As with most books on the topic of how to trade options, the amount of material to get through can be daunting. For example, with Sheldon Natenberg’s Option Volatility and Pricing, it is about 418 pages to digest.Thank you for reading this post, don't forget to subscribe!
There are adequate reader reviews on Amazon and Google Book Search, to help you decide if you will get the book. For those who have just started or are about to read the book, I’ve summarized the core concepts in the larger and essential chapters to help you get through them quicker.
The number on the right of the title of the chapter is the number of pages contained within that chapter. It is not the page number. The percentages represent how much each chapter makes up of the 418 pages in total, excluding appendices.
1. The Language of Options. 12, 2.87%.
2. Elementary Strategies. 22, 5.26%.
3. Introduction to Theoretical Pricing Models. 16, 3.83%.
4. Volatility. 30, 7.18%.
5. Using an Option’s Theoretical Value. 14, 3.35%.
6. Option Values and Changing Market Conditions. 32, 7.66%.
7. Introduction to Spreading. 10, 2.39%.
8. Volatility Spreads. 36, 8.61%.
9. Risk Considerations. 26, 6.22%.
10. Bull and Bear Spreads. 14, 3.35%.
11. Option Arbitrage. 28, 6.70%.
12. Early Exercise of American Options. 16, 3.83%.
13. Hedging with Options. 16, 3.83%.
14. Volatility Revisited. 28, 6.70%.
15. Stock Index Futures and Options. 30, 7.18%.
16. Intermarket Spreading. 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 makes up about 66% of the book. These chapters are relevant for practical trading purposes. Here are the key points for these focus chapters, which I’m summarizing from a retail option trader’s perspective.
4 Volatility. Volatility as a measure of speed in context of price in/stability for a given product in a particular market. Despite its shortcomings, the definition of volatility still defaults to these assumptions of the Black-Scholes Model:
1. Price changes of a product remain random and cannot be engineered, making it impossible to predict price direction prior to its movement.
2. Percent changes in the product’s price are normally distributed.
3. As the product’s price percent changes are counted as continuously compounded, the product’s price on expiry will become lognormally distributed.
4. The lognormal distribution’s mean (mean reversion) is to be found in the product’s forward price.
6 Option Values and Changing Market Conditions. Use of Delta in its 3 equivalent forms: Rate of Change, Hedge Ratio & Theoretical Equivalent of the Position. Treatment of Gamma as an option’s curvature to explain the opposite relationship of OTM/ITM strikes to the ATM strike having the highest Gamma. Dealing with the Theta-Gamma inverse relationship, as well as Theta being intertwined synthetically as long decay and 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 on the effects of Gamma and Vega.
9 Risk Considerations. A sobering reminder to select spreads with the lowest aggregate risk spread versus the highest probability of profit. Aggregate Risk as measured in terms of Delta (Directional Risk), Gamma (Curvature Risk), Theta (Decay/Premium Risk) and Vega (Volatility Risk).
11 Option Arbitrage. Synthetic positions are explained in terms of manufacturing an equivalent risk profile of the original spread, using a mix of single options, other spreads and the underlying product. Clear caution that transforming trades into Conversions, Reversals and Adjustments are not risk-free; but, may raise the trade’s nearer-term risks even though the longer-term net risk is lowered. There are material differences in the cash flows of being long options versus short options, arising from the Skew bias unique to a product and the interest rate built into Calls making them disparate against Puts.
14 Volatility Revisited. Different expiry cycles between near-term versus longer-term options creates a longer-term volatility average, a mean volatility. When volatility rises above its mean, there is relative certainty that it will revert to its mean. Likewise, mean reversion is highly likely as volatility drops below its mean. Gyration around the mean is an identifiable characteristic. Discernible volatility traits make it essential to forecast volatility in 30 day periods: 30-60-90-120 days, given the typical term to be short credit spreads between 30-45 days and long debit spreads between 90-120 days. Reconcile Implied Volatility as a measure of consensus volatility of all buyer/sellers for a given product, with inconsistencies in Historical Volatility and predictive constraints of Future Volatility.
15 Stock Index Futures and Options. Effective use of Indexing to remove single stock risk. Distinct treatment of the risks for stock-settled Indexes (including impact of dividend/exercise) separate from cash-settled Indices (absent of dividend/exercise). Explains logic for Theoretically Pricing the options on Stock Index Futures, in addition to pricing the Futures contract itself, to determine which is economically viable to trade – the Futures contract itself or the options on the Futures.
17 Position Analysis. A more robust method than just eye balling 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 for changes in dates (daily/weekly) before expiration, % changes in Implied Volatility and price changes within and near +/- 1 Standard Deviation. These factors feeding the scenario tests, once graphed, reveal the relative ratios of Delta/Gamma/Vega/Theta risks in terms of their proportionality impacting the Theoretical Price of specific strikes making up the construction of a spread.
18 Models and the Real World. Addresses the weaknesses of these core assumptions used in a traditional pricing model: 1. Markets are not frictionless: buying/selling an underlying contract has restrictions in terms of tax implications, limitation on funding and transaction costs. 2. Interest rates are variable, not constant over the option’s life. 3. Volatility is variable, not constant over the options’ life. 4. trading is not continuous 24/7 – there are exchange holidays resulting in gaps in price changes. 5. Volatility is linked to Theoretical Price of the underlying contract, not independent of it. 6. Percentage of price changes in an underlying contract does not result in a lognormal distribution of underlying prices at distribution due to Skew & Kurtosis.
To conclude, reading these chapters is not academic. Understanding techniques discussed in the chapters must enable you to answer the following key questions. In the total inventory of your trading account, if you are:
- Net Long more Calls than Puts, have you forecasted Implied Volatility (IV) to increase, expecting prices of the traded products in your portfolio to rise?
- Net Long more Puts than Calls, have you forecasted for IV to increase, expecting prices of traded products to fall?
- Net Long an equivalent amount of Calls and Puts, have you forecasted for IV to increase, expecting prices to drift non-directionally?
- Net Short more Calls than Puts, have you forecasted IV to fall; but, expect prices to fall?
- Net Short more Puts than Calls, have you forecasted IV to fall; but, expect prices to rise?
- Net Short an equivalent amount of Calls and Puts, have you forecasted IV to fall; but, expect prices to drift non-directionally?
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