Sean O’Hara is the President of RevenueShares Investor Services. He recently took time out of his busy schedule to talk about weighting methodologies, alpha, and more with ETF Database.
ETF Database: Market capitalization-weighted indexes are widely accepted and used among investors, but they aren’t without their flaws. Why might these cap-weighted indexes be less than ideal for benchmarking purposes?
Sean O’Hara: Market cap-weighted benchmarks are price driven. There has been a lot of work done on the efficient market theory, and I think most investors would agree that over time the market is efficient, but in the short run it can be fairly inefficient. A cap-weighted index tends to push the highest price stocks to the largest weighting and the lowest price stocks to the smallest weighting. We believe that has some flaws in it. At RevenueShares, we rebalance the index on an annual basis to put the emphasis on the lower priced or lower price-to-sales sales stocks. Over time we think this is where the bulk of the outperformance comes from.
A great example of this is the late 90′s. Technology got to be over 30% of the S&P 500, and there was no real justification on the fundamentals for such a large allocation. If you had weighted the allocation to technology based on revenue, you would have been at about 10% or 11%. We would agree with the notion that the market is efficient, but we would say that you have to set a time frame for that and that time frame has to be fairly long in nature. In the short run the market can be very inefficient.
I also find it interesting that despite subscribing to traditional efficient market theory, “market cap biased” advisors will create portfolios for clients and rebalance those portfolios regularly. This is almost a contradiction to that premise that the market is efficient. If the market was efficient you would never rebalance, you would just assume over time that things would work out. But we do rebalance our portfolios and we should rebalance our portfolios because in the short run things get out of whack. Revenue-weighting is nothing more than rebalancing the portfolio to take advantage of short-term inefficiencies. We want to underweight stocks that have run too far too fast, and we want to overweight those that are at lower price-to-sales ratios.
ETFdb: What about the fundamentals-weighted indexes that determine allocations based on metrics such as earnings or dividends? Are there any drawbacks to that type of methodology?
SO: The benefit that we have at RevenueShares is that we’ve had a chance to look at all of the data and pick out a couple of important factors. First and foremost, we want to be able to own the whole benchmark. Revenue allows you to do that because all stocks in the index have revenue, but they don’t all have earnings and they don’t all have dividends at all times. If you eliminate a certain subset of stocks in the index that becomes a challenge over time because you create return drag by that omission of a certain set of names. That can be problematic for ETFs based on certain fundamental-weighted indexes.
The second thing that we looked at was a way to create indexes and ETFs that would be robust over multiple market cycles and that could sustain both growth and value cycles. There are two flaws with using dividends to determine weightings. First, you don’t own the whole index because all 500 stocks in the S&P 500 don’t pay a dividend. And second, you wind up with a portfolio that really becomes value dependent. You need to have a value cycle for a dividend-weighted index to outperform. There’s nothing wrong with that if you know that going in and you can put your portfolio together appropriately. But it might not be an optimal strategy in certain environments.
The benefit of using revenue is that it is able to be style agnostic – it can be optimal in both growth and value cycles in the market. This current run-up in stock prices is a great example because we are clearly in a growth phase and RevenueShares ETFs are doing very well versus their benchmarks.
The last piece of the puzzle is that if you compare revenue to all other fundamentals, revenue produces the highest return. If you were going to make a list of things that you would want to have in an index that was going to be weighted by some fundamental and rebalanced by that fundamental, you would want to create a very robust index that is going to be able to produce excess return over time with great consistency and be less susceptible to style movements.
ETFdb: So how specifically do RevenueShares ETFs come up with their weighting for each individual holding?
SO: It’s very straightforward: we calculate the total revenue for the entire index and we use that as the divisor. Then we take each individual component in the index, and we divide that company’s revenue by the divisor to determine the weight. Let’s say for example that you know Stock A had $1 worth of revenue and the total revenue for the index was $20. We would divide $1 by $20 and when we rebalance that particular stock would get a 5% weight.
What’s also significant about this, which I think a lot of people miss, is the fact that when you use a revenue-weighting methodology, you change the number of outstanding shares you own in each one of these stocks. This is another flaw to market cap-weighting since you have a constant level of shares in the index adjusted from time to time for splits and conversions (such as what Citigroup recently has done with their preferreds). But you never change the number of shares you own in a market cap-weighted index.
By implementing our system, the number of shares can change. For example, Company A’s revenue stays constant, but its share price goes down by 50%. What RevenueShares ETFs will do is buy 2x the number of shares versus the benchmark.
ETFdb: So why the price-to-sales metric as a preferred ratio for the stock valuation – why not something like price-to-book or price-to-earnings?
SO: If you look at some of the academic work that has been done on the subject, revenue produces the highest return. We started with that and began to tear it apart to look at some of those ratios like price-to-earnings, price-to-book, price-to-dividends, and price-to-sales. When you look at those metrics over time, what you start to see is that those companies with the lowest price-to-sales ratios over time produce remarkably high returns relative to the broad based index or to those that have the highest price-to-sales ratio.
If we look at the last 30 years worth of data for the S&P 500, we would see that the historical average for the price-to-sales ratio over time is about one. So a dollar of revenue is worth about a dollar of market cap. If you use that as the benchmark and isolate the high price-to-sales periods and those low price-to-sales periods, what you find is that when stocks have a price-to-sales ratio that is above one, the average return is about 7% the last 30 years. But if you invest when the stocks have a price-to-sales ratio of below one, the average return is around 16%.
By using this methodology and by focusing on revenue, you tilt the portfolio to those companies, when you rebalance, that have the lowest price-to-sales ratios. And these companies have produced remarkable returns over time versus stocks that have a high price-to-sales ratio.
ETFdb: A lot of the RevenueShares products are based on indexes that a lot of people are pretty familiar with: RWL holds the same stocks as the S&P 500, while RWK and RWJ hold the same stocks as the S&P MidCap 400 and the S&P SmallCap 600, respectively.
But some investors might not be as familiar with the Navellier Overall A-100 fund (RWV). What is the investment thesis behind this benchmark and this ETF?
SO: It all started with Lou Navellier. Lou came across the revenue-weighted approach and he reached out to us to create an ETF that kind of takes advantage of revenue-weighting but also focuses on his overall approach to how he constructs portfolios. The first thing we did was construct an index that used his stock grader system. Lou looks at eight fundamental factors and a couple of quantitative factors to score stocks with an A, B, C, D or E rating.
Lou’s research shows that over time, stocks that get the “A” ratings, those that have the strongest fundamentals as measured by his system, have returns that are much higher than those rated B, C, D, and E. Interestingly enough, of the 5,000 stocks that comprise the U.S. market over time, a very small percentage of them wind up with an “A” rating at any given point in time. What he believes is that if you focus on those fundamentals and you try to isolate those stocks that he thinks are the highest quality by those ratings, you can get exceptional returns.
The concept behind RWV is a little bit different than what we would traditionally do, in that we normally don’t have much input into stocks that are in the index – they’re simply the components of widely-followed benchmarks. We think Lou is a terrific manager and the construction of the index underlying RWV starts with his 40 years worth of research.
We took it two steps further. First, in order to create an ETF that really would perform from an execution perspective, we limited it to only the 100 best “A” rated stocks to ensure sufficient liquidity and avoid huge bid-ask spreads. That’s where the “A-100″ name comes from. Second, we take his index, which is off the stock grader system, and then apply a revenue-weighted methodology.
ETFdb: Certainly some very interesting products – thanks for taking the time to speak with ETF Database!
Disclosure: No positions at time of writing.