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Alpha Theory Blog - News and Insights

November 1, 2019

Concentrating on Concentration: New Data on Portfolio Concentration

 

As most of our readers know, we’re proponents of more concentrated portfolios. In May of 2017, we released our Concentration Manifesto which was an attempt to get a critical dialogue started between managers and allocators to ultimately improve the active management process. A conversation that requires both sides cast aside outdated thinking and embraces the notion that concentration is in their best interest.

 

And we’re seeing it in external data:

 

Exhibit 19

 

And in our own managers:

 

AveragePositionSize

 

This conversation began well before our Concentration Manifesto. We recently found an April 2014 study by Cambridge Associates outlining the “Hallmarks of Successful Active Equity Managers.

 

Cambridge Associates analyzed a selection of managers to isolate attributes that lead to success. In their findings, active share and concentration were major contributors. Their analysis1 found that concentrated portfolios (US equity less than 30 positions and US Small-Cap & EAFE Equity less than 40 positions) generated between 100bps and 170bps of additional performance over non-Concentrated portfolios.

 

Table-3.-Results-of-Active-Share-Analysis

 

The performance difference for concentrated managers held after fees and worked across various strategies. The fractal nature (it still works when you break it into different strategies) lends additional validation for concentration’s benefits.

 

In the Cambridge article, we found a reference to another concentration study.

 

Baks, Busse, and Green published “Fund Managers Who Take Big Bets: Skilled or Overconfident” in 2006. The abstract says it all:

 

We document a positive relation between mutual fund performance and managers' willingness to take big bets in a relatively small number of stocks. Focused managers outperform their more broadly diversified counterparts by approximately 30 basis points per month or roughly 4% annualized. The results hold for mimicking portfolios based on fund holdings as well as when returns are measured net of expenses. Concentrated managers outperform precisely because their big bets outperform the top holdings of more diversified funds. The evidence suggests that investors may enhance performance by diversifying across focused managers rather than by investing in highly diversified funds.

 

Their sample covers funds from 1979-2003 and the return advantage per month ranges between +1 and +67 basis points depending on the methodology for measuring fund concentration and how many deciles to included. That equates to a range between +0.12% and +8.34% on an annualized basis for concentrated managers.

 

Fund perf vs. portf weight

 

We continue to believe that there is a demonstrable skill in equity managers and that the skill could be harnessed in better ways than is typically demonstrated by the average manager and that concentration is the simplest ways to improve a manager who possesses positive stock-picking skill.

 

1 eVestment Alliance Database: September 2007 to June 2013 US large-cap core equity, US large-cap growth equity, US large-cap value equity, US small-cap core equity, US small-cap growth equity, US small-cap value equity, and all EAFE equity

 

October 4, 2019

The Difference between Intrinsic and Extrinsic Value – A Case Against WACC

 

In one of our blogs, we highlighted how our clients’ returns would have enhanced returns by more closely following a position-sizing optimization based on probability-weighted return. We also noted how the quality of the probability-weighted returns impacted the improvement generated by the optimization (garbage-in garbage-out). The return our clients calculate is the difference between the market’s valuation and the manager’s calculation of intrinsic value (probability-weighted return). Said another way, gaining a sense of the intrinsic value is the core task of a portfolio manager.

 

For managers that use discounted cash flow analysis to determine intrinsic value, the discount rate is one of the most subjective, yet important, inputs. For managers that do a scenarios analysis, we pointed out a straightforward approach that dramatically reduces subjectivity (June ‘18 blog). However, for those that don’t do scenario analysis, determining the discount rate can be substantially more complicated.

 

We’ve recently spent some time with Ryan Guttridge and his colleague Corry Bedwell of the University of Maryland and they have some interesting ideas on setting discount rates that I thought were worth sharing:

 

Let’s Think about What Intrinsic Actually Means

 

An intrinsic property is well defined in sciences such as chemistry. An intrinsic property is an essential or inherent property of a system. Said another way, an intrinsic property is internal to the system being evaluated like specific density is an intrinsic property of water.  In contrast, an extrinsic property is not internally defined by the entity being evaluated. So, think about them this way:

 

Intrinsic – Totally independent of outside influence

Extrinsic – An influence outside the system

 

Why We Discount – The Marshmallow Test

 

Put a group of kids with a plate of marshmallow’s (or any other tasty treat) in a room and leave. What will happen? Chances are by the time you come back the treats will be gone. Why? Well, something now is better than something later. Ok so change the rules, offer the kids a deal. If they don’t eat the treat right away they will get another one at some later time, growing their supply of marshmallows. So, the deal from the kids perspective, I give up eating the marshmallow now and get two later. What makes it worth it? First, he has trust that the marshmallows will be delivered as promised. Second, the time he must wait for a reward can’t be too long, given the fact he can always eat the marshmallow now. In other words, the reward has to be large enough to overcome the opportunity cost of eating the marshmallow now. This is the classic economic definition of the logic of discounting. Forgo today’s marshmallow for two tomorrow.

 

Investing – Bringing two separate but intrinsic concepts together

 

Think about what goes through your head when you make an investment. You are going through the same steps described above. First, you will estimate the series of cash flows you expect the asset to provide (when are and how often are the marshmallows arriving). Second, you are going to decide how much you will pay for those cash flows (how badly do you want that marshmallow now). Each of these steps are independent but intrinsic.

However, according to the financial literature, determining an appropriate discount rate (i.e. the opportunity cost) isn’t straight forward. The efficient market hypothesis logically implies the correct discount rate for our intrinsic valuation models is the company’s weighted average cost of capital, WACC. Which is defined in the following way:

 

Screen Shot 2019-09-16 at 3.19.54 PM

 

That is WACC is the portion of capital from equity plus the portion of capital from debt.

 

WACC – A Tale of an Extrinsic Rate

 

So, let’s take this apart -- our recommended discount rate is a function of capital ‘’we” have from equity and the amount of capital “we” have from debt. Right? This has at least two fundamental problems.

 

First, if the market is efficient, there is no reason for active management. However, there is a growing body of literature showing that while large swarths of the market can be considered efficient, there are pockets of inefficiency. So, if these inefficiencies are going to be taken advantage of, logically a discount rate that requires efficiency cannot be used. 

 

Second, an active manager is required to have an independent sense of value. He is hired to find “mis-priced” assets. The only way to do that is to develop an independent view of the correct valuation (i.e. outside the market). So, what do we have that is independent of the Market? Think back to the marshmallow test.  The value of the deal is a function of the opportunity cost (compensation for not buying something else) of your capital, and the intrinsic productivity (read cash flows) of the asset.  

 

What to do about Risk?

 

One way to deal with this problem is to use scenario analysis as mentioned above. For those who don’t use scenario analysis, you need to focus on these three issues when calculating a discount rate: 1) Opportunity cost of capital (possibly provided by your benchmark), 2) the average cash flow level, and 3) its variation. Not only are these intrinsic to the system, but your analysis offers an independent sense of value. This, in turn, allows for the calculation of “edge” (the difference between Intrinsic Value and Market Value) and proper optimization. In our next post, we will expand on the calculation of an intrinsic discount rate using this method. In the meantime, feel free to check out our paper on the topic: https://arxiv.org/abs/1903.09683