Updating The Smart Alpha Low Volatility Portfolio
Rethinking Volatility
On paper, that would seem pretty simple to execute a low-volatility strategy; select stocks with low measures under Standard Deviation (the variability of a stock price) and/or Beta (a measure of variability relative to a benchmark, often the S&P 500). But what’s good on paper isn’t always good in real life. That’s because Standard Deviation, Beta, and all similar statistics are based on historic stock price data, and as we know, past performance doesn’t assure anything.
But my quibble with conventional quant risk measures goes way beyond the past-performance legal boilerplate. It’s that the boilerplate, however mundane it may seem after having encountered endless repetitions of it, is absolutely positively correct. Things change.
Whether past outcomes will persist into the future depends on whether what happened back then was based on substantive and sustainable reasons, or coincidence. Consider a stock with a five-year Beta of -0.12. This would, according to established financial theory, be a great stock for risk-averse investors to own. It has very little volatility relative to the S&P 500 and what little it has actually runs counter to the blue-chip benchmark. This penultimate widows, orphans and retiree paragon of stability is, drum roll, Royal Gold (RGLD), whose five-year returns are charted, along with those of the SPDR S&P 500 ETF (SPY) in Figure 1.
Figure 1
The math is correct. The stock did, indeed, have very little volatility relative to the S&P 500. So if you want to compete for a Nobel Prize, you should argue for inclusion of this stock in a low-risk portfolio. If, on the other hand, you refer solvency, run far and run fast.
The problem is that quant models that tell risk-fearing investors to chase stocks like this is that they are nothing more than math exercises. They do not pick up any of the factors that make a stock risky or not risky, either on its own terms or relative to the market. The factors that are relevant are those relating to the business. It’s the business that determines the profit stream, and it’s the stability of that stream that determines investor sentiment toward the stock (i.e. the PE, Price/Sales, etc.).
To properly measure risk, potential future volatility, we need to be measuring fundamentals that address the profit-generating capabilities of the business. That’s what this strategy is designed to do, as explained further in the introductory September 3rdpost.
Performance Update
Figure 2 shows the environment into which the model was introduced; the performance of SPY in the six months leading up to the model’s 9/3/15 launch.
Figure 2
The September 3rd article discussed data showing that the strategy did what it was expected to have done in backtests. Figure 3 shows how it performed during its brief history with real money.
Figure 3
That’s on script.
It would be wonderful to have had the strategy outperform SPY. Who wouldn’t want that for every strategy every day. But that’s unrealistic. For a low-risk strategy, we’re willing to tolerate underperformance on the upside so long as we can beat the market on the downside. This strategy actually did better than expected in that it’s start-to-present return is about even with that of SPY even though the latter was recovering from an exceptional decline. (That says something for the modest extent of the recovery.) And the strategy got from there to here with much narrower zigs and zags.
Fundamental Diagnostics
Portfolio123 Smart Alpha models are measured under three ranking systems built on the basis of actors widely recognized as driving share price performance.
Momentum
- This rank is based on price momentum (trend-oriented technical strength) and improved sentiment (measured through changes in analyst ratings, estimates, and surprise).
- The average rank of the stocks in this portfolio is 72 on a scale of zero to 100.
- That score is consistent with this strategy. It’s not overly high. And it’s not so low as to suggest a contrarian flavor, something that may have been romantic and exciting in past generations but is less so now given the extent of information availability today.
Value
- This rank is based on the following traditional metrics; Price to Earnings, PEG, Price to Sales, Price to Free Cash Flow, and Price to Book Value.
- The average rank of the stocks in this portfolio is 42 on a scale of zero to 100.
- Some may wince at this. Actually, though, the association of value and low-risk is not well founded, as I explained in an article last week. As with insurance in all walks of life, risk protection in the stock market is something for which we need to pay.
Quality
- This is a broad-based measure that considers return on capital, margin, turnover, financial strength, industry leadership, earnings quality, and business stability. Essentially, this rank measures business risk and, I believe, forward-looking stock risk.
- The average rank of the stocks in this portfolio is 91 on a scale of zero to 100.
- Bingo! This is the kind of score I want to see if I’m looking to mitigate volatility.
Size
- This isn’t a ranking system per se, but size is widely recognized as being a relevant driver of returns and risk with larger size, all else being equal, associated with lesser risk.
- As a model that limits itself to S&P 500 constituents, it tends to sacrifice opportunities to achieve maximum return for risk control.
The Stocks
The model is refreshed and the portfolio is reconstituted once every three months. It’s designed to hold up to 20 stocks but if 20 don’t pass muster, the fewer will be held, as the case now.
Here, in Table 1, is the new stock list:
Table 1
Ticker | Name | Sector |
BBBY | Bed Bath & Beyond Inc. | Consumer Discretionary |
BCR | Bard (C.R.) Inc | Health Care |
CMG | Chipotle Mexican Grill Inc | Consumer Discretionary |
DG | Dollar General Corp | Consumer Discretionary |
HRL | Hormel Foods Corp | Consumer Staples |
HSY | Hershey Co (The) | Consumer Staples |
IBM | International Business Machines Corp | Information Technology |
ISRG | Intuitive Surgical Inc | Health Care |
JNJ | Johnson & Johnson | Health Care |
LLY | Eli Lilly and Co | Health Care |
MCD | McDonald’s Corp | Consumer Discretionary |
PM | Philip Morris International Inc | Consumer Staples |
PSA | Public Storage | Financials |
ROST | Ross Stores Inc | Consumer Discretionary |
TJX | TJX Companies Inc (The) | Consumer Discretionary |
YUM | YUM! Brands Inc. | Consumer Discretionary |
Disclosure: None.