On October 19, 1987, the stock market fell 29%.
Dramatic evidence of risk.
Investment risk means variability. How wide is the track that returns follow over time.
People often see the October 1987 number and assume it has some meaning. It did for those who participated but, it is not the kind of change that people should think of as investment risk. It must be something else.
Investment theorists have physics envy
There is a tendency among many financial practitioners to make believe physics and its rules are parallel to similar rules that cover finance. The finance rules have become based on probabilities not deterministic laws. A bit like quantum mechanics.
The efficient market hypothesis
Some economists and other practitioners believe the market is “efficient.” All relevant information is already priced in. Changes in price are fluctuations around this efficient value and they are random.
Standard deviation (sigma) is a statistical measure of variance. In a true normal distribution, about 68% of the observations will lie within one sigma. 99% within 3 sigma. A 6-sigma event is about one in a million.
Impossible events like October 1987 make it likely that the statistical rules in finance fall short
The October 1987 event is not possible really. It is about a 21 sigma event. The probability of its occurrence is about 1 in 10 to the fiftieth power. A one after 49 zeroes behind the decimal. A smallish number.
If the stock market had been open ever day since the beginning of the universe, this event would still be about a one in 10 to the 38th probability. Equally impossible. If there were a trillion trillion universe just like ours, each with a stock exchange open for as long as ours, it would still be extremely unlikely to have occurred.
High sigma events abound.
If stock market returns were truly a normal distribution, a six sigma result would occur about once every 4,000,000 years. The stock market is not normally distributed. Instead of 68% of the daily results within one sigma, there are nearly 90% within one sigma. It is very steep distribution with lumpy tails. Its 6-sigma events occur about once every 800 years, theoretically.
In whatever distribution describes the market, a 6-sigma event is unusual.
There have been several events with sigma values higher than 10. It is not always down either. 13 October 2008 was a plus sigma just under 12.
It is not only the stock market.
When the Swiss unpegged the Franc from the Euro, the result was an event registering 58-sigma. After the Brexit, vote the pound suffered a 15 sigma drop.
The reasonable conclusion
There are some events or facts that are not priced into market results. If an event that is supposed to happen once in 800 years happens every few months or many times in a short period like the autumn of 2008, you should be less tolerant of statistical artifacts.
The future is about possibilities not so much about probabilities. You cannot predict with certainty. As the folks at Long Term Capital Management discovered, impossible events happen.
Don’t rely on numbers alone.
You can prepare
Diversity in your portfolio will help. That will give you some capacity to deal with a fall and simultaneously reduce your exposure. Hold some cash.
Attitude matters. If you can accept the idea that there will be large fluctuations in value, you can prepare to buy when the drop occurs. Keep your purpose connected to your thinking about the markets.
Common sense tells us that there is no tactic that includes all possibilities. Be vigilant.
There are more things in heaven and earth, Horatio,
Than are dreamt of in your philosophy.
Hamlet – Act I, scene 5.
Don Shaughnessy arranges life insurance for people who understand the value of a life insured estate. He can be reached at The Protectors Group, a large insurance, employee benefits, and investment agency in Peterborough, Ontario. In previous careers, he has been a partner in a large international public accounting firm, CEO of a software start-up, a partner in an energy management system importer, and briefly in the restaurant business.
Please be in touch if I can help you. email@example.com 866-285-7772