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.

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