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

91
1002

As with most books on how to trade options, the sheer amount of material to go through can be daunting. For example, with the volatility and pricing of options from Sheldon Natenberg, it takes around 418 pages to digest.

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

The number to the right of the chapter title corresponds to the number of pages contained in that chapter. This is not the page number. Percentages represent each chapter's share of the total 418 pages, excluding appendices.

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

2. Basic strategies. 22, 5.26%.

3. Introduction to theoretical pricing models. 16, 3.83%.

4. Volatility. 30, 7.18%.

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

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

7. Introduction to dissemination. 10, 2.39%.

8. Volatility spreads. 36, 8.61%.

9. Risk considerations. 26, 6.22%.

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

11. Option arbitrage. 28, 6.70%.

12. Early exercise of US options. 16, 3.83%.

13. Coverage with options. 16, 3.83%.

14. Revisited volatility. 28, 6.70%.

15. Futures contracts and options on stock indices. 30, 7.18%.

16. Intermarket propagation. 22, 5.26%.

17. Position analysis. 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. Here are the key points from these chapters, which I summarize from a retail options trader's perspective.

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

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

2. Percentage changes in the price of the product are normally distributed.

3. Since the product price percentage changes are counted as being continuously compounded, the product price at expiration will be distributed lognormally.

4. The mean of the lognormal distribution (mean reversion) is found in the futures price of the product.

6 Option values ​​and changes in market conditions. Use of Delta in its 3 equivalent forms: rate of change, coverage ratio and theoretical equivalent of the position. Treating Gamma as the curvature of an option to explain the opposite relationship of OTM / ITM hits to the ATM hit with the highest Gamma. Manage the inverse Theta-Gamma relationship, as well as Theta being synthetically interwoven as long decay and short prime with implied volatility, as measured by Vega.

8 Volatility spreads. The focus 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 particular attention to the effects of Gamma and Vega.

9 Risk considerations. A sobering reminder to select the spreads with the lowest overall risk spread versus the highest probability of profit. Aggregate risk measured in terms of delta (directional risk), gamma (risk of curvature), theta (risk of disintegration / prime) and Vega (risk of volatility).

11 Option arbitrage. Synthetic positions are explained in terms of making a risk profile equivalent to the original spread, using a combination of single options, other spreads, and the underlying product. A clear caveat that turning transactions into conversions, cancellations and adjustments is not without risk; but can increase the short term risks of trading even if the long term net risk is reduced. There are significant differences in the cash flow of long options versus short options, resulting from product-specific Skew bias and the interest rate built into calls, making them disparate compared to Puts.

14 Volatility revisited. Different expiration cycles between short term options and longer term options create an average of long term volatility, average volatility. When volatility exceeds its average, there is relative certainty that it will revert to its average. Likewise, the reversion to the mean is very likely because the volatility drops below its mean. The gyration around the mean is an identifiable characteristic. Noticeable volatility characteristics make it essential to forecast volatility over 30-day periods: 30-60-90-120 days, as the typical term is short credit spreads between 30-45 days and debit spreads long between 90-120 days. Reconcile implied volatility as a measure of the consensus volatility of all buyers / sellers for a given commodity, with inconsistencies in historical volatility and the predictive constraints of future volatility.

15 Futures contracts and options on stock market indices. Effective use of indexation to eliminate unique market risk. Separate treatment of risks for equity settled indices (including impact of dividend / exercise) separately from cash settled indices (no dividend / exercise). Explains the logic of theoretical pricing of options on stock index futures, in addition to pricing the futures contract itself, to determine what is economically viable to trade – the futures contract itself or options on futures contracts.

17 Position analysis. A more robust method than simply observing the Delta, Gamma, Vega, and Theta of a position is to use the relevant theoretical pricing model (Bjerksund-Stensland, Black-Scholes, Binomial) to scenario-test date changes. (daily / weekly) before expiration% of changes in implied volatility and price changes in and around +/- 1 standard deviation. These factors fueling the scenario tests, when graphed, reveal the relative Delta / Gamma / Vega / Theta risk ratios in terms of proportionality impacting the Theoretical Price of specific strikes composing the construction of a spread.

18 Models and the real world. Addresses the weaknesses of these fundamental assumptions used in a traditional pricing model: 1. Markets are not without friction: There are restrictions in buying / selling an underlying contract in terms of its tax implications, limitation of financing and transaction costs. 2. Interest rates are variable and not constant over the life of the option. 3. Volatility is variable and not constant over the life of the options. 4. Exchanges are not continuous 24/7 – exchange holidays result in price discrepancies. 5. Volatility is linked to the theoretical price of the underlying contract, not independent of it. 6. The percentage of price changes in an underlying contract does not result in a lognormal distribution of the underlying prices to 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 trading account, if you are:

  • Net Long more calls than bets, have you predicted an increase in implied volatility (IV), predicting a rise in the prices of the commodities traded in your portfolio?
  • Net Long more bets than calls, have you expected an increase in IV, expecting a drop in the prices of traded products?
  • Net Long an equal amount of calls and bets, did you forecast an IV increase, expecting a non-directional price drift?
  • Net Short more calls than putts, did you expect IV drop; but do you expect the prices to drop?
  • Net Short more bets than calls, did you expect IV drop; but, do you expect the prices to go up?
  • Net Short an equivalent amount of Calls and Puts, did you expect IV drop; but expect prices to drift in a non-directional way?


Comments are closed.