...

, , , , , , , , , , , ,

How Can You Tell Who Will Be a Good Investor?

In Uncategorized on December 22, 2011 at 3:06 pm

(image credit:  money.cnn.com)

We talked about what a great investor looks like, but how do we figure out who will be a good investor?  You gotta measure it to manage it, so do you look at how much money someone has made?  Their returns?  Or, more sophisticated, at an investor’s alpha or Sharpe Ratio?  These types of measures are the focus of fifty years of finance literature.  I can’t argue with their precision.  But if you care about future returns, we do know that they measure the wrong thing.

The traditional measures of investing prowess only measure the historical output.  In order to decide where to invest and create durable/improving investment performance you have to measure how the inputs make the outputs.  Just imagine sitting down with an investor for a year-end review and saying:  “Look you are doing OK, but we really need you to increase your returns in excess of the risk-free rate divided by the historical standard deviation of returns by at least 0.2 in the next year (Sharpe Ratio).”  Where would one even start with that?  It’s not actionable for an investor.  Like alpha, the Sharpe Ratio is a vanity metric – a figure that looks good for your end customers (limited partners), but has little to do with how to effectively deliver that product consistently to customers in the future.

If that wasn’t clear, consider another example, suppose GM exclusively measured their entire organization based on the finished vehicle.  In this case, vehicles would never get built because no one would know what to do.  To make the final product, you need to measure the performance of the various pieces of the production process in the ways that are under the control and are relevant to each part of the process.  People making seat covers need to be primarily measured on how many fault-free seat covers they can make per hour, rather than the JD Power rating of the entire vehicle.  If the interior, chassis, electronics, engine and assembly people are all executing well on their responsibilities, chances are they will make a great vehicle.  Not rocket science.

OK, so we don’t want to focus on the historical outputs, we want to measure how well the inputs are used, you get that.  What inputs should we measure then?  I will break them down one at a time, but to keep this short, I will give you the answer upfront and then show you how I got there.  The number one metric to measure is batting average.  Batting average, batting average, batting average.  In other words, the number of investments that an investor makes that are profitable divided by the total number of investments.  If an investor’s batting average over time is <50%, there are few ways to sustainably make money.  That is the breakpoint between success and a painful spiral.  A batting average <50% means that an investor will have to roll the dice for a few big winners and/or hope to allocate more capital to the winners than the losers.  It’s not sustainable or repeatable.

What is true about individual investors is true about investment organizations as well.  Obviously, if the aggregate investment organization’s batting average is <50%, they will need big winners or lucky capital allocation to perform.  But the batting average within the organization tells you even more.  If only a few partners have a batting average >50% or batting averages are declining among partners over time, that means that the partnership is sick.  If young analysts’ batting averages aren’t improving over time, that means the organization is not investing in training and/or recruiting.  In both cases, the great investment returns of the past are very unlikely to be repeated in the future even if the whole dollars, returns, alpha and Sharpe Ratio appear to be fine today.

It is clear that having a batting average >50% is at the core of making money investing, but is it an actionable metric?  Consider the year-end review to discuss a batting average:  “Look you are doing OK, but we really need you to increase your batting average from 40% to 60% next year.”  What do you do with that?  Well, go pick more stocks that go up than down.  What is the easiest way to do that?  Weed out the losers.  Do more of the winners.

In order to do that, you need to actually have data on when/where you win and lose.  I track my batting average by geography, market cap size, sector, industry and situation (IPO, spin-off, merger, etc…).  After a few years, an 80/20 emerges.  80% of my losses come from one particular type of investment .  So the actionable outcome is that I need to not trade those stocks or have the trading desk refuse to execute orders in those stocks.  In short, batting average is very actionable.

The readers of this post are smart, so I am sure a number of objections have started popping up in your heads.  Shouldn’t you measure batting average relative to the market?  Over what time frame should you measure the batting average?  Agreed.  So in an absolute return setting, a >50% batting average is what matters.  If you are long-only or benchmarked, then you gotta beat the batting average of the index.  If you are long-short, with certain exposure weightings, then you can benchmark against the index with those exposure weightings.  The same flexibility goes for timeframe.  If you care about performance over 3 years, then track batting average over 3 years, not year-to-year.  If you care about performance daily, then track the batting average every day.  A batting average is simple division, make it work for you.

Obviously, batting average does not = profits.  You gotta multiply the batting average times the exposure (the amount of money allocated to each investment) to get profits and we’ll go over measuring exposure in the next post.

Comment »

, , , , ,

What Makes a Good Investor?

In Uncategorized on December 16, 2011 at 7:33 pm

Thank you for all the great feedback this week.  From your questions, I think it makes sense to step back and first answer the question:  What Makes a Good Investor?  Once we’ve got that under our belt, we can break the relevant skills into their component parts so we can measure and get better at them.

Good investing is hard because it requires three different types of people.  You need to be creative to come up with ideas.  You need to be a diligent researcher to vet them.  And you need to be shrewd to turn ideas into money.  Unfortunately, human beings usually come with one of these qualities at a time.  For example, top-decile creatives aren’t often in the investment business.  They are artists or in an asylum.  Diligent researchers usually lack the creativity to spot opportunity or the business sense to capture the money for themselves.  Bazaar merchants are good at churning inventory, but without a structural opportunity on which to apply their skills or a filter on what they are trading, they frequently run themselves into the ground.  So you need to start by knowing, big picture, where your strengths are while tending to your weaknesses.  Tending to your weaknesses means both working on the weak spots as well as surrounding yourself with people who excel in the categories in which you do not.

In my view, it is kind of obvious that you should envision investing as a supply chain of ideas, research and making money…and then organize people around that chain based on their skills.  Folks don’t seem to talk about it this way and investment organizations aren’t structured around this reality, so I wanted to make sure I laid that out before we get into the details.

Now let’s try to figure out where your strengths and weaknesses are.  Answer these three questions for yourself:

How many investment ideas do you come up with a month that merit researching?

When you research an investment, how many different people (non-investors) do you interview to evaluate the company?

How many things do you negotiate a day on average?

In broad strokes, these three questions help me figure out the relative strengths of the investor that I am talking with.  To make this fun, we’ll make a numerical game out of it.  Divide the answer to the first question by 100, the second question by 35 and the third question by 3.  Add them up.  If the number you get is 3.  You are indeed God’s gift to investing.  The rest of us have work to do.  But now you know where to focus your attentions in terms of training and hiring in order to run a productive investment “supply chain”.

How did I get to those numbers?  The numbers 100, 35 and 3 represent the extreme best creatives, researchers and traders that I have met in my life.  Think about it.  If you meet someone who negotiates, on average, three different purchases/things a day.  That guy is a huge pain in the ass, so much so, that he barely exists in real life.  But that guy, in a narrow way, is extremely good at extracting value out of a given situation for himself.  Similarly, the person who comes up with three investment ideas a day is difficult to fathom.  They are very productive, but scattered and often referred to by their colleagues as “crazy” or “has ADD”.  If these extremes can live within you, one person, congratulations.  The rest of us, however, need to be aware of these strengths and weaknesses, and plan our network and organizations around them.

The coming posts will mainly focus on measuring yourself and your behavior accurately so that you can tell what you are good at and what you are bad at.  I hope this post provided you with a backdrop for what we are digging for and how it will all fit together.

Comment »

, , , ,

View from the Bottom #24

In Uncategorized on December 13, 2011 at 1:40 am

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.

 

Comment »
Follow

Get every new post delivered to your Inbox.

Join 160 other followers