Wed 20 June 2018
Regression to the mean; respect skill but acknowledge luck!
Luck is a dirty word in financial services. But luck is everywhere, and it explains regression to the mean – the tendency for extreme performers to come back to the pack. Regression to the mean is difficult to understand because it goes against every notion of the way we understand the world.
The correlation coefficient between two measures,
which shows the relative weight of the factors they
share, is a strong starting point to understanding this
strange phenomenon. One is a perfect match and zero
shows no predictive relationship.
For example, the correlation between a parent and
their child’s height is about 0.5, given height is largely
hereditary (you get 50% of your genes from your mum,
50% from your dad). It is a mathematical inevitability
that whenever the correlation between two factors
is less than 1, there will be regression to the mean. If
a child is significantly taller than both their parents’
height, their sibling is less likely to be – since the tall
child was a far lower probability event to begin with.
In financial services, this leads to some disturbing
Investing requires a deep understanding of some of the
most complex, inter-related systems ever devised. But
there is no perfect correlation between measures of skill
and investment outperformance. This means regression
to the mean is everywhere, just as it is everywhere in life.
Yet investment performance is (still) the dominant way
that most funds sell themselves and how most investors
pick their managers. But this year’s top investment performers tend to underperform the following year
and vice versa.
Unfortunately, our minds are not structured to interpret
this as a statistical fact of life. Instead, we assign
causal interpretations, which may sound perfectly
plausible even though they are wrong. If these causal
interpretations were correct then reversion to the mean
wouldn’t occur in reverse, but it does – this year’s top
investment performers also tend to underperform the
previous year (and vice versa).
We all have a deep need to understand and control
the world, but this ignores the significant role of luck.
So how should investors account for regression to the
mean when making decisions?
GOALS: SETTING YOUR
If so many fundamental aspects of investing suffer from
regression to the mean, why invest with one group over
another? Why invest at all?
Skill still plays an important role in this industry but
it’s important to understand what you can control and
what you can’t, to avoid wasting resources at best or
selling snake oil at worst.
The financial services system is so complex that regression
to the mean is inevitable although not always predictable:
it comes in swings and roundabouts. While tail events are
rare, they may have excessively large negative impacts
on portfolios. When luck plays a significant role, risk
management becomes even more crucial.
Counterintuitively, investors should consider selling
rather than buying the latest top performing fund
managers, rotating into those underperformers (who
nonetheless still meet their long-term criteria). It
can be uncomfortable to sell yesterday’s winner to
buy tomorrow’s winner but regression to the mean is
These approaches are both part of our investment
process at Innova: we have a stringent focus on risk
management and asset allocation.
However, none of this counts for much if not viewed
through the prism of investors’ personal goals. The
mean differs in many ways, whether it’s one asset class
return compared to another (such as government bonds
versus equities) or returns from different investment
styles within asset classes (such as growth versus value
This personal ‘mean’ return must be aligned with an
investor’s goals, outlining a path to achieve it with the
least risk. This is why good financial advice is so important
and why Innova has invested in tools to support advisers
giving goals-based advice.
Most people don’t know why they invest, so they don’t
know when to sell. If their investments have performed
better than expected, they may not need to take as much
risk to achieve their goals (and vice versa) but typically
behavioural biases kick in and few make this choice.
Regression to the mean can then destroy any
outperformance, but it is often ignored because the
concept is so alien to the way we interpret the world.
But understanding this concept can explain many
investment tendencies and allow investors to avoid
paying for luck rather than skill.