Selling naked options on an exchange-traded fund (ETF) has an advantage over selling an individual stock option. In terms of their vulnerability to market surprises, ETFs are usually safer than individual stocks. One stock may take a big hit because of isolated bad news (earnings, litigation, scandals, etc.), but it is less likely that an entire index will suffer.
A case in point is the collapse of Bear Stearns Companies (BSC) in March 2008. BSC is a component of the SPDR Financial Sector ETF (XLF). While BSC dropped to 4.81 from 61.58 between March 11 and March 17, the XLF dropped only to 23.45 from 24.76. In percentage terms, the difference is even more striking — 92.2% for BSC vs. a relatively minor 5.3% for the index-based ETF.
Clearly, for the naked put seller, a 5.3% drop is more manageable than a 92.2% drop. That being said, there are about 600 ETFs compared to thousands of stocks, and only the most active and liquid ETFs should be used for selling naked options. Only these ETFs have the tight bid/ask spreads that are necessary for reliable execution results.
The liquidity requirement eliminates most of the ETFs with an average daily volume less than a few thousand shares. Now the question is, which active ETFs should be selected for an option-selling program? An ETF is normally composed of different stocks in a sector. If an individual investor has strong feelings that a certain sector, for example, the oil sector, will continue to do well, then perhaps that individual should just concentrate on that sector. We can compare several ETFs based on quantitative analysis to find those that have the most potential profit per month while still minimizing risk.
The most active ETFs are shown in “Liquid markets.” Although each of these ETFs is liquid enough for an individual trader, the volume figures drop considerably outside of the top three, falling more than 50% again from the fourth to the fifth option on the list.
Usually, when considering a derivative strategy, the best measure of an underlying’s effectiveness is the derivative itself. So, in our search for the best ETFs, we will go straight to the options themselves. Here are the rules used to compare the selected ETF options:
1. Naked puts that are 10% out-of-the-money (OTM) will be sold on each ETF
2. Enough shares of each ETF will be sold to produce a potential profit of $1,000
3. The time frame is one month (third Friday to third Friday)
All price data were obtained on May 23, 2008, for the June expiration, which was four weeks away at the time. A performance summary on these five most liquid ETFs is shown in “Profit comparison.”
Note that the margin required is not borrowed money like stock margin. It is basically 15% of the underlying market value of the short position. The margin and projected profit will change with market conditions. The XLF position provides the best profit potential of 7.7% per month, at the time of order execution.
However, this simple analysis does not factor in the volatility and the risk. Beta is a measurement of an investment’s volatility, or risk, as compared to the S&P 500. Assigning the S&P 500 a beta of one, a security has a beta of 1.5 if it has 50% more risk than the S&P 500. For example, if ETF X was priced at $100 with a beta of 1.00 and ETF Y also was priced at $100 and had a beta of 2.00, then if the market dropped by 10%, X would drop to $90 and Y would drop to $80.
Beta can be confusing, particularly as different Web sites list betas that vary widely for the same security. This variance is due to each site choosing to calculate beta over a different, arbitrary time period. The beta found on Yahoo! Finance has a pretty good description of how they compute the beta. From http://finance.yahoo.com , enter “spy” in quote box, then click on “Risk” in the left column. It has the beta and statistics for a three-year, five-year and 10-year period.
The table “Measuring risk” integrates this risk measure into the calculation of an OTM strike. The procedure first computes the 10% OTM strike and then modifies it by beta. For example, with an SPY 10% OTM, QQQQ is 15.7% OTM because of the higher beta. XLF provides the highest potential profit (7.1% per month) with the beta modification.
PROBLEMS WITH BETA
While beta is one measure of risk, it is important to realize that it is based on historical data and can be misleading in some market conditions.
A related way to determine the risk of an investment is by examining volatility. You can calculate volatility by looking at how much a security varies in a month (or a given time period). There are two types of volatility: historical volatility, which is based on a given time period and implied volatility, where a model (such as Black-Scholes) computes the figure based on the current option price, the current market price of the underlying and other factors. Many traders consider implied volatility a more accurate measure.
A reliable source for implied volatility data is www.optionseducation.org. At the site, go to the top menu bar and click “Quotes.” In the second symbol box (under Basic Option Calculator), enter “spy,” and click “Go.” The current price of SPY, the at-the-money option, implied volatility, the current interest rate, etc., are displayed. For SPY, we want the implied volatility of the sold option (strike 130). Move the arrows next to the strike to re-calculate.
Another good site for this data is www.optionistics.com/f/stock_quotes . The volatility provided there is an indexed volatility. It is an average of the implied volatilities of those option contracts that are near the money.
Volatility is usually expressed in annual terms, and represents a one standard deviation move in the underlying. A rule of thumb states that, for a normal distribution, 68% of the values lie within one standard deviation of the mean, about 95% of the values lie within two standard deviations of the mean, and almost all (99.7%) of the values lie within three standard deviations of the mean.
So, 68% of the time, a stock with an implied volatility of 24% will theoretically be between up 24% and down 24% in one year. However, for our purposes, we need to know how much it will move in a month. The standard deviation increases proportionately to the square root of time. So, if there are 252 trading days in a year, we must multiply 24% by the square root of 20/252 to get one standard deviation for one month (20 trading days); the result is approximately 6.8%. Therefore, in one month, 68% of the time the stock will theoretically be between up and down 6.8%.
“Monthly volatility” uses the monthly one standard deviation figure to compute the OTM strike (strike = price - price * IV). Again, the strongest performance is XLF based on the potential OTM put premium profit.
Now, let’s examine how each stock reacts when something goes wrong. What if the market does drop to the strike of the naked positions? A simple reaction is to simply buy back the naked positions. In “Off the table”, current ATM option prices are shown in the “Option price” column. While it is unknown what the exact ATM option price would be in this situation, it is assumed that all ATM prices for the ETFs would be adjusted by the same factor (plus or minus). Thus, a relative comparison can be made.
SPY has the smaller cost to close; therefore, by this measure, it provides the least risk for a naked option position.
That said, in the big picture, for the more aggressive investor, XLF appears to be the best choice. It has the largest profit potential and middling closeout risk. However, consider this information more educational and less instructional. Scenarios change with market conditions, and the best ETF today may not be the best ETF tomorrow.
Tony Elenbaas and David Tsou are software engineers and independent option traders. E-mail them at email@example.com and firstname.lastname@example.org.