This chapter is from the book
This chapter is from the book
This chapter is from the book
A Guide for Readers
This book introduces a charting technique that is designed to help option traders visualize price change behavior. Although the form is new, the underlying mathematics are that of standard option-pricing theory. Many of the charts presented in this book contain a series of bars that measure individual price changes in standard deviations against a sliding window of predetermined length. The exact method for creating these charts is described in the “Profiling Price Change Behavior” section of Chapter 3. All the charts presented were created using standard Microsoft desktop tools and readily available data sources. If you subscribe to a data service and you want to create charts of the same form, you will find that Excel’s statistical analysis and charting functions support these efforts very efficiently and that no programming is necessary.
Many readers who are familiar with the Microsoft Office environment will also want to construct a database containing historical price change information and volatility calculations for thousands of securities and indexes. For the present work, price and volume information was downloaded to a Microsoft Access database from a variety of readily available public and subscription-based data services. A large number of calculations were generated across the dataset and results for individual tickers were exported to Microsoft Excel, where the charts were created. The complete infrastructure is described in Chapter 9.
Just a few years ago desktop computers lacked the capacity and performance to support the work described in this book. Recent improvements in these machines’ size and performance have significantly reduced the complexity of such work. The change has been dramatic. Today’s multigigahertz multicore CPU desktop computers often come equipped with 3 gigabytes or more of memory and hundreds of gigabytes of disk storage. Microsoft desktop products such as Excel, Access, and Visual Basic provide all the necessary tools to build an infrastructure for managing millions of stock records on such a machine. These changes have been a welcome advance for those of us who previously programmed exclusively in C and C++ and struggled with the complexity and expense associated with a large computing infrastructure.
If you want to replicate the database system described in Chapter 9, you will discover that Microsoft Access can support relatively large designs. Most programmers will find the performance of the VBA programming language to be quite acceptable. The actual design includes a large number of Access VBA programs, macros, and SQL queries in addition to modeling tools written in Excel VBA.
Finally, the past few years have witnessed a leveling of the playing field in the sense that a serious private investor can, at reasonable cost, obtain all the tools necessary to build a sophisticated infrastructure. Information sources such as Bloomberg provide a robust set of programming interfaces for capturing and analyzing tick-by-tick data. They can become the content source for custom databases built with Microsoft SQL Server, Oracle, or IBM DB2, whose single-user versions are relatively inexpensive. Depending on the size, such systems can run on a single desktop computer or a cluster of machines linked with publicly available free Linux software. Five years ago this level of computing infrastructure was available only to financial institutions. Today, hundreds of thousands of private investors and small hedge funds are developing customized data mining and analysis tools as part of their effort to gain a technical edge in the market. This trend has become a dominant force in the investment world.
This book begins with an introduction to pricing theory and volatility before progressing through a series of increasingly complex types of structured trades.
The chapters are designed to be read in sequence. No particular technical background is required if you start at the beginning. However, you might find value in reading them in a different order. The following table will help you. It relates the level of technical background that is most appropriate for the subject matter presented. The two categories are option trading experience (Opt) and computer software skills (Comp):
- Opt 1: No prior knowledge of pricing theory or structured positions.
- Opt 2: Some familiarity with option pricing and basic trades.
- Opt 3: Familiarity with option pricing concepts, including the effects of time decay and delta. Experience with structuring option positions.
- Comp 1: Familiarity with basic software tools such as Microsoft Excel.
- Comp 2: Experience using trading tools such as stock-charting software.
- Comp 3: Experience building customized spreadsheets and moving data between software packages. The ability to download and use data from a subscription service. Familiarity with basic database concepts.
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Comp 1 |
Comp 2 |
Comp 3 |
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Opt 1 |
Chapters 1, 2, and 3 |
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Opt 2 |
Chapters 4 and 5 |
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Opt 3 |
Chapters 6, 7, and 8 |
Chapter 9 |
If you plan to study the chapters out of sequence, you should become familiar with the method for creating price spike charts that is outlined in Chapter 3. Because these charts are used throughout the book, it will be helpful for you to understand how they are calculated. Chapter 3 also includes a related discussion of variable-length volatility windows that will be helpful to most option traders. It builds on the discussion of pricing theory presented in Chapter 2.
Chapter 4 contains practical trading information that is often lost to oversimplification. Many authors have written about complex trades without mentioning the effects of bid-ask spreads, volatility swings, put-call parity violations, term structure, and changes in liquidity. Chapter 4 also discusses price distortions generated by earnings and options expiration—topics that are covered in greater detail in Chapters 7 and 8. We close with a discussion of the level II trading queue, which is now available to all public customers. Chapter 4 is meant to stand alone and can be read out of sequence if you’re an experienced trader who understands the basics of pricing.
Chapters 5 and 6 present a broad review of structured positions. Beginners will learn to create mathematically sound trades using a variety of pricing strategies. Advanced traders who are already familiar with the material will find the approach unique. Particularly important are the discussions of dynamic position management and the use of price spikes as trade triggers. Price-spike charts of the form presented in Chapter 3 are used throughout. Chapter 6 also includes an analysis of the VIX as a hedging vehicle—a topic that has recently come sharply into focus on Wall Street.
Chapters 7 and 8 present new information not found anywhere else. The strategies revealed in these discussions leverage price distortions that are normally associated with earnings and options expiration. They are tailored to investors seeking substantial returns with limited market exposure. The focus, as always, is practical trading. Chapter 8 also includes a review of the “stock pinning” phenomenon that has become the driving force behind the expiration day behavior of many securities. Some investors exposed to these methodologies have found that they can generate a substantial return on expiration day and remain out of the market the rest of the month.
Chapter 9 was written for the large and growing population of traders who want to optimize their use of online data services. The database infrastructure described in this chapter was built using the Microsoft desktop tools and databases mentioned previously. Detailed descriptions of the tables and data flows are included, and the layout is modular so that you may replicate the portions that best fit your needs. Investors who are primarily interested in bond, currency, future, or stock trading will also find value in the design elements presented in this chapter.