How to Trade Options – Book Review – Sheldon Natenberg, Volatility and Option Pricing

As with most books on the subject of trading options, the amount of material that needs to be processed can be overwhelming. For example, with Sheldon Natenberg’s Option Volatility and Pricing, that’s about 418 pages to digest.

There are proper reader reviews on Amazon and Google Book Search, to help you decide if you’ll get the book. For those who have just started or are about to read the book, I have summarized the basics in the larger, essential chapters to help you read them faster.

The number to the right of the chapter title is the number of pages contained in that chapter. It is not the page number. The percentages represent how much each chapter makes up out of the 418 total pages, excluding appendices.

1. The language of options. 12, 2.87%.

2. Elementary strategies. 22, 5.26%.

3. Introduction to Theoretical Price Models. 16, 3.83%.

4. Volatility. 30, 7.18%.

5. Use of the theoretical value of an option. 14, 3.35%.

6. Option values ​​and changing market conditions. 32, 7.66%.

7. Introduction to Diffusion. 10, 2.39%.

8. Volatility spreads. 36, 8.61%.

9. Risk Considerations. 26, 6.22%.

10. Bullish and bearish spreads. 14, 3.35%.

11. Arbitration Option. 28, 6.70%.

12. Early Exercise of American Options. 16, 3.83%.

13. Coverage with Options. 16, 3.83%.

14. Revised volatility. 28, 6.70%.

15. Futures and options on stock indexes. 30, 7.18%.

16. Spread between markets. 22, 5.26%.

17.Analysis of position. 32, 7.66%.

18. Models and the Real World. 34, 8.13%.

Focus on chapters 4, 6, 8, 9, 11, 14, 15, 17, and 18, which make up about 66% of the book. These chapters are relevant for practical business purposes. These are the key points of these focus chapters, which I am summarizing from the perspective of a retail options trader.

4 Volatility. Volatility as a measure of velocity in the context of the instability of the price of a given commodity in a particular market. Despite its shortcomings, the definition of volatility is still based on these assumptions of the Black-Scholes model:

1. The price changes of a product remain random and cannot be designed, making it impossible to predict the direction of the price before its movement.

2. Percentage changes in product price are normally distributed.

3. Because percentage changes in product price are counted as continuous compounding, the product price at expiration will have a log-normal distribution.

4. The mean of the lognormal distribution (mean reversion) is found at the forward price of the commodity.

6 Option Values ​​and Changing Market Conditions. Use of Delta in its 3 equivalent forms: Exchange Rate, Coverage Ratio and Theoretical Position Equivalent. Treatment of Gamma as the curvature of an option to explain the opposite relationship of OTM/ITM strikes with the ATM strike having the highest Gamma. This is the inverse Theta-Gamma relationship, as well as Theta being synthetically intertwined as a long dip and a short premium with implied volatility, as measured by Vega.

8 Volatility Spreads. Emphasis is on the sensitivities of a Ratio Back Spread, Ratio Vertical Spread, Straddle/Strangle, Butterfly, Calendar, and Diagonal to interest rates, dividends, and the 4 Greeks with specific attention to the effects of Gamma and Vega.

9 Risk considerations. A sobering reminder to select the spreads with the lowest aggregate risk spread versus the highest probability of benefit. Aggregate risk measured in terms of Delta (directional risk), Gamma (curvature risk), Theta (fall/premium risk) and Vega (volatility risk).

11 Arbitration Option. Synthetic positions are explained in terms of building a risk profile equivalent to the original spread, using a combination of unique options, other spreads, and the underlying product. Clear warning that the transformation of operations into Conversions, Reversals and Adjustments is not without risk; but it may increase the shorter-term risks of the trade even as the longer-term net risk is reduced. There are important differences in the cash flows of long options versus short options, which arise from the unique bias bias of a product and the interest rate built into call options, making them disparate from option options. sale.

14 Revised volatility. The different expiration cycles between short-term options and long-term options create a long-term average of volatility, a mean volatility. When volatility rises above its average, there is a relative certainty that it will return to its average. Likewise, reversion to the mean is very likely as volatility falls below its mean. The turn around the mean is an identifiable characteristic. Discernable volatility characteristics make it essential to forecast volatility in 30-day periods: 30-60-90-120 days, as the typical term is short credit spreads between 30-45 days and long debit spreads between 90 days. -120 days. Reconcile implied volatility as a measure of the consensus volatility of all buyers/sellers of a given commodity, with inconsistencies in historical volatility and predictive constraints on future volatility.

15 Stock Index Futures and Options. Effective use of indexing to de-risk individual stocks. Different treatment of risks for equity-settled indices (including impact of dividends/fiscal year) from cash-settled indices (non-dividends/fiscal year). Explains the rationale for the theoretical price of stock index futures options, as well as the price of the futures contract itself, in determining which is economically viable to trade: the futures contract itself or the options on the futures.

17 Analysis of positions. A more robust method than simply looking at the Delta, Gamma, Vega and Theta of a position is to use the relevant theoretical price model (Bjerksund-Stensland, Black-Scholes, Binomial) to test for changes in dates (daily/weekly) before the trade. expiration, percentage changes in implied volatility, and price changes within and near +/- 1 standard deviation. These factors that feed the scenario tests, once plotted, reveal the relative proportions of the Delta/Gamma/Vega/Theta risks in terms of their proportionality that impacts the Theoretical Price of specific strikes that make up the construction of a spread.

18 models and the real world. It addresses the weaknesses of these core assumptions used in a traditional pricing model: 1. Markets are not fluid: Buying/selling an underlying contract has restrictions in terms of tax implications, funding constraints, and transaction costs. 2. Interest rates are variable, not constant during the term of the option. 3. Volatility is variable, not constant over the life of the options. 4. Trading is not continuous 24/7: There are trading holidays that lead to gaps in price changes. 5. Volatility is linked to the Theoretical Price of the underlying contract, it is not independent of it. 6. Percentage price changes in an underlying contract do not result in a log-normal distribution of the underlying prices in the distribution due to Skew & Kurtosis.

To conclude, reading these chapters is not academic. Understanding the techniques discussed in the chapters should enable you to answer the following key questions. In the total inventory of your business account, if you are:

• Net Long more Calls than Puts, have you forecast the implied volatility (IV) to rise, expecting the prices of the products traded in your portfolio to rise?
• Net Long more Puts than Calls, have you predicted that IV will increase, expecting the prices of the traded products to go down?
• Net Long an equal amount of Calls and Puts, have you forecast IV to rise, expecting prices to drift non-directionally?
• Net Short more Calls than Puts, have you predicted that IV will fall? but, wait for prices to drop?
• Net Short more Puts than Calls, have you predicted that IV will fall? but, wait for prices to rise?
• Net Short an equal amount of Calls and Puts, have you predicted that IV will drop? but do you expect prices to drift non-directionally?