This article from the CFA (Chartered Financial Analyst) Institute by Harry S. Marmer, CFA is chock full of graphs that quickly dispel some widely held views. One is that market “cycles” are really not cycles at all but are, rather random fits and starts that are characterized in the article as “episodic”. “Predicting the duration of the business cycle was aptly summarized by noted business-cycle analyst Victor Zanorowitz, who said, ‘Few business cycle peaks are successfully predicted, indeed, most are publicly recognized only with lengthy delays.'” So much for analyst humor.
The graph of 155 years of US business cycle history shows a “typical” average length of 4.7 years but with a standard deviation of 2.2 years. “In other words, the underlying length of the business cycle has broadly ranged anywhere from 2.5 years to 6.9 years 68% of the time.” The bar chart in the article looks like a silhouette of a major downtown city skyline. Because of this unpredictability in business cycles, investors “should avoid investment and policy decisions (based upon predicting market cycle turns).”
The shape of stock return distributions from the last 89 years resembles a fat rocket ship on a plain. The sharpness of the graph is called its “kurtosis”. “The kurtosis from this distribution is 9.7; a normal distribution has a kurtosis of 3”, that is like the “bell curve” we all heard about in high school. The plain of the rocket ship is there to report a -30% on the one side and a 42% on the other side. The shape of the curve is due to “the fact that stock returns are characterized by jumps. More specifically, financial prices tend to “jump, skip, and leap” up and down rather than change in a continuous fashion.” How many of us have heard colleagues talk about “trends”, “price supports”, and “floors and ceilings”? These are empirically fictitious. Who among us could say with any accuracy what the Mean, Median, or Standard Deviation is of the monthly returns of the S&P 500? Here you have it. The Mean is .94%, the Median is 1.21% and, GET THIS: the Standard Deviation is a whopping 5.46%. That means that 68% of the time, the range is between 6.4% and -4.2%. The high is 42.98% and the low is -29.61. The probability of seeing the extremes of the distribution are about .1% judging by the graph.
“Why do markets behave in this fashion?” These are most likely caused by “traits in the world outside the markets or ‘exogenous’ effects”, says noted mathematician Benoit Mandelbrot. The lemming effect or “investor behavioral biases” is also cited as “a primary driver of the heavy or fat tails in asset class return distributions. That is a very high summit to scale. On the one hand we have “real world” events, both physical and financial to have to contend with and, on the other hand, irrational investors if we are to be successful in market timing. Indeed, as the article goes on to say, “Nobel prize winning economist Paul Samuelson described the challenges in market timing best: ‘Scores of documented statistical studies attest that not one in ten ‘timers’ ends up getting back into the market at bargain prices lower than what they sold at earlier.'” So much for market timing.
Indeed, the “Opportunity Costs of Missing Market Performance: $1,000 Invested” bar graph in the article shows that investors who bought and held their portfolios for the 10 year period ending July, 2016 in the S&P 500 gained an annual average of 7.4% or cumulatively $1,046 while those who missed just 10 of the best days saw a .3% or $33 cumulative gain. It gets worse as the hapless investor, trying to escape downturns buys and sells in and out of the market until the worst in the chart, 40 best days missing loses 10.3% on average annually or $664 cumulatively.
Marmer finishes the article by advocating “implementing a disciplined rebalancing policy back to the long-term policy mix (over market timing).” That is the investment strategy of Jim Hannley LLC because I exercise discipline and I look for rebalancing opportunities in my portfolios daily.