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Finally, the key concepts of modern quantitative finance made easier and visual: a breakthrough for investors, financial pros, and students.
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.
Introduction to Visual Quantitative Finance
Download the sample pages (includes Chapter 1 and Index)
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