09 Jan Constraining Chaos – Part One
cha·os - behavior so unpredictable as to appear random, owing to great sensitivity to small changes in conditions.
Many events tied to organic and non-organic matter appear to be chaotic: Bees hovering around a hive, a handful of pebbles bouncing around on the face of an audio speaker, the flip of a coin, etc. Upon closer inspection, we know that what can sometimes seem random, is really just complex mathematical statistics playing with our sense of perception. Humans were not designed to "see" complexity all that well. We have evolved to make the best quick assumption of our current perception of reality in favor of quicker decision making; i.e., our fight or flight response.
To many, the stock market, along with the price action related to securities, seems very random. Tiny little blips of green and red flash along with lightning speed filling the screens with a blur - not to mention, stocks that go down on good fundamentals, while others with horrible balance sheets and no earnings go straight up - it almost seems like there is no rhyme or reason to any of it.
Enter the term: Standard Deviation. If we think of chaos in terms of what is or isn't probable, we get a bigger picture view of what is or isn't going on and with a level of frequency. Things that happen more frequently can be plotted against things that happen less frequently.
If we have a look at a graph describing rainfall at certain times, we can see that "normal" rainfall occurs the most frequently and at the outside of the curve (the standard deviations, or "tails") we see how to plot the times when there is much below/above normal rainfall, etc.
Using this type of visual, it starts to become more clear that within something that seems random, there are groups of occurrences that can be plotted against each other. If we take it a few steps further and with a little more inspection we can assign levels of probability to these events.
What does rainfall have to do with the stock market? Well, if we revisit the notion of price action in the markets, we can observe that securities are not necessarily random and that all prices within a security also has standard deviations from its mean price.
The options market arrives at its prices for strike prices in this very manner - at lightning speed. Strike prices that are further away from the money, which have a less likelihood of being "in-the-money" cost less because they have a lower perceived probability becoming profitable, according to the general consensus of the options market along with its formula for calculating these prices.
The basic gist of this is: Selling these out-of-the-money options have the greatest probability of success, speaking from a mathematical point of view. However, there is always a trade-off - with greater probability of success comes greater risk if one of these "standard deviation" outlier events happen. Meaning that the trader "selling" this premium is taking on the risk of one of these events wiping out months or sometimes years worth of steady gains.
"So how do I get the best of both worlds? I want to sell these out-of-the-money options for small profits and protect myself from the big cataclysmic event that will bankrupt my account!"