Seasonality  Truth or Fooled by Randomness?

Seasonality Truth or Fooled by Randomness?

Posted on January 02, 2019
Market State – Transitional: The current Market Environment is volatile and irrational, somewhere between a bull and a bear.  The last two weeks have seen a volatile decline followed by a volatile increase.  As the market continues to fluctuate, it will either stabilize or continue into a bearish environment.
Canterbury Volatility Index (CVI 121): CVI 121 is higher than average and is mostly due to the large (5%) up day experienced the day after Christmas. Prior to this day, volatility measured CVI 108.  It then jumped by 17 points on the large outlier up-day.
I am not a believer in seasonality. Meaning, “As January goes so does the market.” “The market typically performs best during the 3rd year of a President’s term.” There is not enough statistical data to make such claims. Seasonality doesn’t really make logical since. If we knew that the month of October would be down, then investors would react in anticipation, and make September the down month. There was a famous book by Nassim Taleb, titled Fooled by Randomness. We humans tend to look for patterns or reasons for why things happen the way they do. Sometimes randomness doesn’t appear to be so random.

All that said, the Santa Clause rally came a little late this year by starting the day after Christmas. The last four days of the year saw the S&P 500 go up +6.62%! Don’t get too excited. The previous five days were down -7.66%. During that time, there were 5 consecutive days that should be statistically impossible to occur back to back, according to the bell curve: -1.54%, -1.58% -2.06%, -2.71% and +4.96%. Actually, the +4.97% day should statistically only happen about 1 time every 7,000 years. The truth is that these outlier days are not randomly distributed, and, when they do occur, they can be much more often and can be much larger than what academics and what Modern Portfolio theorists would predict.
Here is another point about markets. Markets do not perform on a predictable time table. In other words, markets do not know that they are supposed to hit their 10% average return on December 31 every year. In fact, over the last 100 years, ending on December 31st, the Dow has returned between 6% and 14% only 13 times! That is 13 times out of 100 years. The market has actually been down 27 of those 100 years.
Last year (2018), the S&P 500 was down -6.24%. If the year had ended 4 days earlier, it would have been down -12.79%. On December 24th, the financial news stations were acting like the financial world was coming apart. It was 1931 all over again., More than half of 2018’s loss was recouped only 5 days later.
Bottom Line:
Canterbury purchased 3 inverse ETFs (inverse ETFs go up when the underlying index goes down) prior to the decline, which began in October. These holdings helped cushion the decline. These actions were followed by making slight adjustments to increase equity exposure at key periods during the decline.

The big mistake made by most, is to get emotional and reduce market exposure after the first leg down and miss the eventual bounce. This is the mistake that cannot be fixed after the fact. The key is to have as much or more market exposure on the bounce as we had on the way down. We are now in position to continue the stabilization process to counter further market volatility.

Canterbury Investment Management: Tom Hardin

More About Tom Hardin

As Chief Investment Officer, Tom has more than 30 years of experience in the investment management industry and has a broad breadth of knowledge. He is known as an innovator, educator and has been revolutionary in the advancements of portfolio and risk management.

Every effort was used to provide accurate data and mathematical calculations to provide, what we believe to be, accurate results. Canterbury Investment Management, LLC, and its principal owners, make no guarantee of completeness or accuracy of data or calculations as well as conclusions of any statistical data or information contained in the simulation illustrated on this page. Past results or performance is in no way a guarantee of future results.