Because there are S&P 500 futures-related moves in the market on a daily basis, I have found it extremely valuable to utilize current options' implied volatility and its inherent statistical characteristics to identify high-probability trading levels.
There are two kinds of volatility: implied and historical. The implied volatility (IV) of an option is a perception of how the underlying stock will trade in the near future. The historical volatility (HV) measures the percentage price changes over a particular time period (20 days, 100 days, and so on). The IV tends to track the HV but often will differ because of the current perception of a particular stock and the overall market.
Applying volatility to short-term trading
I use the following strategy simply to find a trading level for day trading. Any dangers of IV have no effect because it's only for one day. There are no options positions involved.
- Calculate the combined IV of the most current at-the-money (ATM) call and put for a stock.
For our example we will use GE, which closed at 119 on September 22, 1999. The Oct. 120 call had an IV of 28% and the Oct 120 put had IV of 26.7%.
- Add the two IV's = 28% + 26.7% = 54.7%, and divide by 2 for a combined IV of 27.4% (.274).
Statistically, this combined IV can mean there is a 68% probability that GE will trade between 27.4% above and below 119.
- Convert the 27.4% combined IV to a trading range by multiplying .274 times the closing price, or .274 * 119 = 32.60 points. Then subtract this figure from the close to determine the lower boundary of the range (119 - 32.60 = 86.4) and add it to the close to determine the upper boundary of the range (119 + 32.60 = 151.60). This range tells us there is a 68% probability (one "standard deviation") that GE will trade between 86.4 and 151.6 over the next 365 days.
- Convert the annual volatility figure to a one-day figure. As day traders we want to convert the combined IV of 27.4% to a one-day range. One standard deviation would be 1.0 * 2.74, but we will create a range that reaches out two standard deviations, which has a 95% probability of containing price moves.
The key point about volatility is that, sooner or later, it will revert to the mean. This is why you should look for a reaction in the stock at the various standard deviation (SD) levels.
Standard deviation and probability
The following probability estimates for various volatility standard deviation levels should be your guideline for determining daily trading bands at which the stock might react.
Table 1
Standard
Deviation (SD) | Probability |
|---|
| 1.0 | 68% |
| 1.28 | 80% |
| 1.5 | 87% |
|
2.0 | 95% |
In our GE example, we saw the 365-day trading range using a 1.0 standard deviation of the combined IV of .274 has a 68% probability of trading between 86.4 and 151.60.
- 1.0 * 2.74 = 0.274 * 119 = 32.60
- 119 + 32.60 = 151.60 upper range
- 119 - 32.60 = 86.40 = lower range
An extreme move would be 2.0 standard deviations, or 95% probability (see table) of trading between 184.21 and 59.70
- 2.0 x .274 = 0.548 x 119 = 65.21
- 119 + 65.21 = 184.21 upper range
- 119 - 65.21 = 59.79 lower range
As you can see, a two-standard deviation move would be very strong for GE.
Continuing the GE example
You should now feel comfortable calculating a trading range for 365 days using the combined IV of both the at-the-money (ATM) call and put. Table 1 gives you the probability of the stock trading between your calculated range using various standard deviations (SD) of the combined IV. Now, we must convert this to a one-day trading range for GE at various SD levels.
The first thing you do is to find the square root of the number of days divided by 365. For this example, it is the square root of 1 day/365, which is 0.0523421. The next step is to find the trading levels related to the various SD numbers.
Example: GE closed at 119 on September 22 with a combined IV of 27.4% (.274).
- 1.0 SD * .274 * 119 * 0.0523421 = 1.70 points
- 1.28 SD * .274 = .35 * 119 * 0.0523421 = 2.18 points
- 1.50 SD * .274 = .41 * 119 * 0.0523421 = 2.56 points
- 2.0 SD * .274 = .548 * 119 * 0.0523421 = 3.41 points
Table 2
| Probability | SD | Price bands* |
|---|
| 95 | 2.0 | 122.41 |
| 87 | 1.5 | 121.56 |
| 80 | 1.28 | 121.18 |
| 68 | 1.0 | 120.70 |
| close | 9/22/99 | 119 |
|---|
| 68 | 1.0 | 117.30 |
| 80 | 1.28 | 116.82 |
| 87 | 1.5 | 116.44 |
| 95 | 2.0 | 115.59 |
(*Subtract or add the band points to the stock price to determine the trading band. The 1.0 price band is 117.30 (see table above) calculated by 119 - 1.70 = 117.30)
Key Point: From my observation, about 80% of all the market-related moves are contained within the 1.28 SD band.
Figure 1 shows a five-minute chart of GE on September 22, 1999. GE opened at 119 1/2 and traded down to 117 3/16, which is just between the 1.0 and 1.28 SD levels. Buyers showed up and GE gave good entry at 117 3/4 and again at 118 1/8. If you were very aggressive and the dynamics were good, you might have taken a position at 117 1/2 as GE moved back over the 1.0 SD level of 117.30.
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Figure 1. General Electric (GE), five-minute. Source: Quote.com.
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This is an excellent method of spotting good trade opportunities during the day, but it also can be used for other time periods and strategies. It's especially effective when used in conjunction with Fibonacci ratios.
Remember, don't take a position blind at the trading bands. There must be some reversal pattern out of the level as the stock and market dynamics tell you it's a go.
