Explore Your Options

with Tom Gentile

Tom Gentile Portrait

Got a question about options? Tom Gentile is the chief options strategist at Optionetics (www.optionetics.com), an education and publishing firm dedicated to teaching investors how to minimize their risk while maximizing profits using options. To submit a question, post it on the Stocks & Commodities website Message-Boards. Answers will be posted there, and selected questions will appear in future issues of S&C. Contributing analysis is by senior Optionetics strategist Chris Tyler.

How can I best ensure against slippage on an option order?

If you’ve been trading long enough, you probably have learned about slippage the hard way. Two good ways to guard against this enemy of profits is to deal in options with strong liquidity characteristics and stay clear of market orders whenever possible.

As for a stock’s options providing strong liquidity: Average daily contract volume, large open interest, and tight quoted call and put markets are the three components that we can use as measures against unjust slippage. Having one of these characteristics in place is no guarantee of the other two. Without all three in place, without a contract month that’s new to the board, there’s a strong chance that what looks to be worth trading today, all else being equal, might not be so at a later date.

In addition, you might want to go back to earlier trading sessions and look at contract volume on any given day. Knowing how both larger and smaller traders are vested is better than a situation with the same volume but with all the activity stemming from one group. Block prints that occur with regularity can paint a distorted picture of liquidity, for example, as could a large amount of retail trading that’s there one day but gone the next due to the likes of a newsletter recommendation.

In the end, slippage costs us capital as it takes away from our bottom-line results. Fortunately, traders can run scans to weed out slippage risk. A simple starting point would be to use a benchmark 50-day simple moving average of option activity in a stock trading 3,000 contracts on a daily basis. You may want to use this as a filter on stocks already on your watchlist, whether the common bond is upcoming earnings, a sector of interest, or some sort of technical or fundamental correlation.

Your broker or software platform might also allow you to put in option-related parameters such as the average spread or bid/ask percent distance for near-the-money options. In my experience, 5% to 7%, along with a stock that trades more than 3,000 contracts daily, should provide the type of environment in which your orders have the opportunity to get filled midmarket or for essentially fair value and remove potential slippage issues both entering and exiting.

In the end, slippage costs us capital as it takes away from our bottom-line results. Another way to avoid slippage is to use limit orders rather than market orders. Remember, you can always place a limit price that’s below the current market for a sale or above the offered price for an option or spread that’s being purchased. Unlike with a market order, a limit order allows traders to know what their worst-case fill would be when an order gets executed outside the quoted market. If a trader is unrealistic about the limit or uses the order during a fast or unstable market condition, he or she runs a risk of not receiving a fill.

How can an option be priced at one volatility level and the underlying movement of a stock trade at a different one? Shouldn’t traders be able to exploit this phenomenon somehow?

What you’re seeing is largely due to traders’ collective forecast of a stock’s or index’s underlying movement. Essentially, implied volatility is how traders vote on what they think about both current and future market conditions, which might include a catalyst such as earnings or an FDA announcement that’s anticipated to move shares dramatically.

The pricing of implieds could also be the result of information unknown to you and me. Despite the leveling of the market’s playing field in recent years, the surface can still be uneven at times.

A second factor causing a disparity in volatility levels could be the hedging assumption in the pricing of volatility. A pricing model like Black-Scholes assumes perfect hedging scenarios and continuous prices at which traders can shift their deltas at a moment’s notice without incurring real-world inconveniences such as fast markets or price gaps.

That said, what statistical volatility is supposed to be on paper versus how it might be traded consistently can be two different animals. A $50 stock might show an average trading range of three points daily over an extended period but trade in a much narrower range for 95% of the session. If a good portion of each day’s trading range is unavailable to trade for whatever reason, premiums will look deceptively cheap.

At the end of the day, if the traders’ long premiums aren’t able to manage their time decay effectively, the net result could manifest itself in deceptively cheap-looking implieds versus the reported underlying volatility.

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