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Patterns in financial markets are related to human behavior, the business cycle, and long cycles of inflation
My post on Monday presented the results of some statistical analyzes I performed on a database of monthly inflation-adjusted US stock and bond returns going back 170 years. Yesterday’s post was for those who wanted or needed to understand randomness and the normal distribution in a more formal sense.
Today I’ve laid out my thoughts on how to interpret the patterns found in my analysis: what they mean for investors, how they can be used to improve portfolio returns, and more. This will include reference to the normal distribution – randomness – and the momentum and mean reversion patterns that were the subject of yesterday’s explanatory post.
There are still a few charts in this post, but many were introduced in Monday’s and yesterday’s posts and annotated below.
To recap, based on 170 or so monthly inflation-adjusted returns for stocks and bonds, I calculated for each the average monthly return – the mean – and the variation – the standard deviation. I then constructed a simulated series of stocks and bonds based on the means and standard deviations of the actual series. Since the mean and standard deviation were the only parameters used to construct the simulated series, this ensured that they were random walks with which the actual series could be compared.
One hundred 30-year periods were then randomly selected from each of these four 170-year series – Stocks/Actual, Stocks/Simulated, Bonds/Actual, Bonds/Simulated – Chart 1 shows how this was done in relation to the actual series capital.
Four sets of one hundred 30-year periods have been plotted on top of each other – charts 2-5 below, with the upper and lower 1 standard deviation ranges colored in red. If all 100 selected periods correspond to random walks, 68% of them fall into the red lines, i.e. within +/- 1 standard deviation.
Charts 2 and 4 – the two simulated series – show that about two-thirds of the series fall into the red lines, which is quite logical given that they were generated from random walks, i.e. 68% should be within +/- 1 standard deviation. I have marked them with a green bell curve, which represents a normal distribution ie. random wandering.
Charts 3 and 5 show actual stocks and bonds, respectively.
In terms of actual stocks, for the first 4 years or so more of the 100 periods were outside the red lines than they should have been if they were following a random walk. After that, too few of them are outside the red lines. These two different periods have been marked with red and blue bell curves representing the impulse and the mean, respectively.
In real bonds, there is a clear momentum pattern for the first 15 or so years, followed by a number of years in which they are essentially a random walk, then around the 25 mark they begin to show mean reversion.
I find these results fascinating because while it is known, accepted and understood that bond returns are lower than stocks – 2.2% vs. 6.4% – and that they are less volatile over short periods, the corresponding patterns that emerge in each period longer periods show a less clear distinction between the two asset classes.
Namely, that the monthly cycles in equity markets are much shorter than those in bonds, perhaps 4-6 years versus 25-30 years – in many ways this discovery would be obvious from a glance at Charts 1 and 2 in Monday post but it is important that the data confirm the patterns/cycles.
The next question is of course what these two cycles are related to. The two main cycles at work in these timelines are, respectively, the business cycle and the inflation cycle. Stocks track the former, bonds track the latter. But why don’t stocks track the inflation cycle? and business cycle? Perhaps because stocks – companies – can do all sorts of things to counter the effects of inflation – they can raise prices, move production, cut investment, cut the workforce. Bonds, on the other hand, can do nothing. Their coupons and principal are fixed in nominal terms, so will rise in real terms when inflation falls and fall when it rises. Even indexed bonds, which you might think are immune, are subject to cycles of inflation. This is because there is a high correlation between real returns and inflation. Rising inflation may not affect index-linked bonds in the same way it affects straight bonds, but rising real yields do.
In addition, the business cycle and the long-term cycle of inflation can be related to basic human behavior. The business cycle consists of expansion and contraction phases, which are associated with increasing and decreasing costs. These spending patterns are largely driven by changes in consumer confidence, ie. human behavior.
It may be a little more difficult to link a long cycle of inflation to human behavior, but it is still possible. For several decades, we can be complacent about the dangers of inflation, as perhaps we did in recent decades until two years ago. Complacency is the quintessential human trait.
What about the implications for investors? First, because bonds exhibit multi-decade cycles, there are long periods of negative real returns, ie. their risk is higher than many people think. Moreover, we may well have entered one of those extended periods two years ago. Second, because companies – stocks – are able to adjust to the rise and fall of inflation, you really only need to be bearish on them when they clearly outperform the trend towards the end of the business cycle.
These are simple observations, but ones that investors – active and passive – should be aware of.
Diagram 1:
Source: Credit Suisse/Yahoo
Diagram 2:
Source: Credit Suisse/Yahoo
Diagram 3:
Source: Credit Suisse/Yahoo
Diagram 4:
Source: Credit Suisse/Yahoo
Diagram 5:
Source: Credit Suisse/Yahoo
The opinions expressed in this post are those of Peter Alston at the time of writing and are subject to change without notice. They do not constitute investment advice and, although every reasonable effort has been made to ensure the accuracy of the information contained in this communication, the reliability, completeness and accuracy of the content cannot be guaranteed. This communication contains information for professional use only and should not be used by retail investors as the sole basis for investment.
© Chimp Investor Ltd
