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Alpha Theory Blog - News and Insights

July 05, 2018

More Evidence of Manager Skill – Concentration Manifesto Continued

In preparation for a webinar we hosted about the Concentration Manifesto on June 21st we had a client question using batting average (win percentage) as a way of measuring skill. Their contention was that high batting averages do not always result in great returns, because a low hit rate with high asymmetry (lots of upside with little downside) can be even more profitable than predictable low returners.

 

Screen Shot 2018-07-05 at 12.25.30 PM

 

To analyze that point, we looked at the Return on Invested Capital (ROIC) by the same buckets we analyzed batting average.

 

Chart2

 

You can see that there is a similar correlation. Assets that are sized the largest had the highest return on invested capital. Said another way, the Top 5 positions went up an average of 12.1% while the portfolio as a whole went up 8.4% (for shorts, went down 8.4%).  That’s 50% better!

Chart3

 

We then analyzed the distribution of returns by bucket.

 

Again, you can see a predictive quality in manager position sizing. Stocks that have smaller positions have a wider distribution of returns (and more downside). The smallest positions had the most upside, but what we see in the data is that managers can forecast more volatile positions and size accordingly.

 

To finish the point, I’ll pull up a chart from the original Concentration Manifesto where we use our clients’ forecasted returns (Expected Return) and created two portfolios. One with the 20 best forecasted returns and then the rest. In the graph below, you can see that managers can forecast which assets will have the best returns. This shows skill not associated just with positions sizing, but on forecasting price return.

Chart4

 

There is very little question that our clients demonstrate skill. There is also very little question that they have mitigated a substantial portion of their skill by having too many positions.

 

June 04, 2018

Don’t Double Discount your Discounted Cash Flow

 

I was working with a client recently and we were discussing their use of discounted cash flow analysis (DCF). Most of our clients are value investors, so DCF is a key tool for many of our clients, especially when valuing businesses where the major value to be unlocked is more than a year in the future.

 

Here is the problem. The client was double discounting the risk-premium in their discount rate. What exactly does it mean?

 

Below is a simple DCF, where there is a single stream of cashflows. The investor picks a terminal date and terminal multiple and then discounts the Terminal Value back to today. The discount rate is usually a combination of the risk-free rate and a risk premium (cost of capital) that accounts for the “riskiness” of the stream of cashflows. One of the biggest challenges is the sensitivity of the discount rate. Small changes of large impacts on the total value (there is a 15% difference in valuation if I use 2% above or 2% below the current discount rate).

 

Screen Shot 2018-06-04 at 11.09.25 AM

 

The most subjective assumption in the analysis above is the risk-premium in the discount rate. It is required when looking at a single stream of cash flows. But, for investors that use scenario analysis, a risk-premium isn’t required. That’s because the risk premium (the “riskiness” of the cash flow streams) is accounted for in the forecast of risk scenarios with probabilities:

 

Screen Shot 2018-06-04 at 11.10.12 AM

 

In this case, only the risk-free rate is needed in the discount rate. The probabilities and multiple scenarios account for the “riskiness” of the cash flow streams.

 

This benefits scenario-based investors in three ways:

1. NO RISK PREMIUM: The Risk Premium assumption is subjective and creates extreme sensitivity in DCF analysis. Removing this step reduces the noise in the analysis.

2. NO DOUBLE COUNTING: Using this approach means that there is no double counting of risk (risk premium + Risk scenario).

3. EFFECTIVELY ACCOUNT FOR RISK SCENARIOS: What’s the right risk premium to add into the discount rate for a Risk scenario that is bankruptcy. 12%? 18%? 26%? It’s a question that’s not required to be answered when there is an actual probability weighted scenario that includes bankruptcy as part of the entire analysis (now how you size a position by scenario is a topic for another blog).

 

I think there is general confusion about using DCFs and scenario analysis. For most, DCFs came first. We learned to build them with a single stream of cash flows that were discounted back to present value. We learned scenario analysis at a different time and merged them together on our own. There is overlap in those two methods and hopefully this article will prompt a discussion for those funds using both DCF and scenario analysis.