I have been working in the investment industry for my entire
sixteen year professional career and have had the opportunity to meet and
advise hundreds of portfolio managers, analysts, and traders. In addition, I’ve
read as much psychology, investment, and decision process research as I could
get my hands on. Because of this background, clients often ask for best
practices I’ve observed. I’ll usually rattle off a few that are top of mind,
but I thought a more thorough list of the Best Practices was warranted.
Some of the best practices are narrowly applicable to Alpha
Theory but most are broadly applicable to investing and even to decisions we
make in everyday life. The best practice list is a living document that continues
to grow and improve. I suspect that I’ll never stop refining this list but I believe
there are a few central tenets:
1. Process is important
2. Good decisions can have bad outcomes…and vice
3. Emotion is the enemy of good decisions
4. Only explicit assumptions can be properly judged
5. A simple model almost always beats an educated
Over the coming months, I will memorialize some of the Best
Practices through a series of blog posts. I’ll start out with what we’ve
observed to be the single most important Best Practice:
Best Practice #1: RISK-ADJUSTED
is gained by making assumptions explicit so that they may be examined and
challenged” – Richards Heuer, CIA Head of Analytic Methods and author of Psychology
of Intelligence Analysis
It will come as no surprise to anyone that knows Alpha
Theory’s work that using Risk-Adjusted
Return1 is the first Best Practice. So many ills are healed by
using Risk-Adjusted Return that it is unacceptable for a fund not to use it. Here
is a litany of reasons why:
Decision Tool. Risk-Adjusted Return is the
ultimate culmination of the research process. Every piece of information
gathered through the research process can be incorporated into a probability weighted analysis.
Every new piece of information will alter it. A Risk-Adjusted
Return effectively conveys the learned information in a form that can be used
to make subsequent decisions like, should I buy this asset, and if so, how
Explicit. Risk-Adjusted Return is explicit (see quote
above). In a conversation without a Risk-Adjusted Return, the important data
can lose context because the listener (or reader) is required to build their
own mental model of how to think about risk and reward. Explicit estimates of
reward, risk, and probability allow for the information learned through the
research process to have context with regards to how they impact either the
risk, reward, or probability.
Accountability. Explicit estimates create
accountability and auditability. Implicit assumptions can be misinterpreted or
allow equivocation. Accountability is gained when estimates are written down,
tracked, and audited.
is disproportionately more important than upside in a fund because of
compounding. Downside estimation is critical to position sizing and is often
given short shrift. Of course, downside is discussed in research overviews, but
is it effectively accounted for? Risk-Adjusted Return requires an explicit
estimate of downside that must be justified and defended.
Thesis Myopia. It is easy to get lost in the
story of an idea and forget about the value. Stories are enticing but without
value, there is no inefficiency to take advantage of. When an analyst is forced
to describe both reward and risk, the myopia that comes with focusing on a
single thesis is stripped away and the importance of price paid becomes
Maximize Fund Return. If the goal of the fund is
to maximize Risk-Adjusted Return then it is imperative that it be calculated for each position. How else could you calculate the Risk-Adjusted
Return of the fund?
This is the first installment of Alpha Theory Best Practices.
Stay tuned for more over the coming weeks and months (maybe even years). As we
release these, we’d love to know some of your Best Practices and where you may
disagree with our conclusions.
1 Risk-Adjusted Return in this context refers to
a probability weighted return with an estimate of reward, risk, and probability