0Overview of Volatility Forecasting
Most traders think that high Implied Volatility is conducive for any short strategies. However, any high volatility might become even higher and low volatility might become even lower. And “high” and “low” are relative terms. Further, the Realized Volatility is also dependent on any news events that may affect the underlying stock. News events may be pertaining to government policies that affect the business of the company, or it could be any other macro-economic events such as central bank policy. The most popular event that could jack up the Implied Volatility as well as the Realized Volatility is the quarterly results event.
Short Strangle trades are best suited when you believe that the underlying stock might not trend in one direction, and might stay in a range. So, the Realized Volatility should either stay as is or decrease (but not increase).
Estimating the Distance that the Underlying Might Travel
In this section, we shall use the Realized Volatility to identify the Strike Prices that are safe to short. Before you read further, remember that for the purpose of picking the strike prices, we are concerned with the likely distance that the underlying might travel during the life of the option contract. So, we could use the Realized Volatility of the underlying or the Implied Volatility of the option’s at-the-money strike. Remember that the latter is forward looking while the former is based on past data. For trading any index, we could also use the VIX Index value as a proxy for Implied Volatility. VIX value is a forward looking volatility forecast. VIX values are published by the exchange in which the particular index is traded and is based on the Implied Volatility of a set of underlying stocks that are part of the Index.
Let’s take an example to illustrate how by using the Realized Volatility, we could estimate the distance that the underlying might travel. Say the underlying stock is trading at $100. The Forecasted Annual Realized Volatility is 25% (or 0.25). Let’s also assume that the volatility is in its 90th percentile (considered as high) and the Long Term Average Realized Volatility is 18%. It is well known that Volatility usually reverts to its mean or long-term average once the conditions that cause spike in volatility no longer exist. Therefore, we could expect the Realized Volatility to decrease or at least stay close to 25% but not increase. Now, we shall decide to sell the option contracts that will expire in 30 days. Therefore, we shall convert the Annual Volatility of 25% to a 30-day timeframe using this formula: Annual Volatility / Square root (number of days in a year / 30)
Substitution with the values, we get: 0.25 / square root (365/30) which is equal to 7.16%. 3.4880
This means that in a 30-days period, the underlying stock price might move plus or minus 7.16%, which is a 1 standard deviation move. Note that you can also use the number of trading days in a month (21) and year (252) instead of the calendar days shown here.
According to statistics, 68% of all the moves in the given period fall within 1 standard deviation, which in our example is 7.16% (in a 30-day period). Or, there is only a 32% chance for the stock price to move beyond or below 7.16% in a period of 30 days. Similarly, 95% of all moves fall within 2 standard deviations or 14.32%. This means that a move beyond or below 14.32% has less than 5% chance in a 30-day period. For more discussion about standard deviation rules, refer to this link: https://en.wikipedia.org/wiki/68–95–99.7_rule
These theoretical conclusions are not accurate though, and they depend on the stock price returns complying with the rules pertaining to normal (or lognormal) distribution. The Realized Volatility can also be used to derive the probability of the price closing above or below a specific Strike Price in a given period.
Remember that you can make the calculations we discussed by substituting the Realized Volatility of the underlying stock price with the Implied Volatility of the at-the-money Strike Prices.
Analyzing Implied Volatility
Let’s now focus on the Implied Volatility, which is the volatility exhibited by the option price. Traders believe that the Implied Volatility is a forward looking value. It can be derived by inversing the option pricing formula such as the Black & Scholes equation or by using the Binomial method. Let’s not worry about these formulas or the way we can derive the Implied Volatility. There are good tools that calculate the Implied Volatility for us in a jiffy. A lot of brokers, exchanges, and even financial websites such as Yahoo Finance publish this value in the option chain. The discussion on the relationship between historical and implied volatilities can take several hundred pages. Let’s however not waste our efforts getting to the details. What is relevant for trading purposes is what we shall cover. However, try to remember this logic:
If the Implied Volatility is extremely high compared to the Historical Volatility at a time when Historical Volatility is forecasted to revert to its mean (Average Volatility), then chances are that the Implied Volatility may gradually drop bringing down the value of the option. Remember that the Historical Volatility is considered high if it’s at or above its 90th percentile as seen in the cone as we discussed earlier in this book. When you notice that the option price is not moving in tandem with the stock price it is a confirmation that the Implied Volatility along with the Historical Volatility is dropping towards their average levels.
