I’m going to transition the View from the Bottom from telling you what will happen in the coming 6 months to writing about how to make more money investing.  Here’s why I am changing the focus:

The public (and private) investment business has gone from an “explorer” business where returns were so fat that anyone with a calculator, a phone and a command of the English language could make enormous sums of money – to an “exploitation” business where profits are thin and are eeked out through efficiency.  Don’t worry, this happens to every industry over time, so we know there are two implications that we can prepare for:

1)  There will be less alpha to go around.

2) Investment firms will compete on how well they are managed.  More specifically, how quickly they can discern and give capital to investors who can produce abnormally large returns.  Investment firms that can do this will attract more LP money, better people and more carry dollars to buy that house and that new pair of shoes, every now and then.  If you just thought – don’t we do that already?  You don’t.  Keep reading.

So let’s look at what investment businesses are doing now to compete on challenge #2.  Training at investment firms takes two forms, both woefully ineffective in the current environment:

1) The Osmosis Model:  A new analyst is paired with a portfolio manager and engages in an “apprenticeship”.  The analyst assists the portfolio manager in their work and learns by doing.  The observed hit rate in developing great investors in this model is low (<25%) because it assumes that analysts can tease out lessons from an extraordinarily complex set of variables simply by observation.  In addition, the portfolio manager’s and the analyst’s risk tolerance, personalities and experiences may differ and thereby greatly impede learning.

2)  The Filter Model:  Hire a bunch of analysts, give them some money to manage, fire the bottom 20% of performers every 6 months.  A few years later, you have a group of people that is either lucky, smart or both.  Again, the observed hit rate is low <25% because you have no idea who is lucky or has skill or whether the skills are appropriate for the outlook going forward.

It is easy to throw stones…so what is the better alternative?  Well, it becomes clear if you just breakdown where investment profits come from.  *ALL* investment performance, regardless of asset class, is a product of two factors:

1)  Batting average – the percentage of investment picks that are profitable vs. not profitable.

2)  Exposure – the weighting of investment picks, i.e. how much money you choose to put behind each investment.

That’s it.  Batting Average  x  Exposure = Investment Performance.  Every.  Single.  Time.  So in developing investors, your goal is really to get the team to have a batting average well-above 50% and have exposure that favorably selects the batting average.  With that, you will always make money in all market environments.  So how do you do that?  In my experience and observation, this is a result not of putting resources towards “training people”, but of figuring out what investors are already good at and amplifying those skills…which leads me to what I call the Discovery Model.

The Discovery Model:  The 1-4 year investment “training period” is far too short for someone to learn how to invest.  The only thing that can be reasonably ascertained during this period of time is what an investor is good or bad at.  In order to produce a viable batting average >50%, an investor should focus on what they are good at and stop doing what they are bad at.  This concept extends to exposure management as well.  If an investor’s exposure selection underperforms the batting average, then an investor should not select exposure, regardless of tenure.

The implication of the Discovery Model is that investment firms that can discover what their analysts are good at the fastest and allocate the greatest amount of responsibility to these skills, win.  Have you heard that in an LP meeting before?  Never, right?  You’ve probably been lulled to sleep by stories about investment process, discipline, training programs and great people instead.

This post is getting long, so I will stop here before going into detail on how to implement the Discovery Model as an individual or an organization.  Instead, I will leave you with an “Appendix” – a breakdown of my own batting average to demonstrate how this information can be used to develop analysts and wield investment research for maximum profit with minimal effort.

So my batting average over the last 6 years has been 80% and approximately 80% in each year since 2005.  This is quite high for a period where the market has gyrated between +20% and -40%.  None of the investment firms that I have worked for have gathered this data, so none of them have peeled back the data and looked to see why my batting average is so high and how it might be maintained or propagated throughout the organization.  So let’s do that now.

On the long side, my hit rate averaged about 60% during a period where the market is down.  Let’s look one step closer:  For companies that I am covering for the first time, the hit rate is about 60%, for companies I have looked at a few times before the hit rate is 80% and for companies that I have looked at for years, the hit rate is 40%.  Now that is important information for an investment organization to know.  The more I know about a company, the worse my ability to buy stocks.  So the longer I become expert in a set of companies and the more responsibility and capital I am given, the more likely it is that I lose a lot of money.  This seems strange.  But it is the reason portfolio managers and experienced investment professionals blow themselves up all the time.  The underlying cause is the human tendency to believe our own b.s.  This isn’t inherently a bad thing.  It just means, the less I invest in companies that I have gotten very comfortable with, the better I will do in any market.

On the short side, my batting average is 95%+.  Whether I have known a company for a short period of time or years, the shorts work in any market conditions.  I think this is because shorting is inherently nerve-racking and so complacency doesn’t set in.  I also have a tendency to see the worst in people and situations.  Since the point here is to become as great at investing as fast as possible, I should just do more shorts within appropriate exposures and my batting average, and likelihood of making money will go up.

What other interesting insights are there to glean from my batting average?  I have no statistical skill at determining outcomes of government regulation.  But I have a perfect batting average with IPOs on the long side in all market conditions.  This also correlates with other data that suggests when an investment landscape is undefined (i.e. there are no comparable companies, limited coverage, etc…), I am at my best on the long side.  So for me, “getting better at longs” doesn’t mean “spending more time on the long side” or “seeing the upside” or similar nonsense.  It just means focusing my efforts on buying stocks in uncertain or unusual situations.

The batting average is only half of the equation.  Selecting exposure is equally important.  I hope to cover how to gather and analyze data on both easily and systematically in the next post.