I just pulled down from CapitalIQ a data set of every private equity deal from 2017-2019 with EV>$1B. Average EBITDA multiple was 17.3x and of those with a credit rating 35% rated B-.
Pod shops are defined by 3 things: 1) lots of siloed managers 2) a risk model to separate alpha and beta and 3) lots of leverage. We tried to see if we could use our risk model to build a "poor man's pod shop" out of the thousands of active mutual funds and etfs
Our first finding was that alpha in the active fund universe is persistent over the short-term (1-12M), even though it isn't over multiple years
Note that these are alphas, not returns. We are using a risk model to short out all the factor exposure and just get the pure alpha stream, as illustrated in the graph below
There is no empirical evidence that a company's market share predicts its profitability. But that hasn't stopped academics, business school curricula, and management consulting firms from promulgating the idea for decades. The below chart shows industry leaders vs. industry median margins:
market share is not a consistent indicator of firm performance. And this finding holds true across industries, with many illustrating a negative relationship between market share and profitability - like retail:
Lina Khan might find this to be an "antitrust paradox,” but it’s actually firm strategy operating exactly as her Chicago School opponents would envision. Consumers choose Amazon because of the low prices, driving Amazon’s market share, and allowing Amazon to invest more in lowering prices and improving service.
Is the private equity model of running companies materially different from public companies? Can we see that difference in the financials? We built a database of 993 deals that had public debt and public financials to answer this question.
We first looked at revenue growth. The graph below shows the median difference between year-over-year growth in overall sales for the companies that were acquired by private equity firms and the benchmark.
We then looked at EBITDA margins. The graph below shows the median difference in EBITDA as a percentage of sales between the LBO companies and the benchmark.
If you're not already following the high-yield spread (fred.stlouisfed.org/series/BAMLH0A…) as a macro indicator, you should be. The level and trend of the spread have strong ability to predict the next month’s change in GDP and inflation - and thus business cycles
The level and direction of spread also predict returns across the full range of asset classes most investors trade. (Note the remarkable outperformance of small value equities (+39.3% annualized return!) in the recovery phase, when spreads are wide and falling (quadrant 1)
Investors could easily rely on the relative level and direction of high-yield spreads to support their asset allocation decisions. The chart below provides a visualization of the business cycle, the high-yield spread signals, and suggested assets to own in each cycle