More Options Trades on Slow Days and Average Days Than Busy Days

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Please compare and contrast these two days. On September 29, 2008, the Dow fell 7.50 percent, the Nasdaq dropped 10.06 percent, and the S&P 500 dropped 9.63 percent. The Dow rose +6.25% from November 13, 2008, while the Nasdaq rose +6.11% and the S&P 500 rose +6.47%.

There would have been a mad dash for spread fills on large days like that among retail options traders. The few who knew that a day with a +/-X% change in equities was not a good day to enter the market but rather a signal to scale off profits or decrease exposure would have made gains or limited losses on those days.

The following reasoning can be used to classify the day. The product’s price has likely moved close to or outside 1 Standard Deviation, even if the order was placed at mid-price for that spread if you theoretically priced a long Calendar or a short Iron Condor on a Big Day (up or down).

If the next day were a Dull Day, the Futures wouldn’t change by more than a third within 1 Standard Deviation, regardless of whether the previous day was up or down. You overpaid for the Calendar on an extreme day you priced the entry, even if you were complete at mid-price, or you sold more Theta as premium than is necessary to defend the wing span of the short Iron Condor, possibly raising the risk of Gamma instability. If, on the other hand, you filled an order for a Short Vertical or a Long Vertical on a Big Day, you need a continuance in extreme days – beyond that Big Day – for the price to go in the direction you expected.

The price rising towards 2 or 3 Standard Deviations on a Big Day is not a worry if it has already moved 68% (1 Standard Deviation). The issue is as follows. After a great day, can the price action maintain a move of 2 or 3 Standard Deviations on subsequent days? It’s not unheard of, but it does happen rarely.

There is a lot of pressure on your orders to perform well due to the vast price gaps required for entry in extreme market conditions. Trading in such a manner is difficult. The trading account’s profit and loss are being unfairly impacted by your actions. Psychological and aesthetically, relying on Big Days to begin trades can lead to a constant quest for “magical” chart patterns signaling the next significant price movement. You won’t go blind, don’t worry. However, you must avoid developing harmful trading habits to achieve long-term success with online options trading.

So how do you calculate the X% increase or decrease that separates a Boring Day from an Average Day and a Big Day? Classify the day’s market ranges based on the implied volatility of the options for the next month’s DJX, MNX, and SPY mini-Dow, Nasdaq, and S&P 500 indexes. Just consider the following:

For the DJX, if the volatility in the first month is 27.38%, then 27.38% divided by 16 is 1.71%. That’s a range of +/- 1.71%, so market participants trading that product expects the DJIA to rise or fall by that amount on that day. The “%Change” field can be added to the watch list in most trading platforms. We just arrived at that conclusion. It’s a Boring Day when the %Change is less than +/- 1%. If the forecast is for a percentage change of +/- 1% to +/- 2%, consider the lower whole number 1% and the higher whole number 2% to be a “Normal Day.” An up or down day for the DJIA would be considered significant at +/- 2%. Due to the usage of a percentage rather than an absolute number, the definition of +/-%Change can be used for the Dow even if the DJX is the “mini” version of the Dow.
Let’s say the MNX front month IV is 30.73%/16, equating to a +/- 1.92% range. When the MNX’s %Change drops below +/-1%, it is considered a flat day. The MNX’s average daily %Change ranges from 1% to 2%. If the %Change is more than +/- 2%, it is an important day for the MNX. The Nasdaq has the same +/-%Change.
For the SPY, the IV for the first month is 31.25/16, or +/- 1.95 percent. Under 1% % Change in a Day = Boring. The daily percentage variation is typically between 1% and 2%. A significant day is defined as a day when the %Change is more than +/- 2%. The S&P 500 has the same +/-%Change.
The VIX or any other optionable product you have located in a potential trade can be used in this computation.

The volatility of the first month shouldn’t be divided by 16. As you may know, volatility is typically reported as a yearlyized figure. Divide this figure by the square root of the number of trading days in a year, which is 256 (rounded off), and you have the daily volatility. Weekends and exchange holidays mean no price movement and hence no trading. Although there are years with less or more than 256 days, the standard is to use 256. There are 16 in the square root of 256.

You should use a spreadsheet to determine the daily market ranges (Small, Medium, or Large) for the DJIA, NDX, SPY, and VIX as part of your pre-market preparation. This is not to pick a direction, as even if futures indicate an upside or downside bias, you cannot be sure that the market will open in that direction and remain there. After the call begins, the formula provides a quantitative indication of whether the day’s trading range is likely to be low, average, or high. Then, you need to decide if it’s worth your time to calculate the theoretical value of a spread, such as a Calendar, Iron Condor, Vertical, etc. This will protect you on the Big Day from having to chase prices down to fill your orders. When the market starts, your strategy for making money or minimizing losses depends on your work before the market opens.

There are fewer transactions to price on Big Days than on Dull Days or Normal Days. Most floor traders take a vacation from about the middle of July until the end of August. The aggressive pricing of an order by 0.10–0.15 below the theoretical price for a debit spread, or by 0.10–0.15 above for a credit spread, on dull and average days only adds around two to three hours to the time it takes to get filled. If your order gets fulfilled in less than five minutes, you probably weren’t putting in as much effort at the entry-level as someone who waits two to three hours. Careful preparation can significantly improve a trade’s returns. When you avoid entering the market on “Big Days,” when most retail traders are racing to get filled at any cost, you are not missing out on anything. The entry and exit prices you pay can significantly impact the profitability of your trading account. Maintaining discipline requires filling within a reasonable range of the spread’s fair value on any trading day. Online options trading is a business where it takes just as much common sense to avoid making trades as it does to make them.

I appreciate you taking the time to read my piece. Lee Clinton.

Creator of Home Options Trading, a brokerage that specializes in options trading for individual consumers.

For the Model Portfolio’s Performance Year to Date, updated at the end of each month, please visit Consistent Results ([http://www.homeoptionstrading.com/consistent_results/]). The portfolio simulates the investments of a retail options trader with a trading account of up to US$50,000. In a nutshell, these are the numbers:

The yield is 75.62%, or the profit divided by the cash at the beginning of the year. The odds of winning are 90.48 percent. A 9-1 win-to-loss ratio. The ratio of wins to losses is 3.09:1. The performance ratio is 90.48 times three dollars and ninety-nine times one loss, or 2.80. Earnings per deal = $1,051 (a positive expectation).

Visit [http://www.homeoptionstrading.com/original_curriculum.html] for a sneak peek at a 55-hour video-based course on online options trading from the comfort of your own home. If you buy the system, you’ll get a free $800 options introductory course as a bonus.

For the past 16 years, Clinton has worked in treasury, finance, and banking for many companies, including Hewlett-Packard, JP Morgan Chase, Citibank, and most recently, ABN Amro (bought by RBS) in Asia, where she was a corporate director for regional business development. His background in banking and finance did not equip him to trade options online from home, though.

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