic Annuity Overview 295
Chapter 15 Covered Synthetic Annuities 298
Covered Synthetic Annuity (CSynA) 299
Example: Deere & Company 302
The Standard CSynA 317
Supplemental Material: The CBOE S&P 500 BuyWrite Index 324
BXM Study by Callan Associates 325
Index 328
A 328
B 328
C 328
D 329
E 330
F 330
G-H 331
I 331
J-K-L 331
M 332
N 332
O 332
P 333
Q-R 334
S 335
T 336
U-V 337
W-Z 337

<i>“Michael Lovelady takes a very complex topic and explains it in basic, clear terms. Anyone interested in gaining insight about how the logic behind options pricing works needs to learn the visual quantitative finance skills in this book. This is the key to managing risk and to designing options strategies. The author has combined mathematical formulation with clarity of thought and expression.”</i> <br>
<b>--Michael C. Thomsett</b>, author of <i>Options Trading for the Conservative Investo</i>r, and co-founder of ThomsettOptions.com
<p><i>“</i>Visual Quantitative Finance <i>demystifies the complex mathematics of quantitative finance by moving from the abstract to the intuitive. Lovelady lays bare the mechanics of the Black-Scholes formula and then uses the framework to explain, both intuitively and visually, risk management and options-based structured securities. A crowning achievement in simplicity that will benefit investors and students alike!”</i><br>
--<b>Don DePamphilis</b>, Ph.D., Clinical Professor of Finance, Loyola Marymount University, and author of <i>Mergers, Acquisitions, and Other Restructuring Activities</i>, 7th Edition</p>
<p><b>Modern Quantitative Finance Demystified! A simpler, visual approach for every investor, financial professional, and student.</b></p>
<p>Most investors today recognize the inadequacy of traditional strategies and instruments. However, they sensibly refuse to invest in securities they don’t understand. Unfortunately, alternative investments based on quantitative finance have been shrouded in confusion and advanced mathematics--placing them off limits to many investors who could profit from them. Now, Michael Lovelady cuts through the complexity, introducing a powerful visual approach to understanding options and related alternative investments.</p>
<p>Blending practice and theory, Lovelady illuminates and simplifies the core principles of modern quantitative finance. Lovelady introduces an intuitive, visual framework for understanding option pricing: foundational knowledge for managing risk and designing alternative strategies. Then, building on this framework, Lovelady presents a complete option-based model for tailoring risk/reward profiles, adjusting market exposure, generating income, and building creative portfolio structures.</p>
<p><i>Visual Quantitative Finance</i> will be invaluable to retail and institutional investors contemplating alternative investments, to advisors who guide them, and to all students of finance.</p>
<p>Coverage includes:<br>
• Random variables and option pricing<br>
• Option pricing methods<br>
• VaR and CVaR<br>
• Black-Scholes models<br>
• Investment profiles and model building<br>
• Stock-only and option-based profiles<br>
• Covered calls, condors, and SynAs<br>
• Understanding price changes<br>
• Greeks<br>
• Position management<br>
• Synthetic annuities, and more</p>
<p>Michael Lovelady makes quantitative finance more intuitive, visual, and accessible than ever before--giving investors the knowledge they need to confidently consider alternative strategies for controlling risk and increasing profit.</p>
<p>Lovelady introduces powerful visual techniques for analyzing options pricing, profit probabilities, virtual dividends, market risk exposure, and more. After introducing his visual approach, he applies it to one of today’s most important investing trends: lower-volatility, higher-income strategies.</p>
<p><i>Visual Quantitative Finance</i> will be invaluable for everyone interested in quantitative finance, options, risk, structured securities, or financial model building--and for everyone who must explain these topics to nonspecialists.</p>

2022-03-08