What is normal distribution?
The most common way to understand volatility is through a statistical technique called standard deviation. For standard deviation to be correct, the performance of an investment option should follow a normal distribution.
If you own individual stocks, you might notice that they experience constant price changes over a given period, while other commodities are relatively stable. This is what you call capital “volatility.” Depending on your willingness to take risks, you might panic when the prices behave erratically.
Is there a way to predict stock volatility? Unfortunately, there is no definitive way to know when a stock is going to go up or down. All we have are probabilities. Probabilities help us figure out the likelihood of something happening or not. To a certain extent, they help us learn the possibility of prices skyrocketing or plummeting.
Normal distribution as a measurement of risk
While the statistics surrounding normal distribution are easy to calculate, its underlying assumption is way more complicated. In fact, a lot of investors are skeptical about normal distribution’s ability to measure risk accurately. Three factors affect a stock’s performance: skewness, kurtosis, and heteroskedasticity.
Big words, but it’s just a statistician’s way of saying, “I don’t know for sure.”
- Skewness: In the real world, investment performance is sometimes asymmetrical. In a skewed distribution, investors will experience exceptionally high and low-performance periods.
- Kurtosis: There are times that investment performance is said to be kurtic. In a normal distribution, the tail end of the production is equal to 3. In a kurtic performance, the tail end is either higher or less than 3. In this case, investors will experience an abnormally huge number of positive or negative return.
- Heteroskedasticity: It is common knowledge among investors that performance data does not remain constant. It will fluctuate, and depending on the length of time or the period in which you took the sample, standard deviation also varies.
If you take these factors together, you will see that you will not get a perfect bell-shaped curve in your graph. It means that you have a distorted picture of the actual risk of your investment. These three factors taken together will cause you to misunderstand volatility, and could potentially lead you to make a wrong investment decision.
What should you do as an investor?
Although its accuracy is a bit questionable, you can still use standard deviation and normal distribution to measure volatility. You just have to be mindful that performance of investments doesn’t always follow a bell-shaped normally distributed graph. At times, it can be skewed, kurtic or heteroskedastic.
Depending on the what kind of an investor you are, volatility may or may not play a significant role in your success. If you follow the buy-and-hold strategy, you can use a normal distribution to weed out extremely erratic investments. Low volatility can mean huge profits over an extended period because it gives you the opportunity to buy stock from stable companies at low prices. All you need to do is wait for its cumulative growth as the company grows.
If you’re a short-term trader, you can use the same technique to do the opposite. Instead of looking for less volatile investments, you’d want to spot the highly volatile ones because it is in the constant changing of prices that you earn your profit. Lastly, you have to remember that volatility is not the only predictor of your success. You also need to be watchful of other more significant economic and financial events.