Beating the S&P 500 by almost 7% per year: How to find quality stocks at reasonable prices – Part 2

Back in 2014, I published a post entitled How to find quality stocks at reasonable prices which explained how to use the Zacks free online screening tool to identify quality stocks at reasonable prices. This post illustrates the impressive results that are possible with such a strategy.

I used a commonly available investment data service to run the screen as described in my earlier post, except for one difference:  the screen was limited to S&P 500 stocks instead of all US stocks with a market cap greater than $2 billion (see below). This tool was able to generate a back test illustrating how a screen would have performed though time.

I used the following parameters for my screen and back test:

  • Time Period = 30 years to 31 December 2014.  I chose 30 years because it is long enough to capture several market cycles including the 1987 crash, the tech boom and bust bust and the global financial crisis.
  • Investment universe = Stocks included in the S&P 500 Index. Limiting the investment universe to large, highly liquid stocks demonstrates that the performance of the screen isn’t due to the size effect (i.e. isn’t driven by the out-performance of small cap stocks).
  • Portfolio construction = Equal weighting, rebalanced annually. Equal weighting is appropriate as the screen makes no judgments about which stocks are more likely to out-perform and are therefore deserving of a higher portfolio weight. Annual rebalancing reduces trading activity and therefore helps to reduce the negative impact of taxes and trading costs.
  • Valuation = Price to cash flow ratio ≤ 10×. Price to cash flow is a valuation metric that compares a company’s stock price with the amount of cash that the company generates. A price to cash flow ratio of 10 × = a cash flow yield of 10%.
  • Quality = Return on invested capital (ROIC) ≥ 10%, total debt to total capital ratio ≤ 25%. I’ve used two measures of quality, a profitability measure and a debt measure. A ROIC of 10% of more means that a company can re-invest any retained profits at a cash flow yield of at least 10%. It also ensures that, in most cases, a company will earn a return on equity greater than its cost of capital**. A total debt to total capital ratio ≤ 25%  results in a list of companies with low levels of debt and therefore conservative balance sheets.

The idea of creating portfolios of stocks screened for quality and value is not new. My screen was inspired by the work of Joel Greenblatt – The Little Book That Still Beats the Market and Wesley Gray and Tobias Carlisle – Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors.

The result was a compound annual return of 19.71% per annum, versus a return for the S&P 500 Index of 12.83%. $100,000 invested in the strategy at the end of 1984 would have grown to $4,097,110* by the end of 2014.

But 6.88% out-performance over 30 years doesn’t come without a catch. The catch is short to medium term under-performance bad enough to get ANY fund manager fired.  For example, the screen under-performed the S&P 500 for 5 years in a row from 1995 – 1999. In fact, under-performance saw so bad the screen under-performed the S&P 500 by over 30% in 1999 alone!

The effect of the 5 years sever under performance was simply to bring the performance of the strategy from 1984 – 1999 back to the performance of the S&P 500 over the same period. In other words, an investor using the screen was no worse off than if they had simply invested in the S&P 500 from 1984-1999 even though they had dramatically underperformed the market for 5 years.

An investor who pulled out of the strategy in 1999 couldn’t have pulled out at a worse time. Their decision would have cost them approximately 40% out-performance of the S&P 500 in 2000 and a further 60% in 2001.

Overall, the screen under-performed the S&P 500 9 years out of 30 or 30% of the time. In other words, an investor using the screen would have to endure being wrong about a third of the time.

So the long-term returns were impressive, what about the risks? Here are the results.

  • Standard deviation = 18.64%
  • Tracking error to S&P 500 = 11.29%
  • Skewness = 0.14
  • Sharpe ratio = 0.67
  • Jensen alpha = 5.16%
  • Information ratio = 0.48
  • Beta to S&P 500 = 1.02
  • Correlation S&P 500 = 0.84

The screen has more or less the same volatility as the stock market.  According to Jeremy Siegel , the 1 year standard deviation of US shares from 1802 to 2012 was 18%, which is similar to the standard deviation of the screen. Also the beta of the screen to the S&P 500 is approximately 1, indicating that  the portfolio is no more risky (according to the capital asset pricing model) than the S&P 500.

While the absolute risk of the screen is the same as the S&P 500, the relative risk is high. A tracking error of 11.29% indicates that the screen will have short to medium term performance that is VERY different to the S&P 500. But isn’t this the whole point? After all, isn’t the screen trying to beat the market? How will it ever beat the market after fees and costs if it tracks the market closely? Shouldn’t investors be more focused on the long-term absolute risk of the screen, which is no worse than that of the S&P 500? My advice, forget about relative risk or tracking error if you’re trying to beat the market over the long-term.

Most active investment strategies can only dream of a 30-year information ratio of 0.48. The information ratio is a measure of active manager skill. It measures how much out-performance relative to a benchmark is generated for each unit of tracking error.

Readers may be wondering about the types of portfolios generated by the screen. In most years, the screen generates portfolios containing 10 to 20 stocks. The smallest number of stocks was 5 (1990 and 1999) and the largest number was 64 (2008). Turnover is usually between 40-60% with a maximum of 84.4% (2008).

It would be impossible for a mutual fund to build an investment strategy out of this screen. The small number of stocks would limit the amount of funds that the mutual fund could invest in the strategy, potentially rendering it economically unviable. Holding as few as 5 stocks could potentially breach the “prudent man” rule, which is usually satisfied by running a well-diversified portfolio. A high tracking error creates the potential for under-performing the market over several years, which, of course, carries the risk of being fired. And finally investors would pose a risk to themselves by entering and exiting their investment at the worst possible time (chasing historical performance).

But there’s no reason why an informed, disciplined and patient individual can’t do this for themselves.

The screen results illustrate several points discussed in earlier blog posts.

Both institutional and ordinary investors make behavioural mistakes:

Beating the market requires doing something different:

It’s impossible to out-perform the market over the long-term without under-performing over the short-to-medium term.

Finally a friendly warning. Back test results should always be treated with a healthy dose of skepticism#. Firstly, the results above do not factor in the effects of trading costs and taxes, which will lower investment returns. Secondly, a back-test shows what would have happened in the past and not what will happen in the future. The two are often very different.

 

* This figure ignores the significant impact of taxes and transaction costs.

** According to Damodaran, the cost of capital for a large mature company ranges between 7 and 9%, depending on the level of financial and operating leverage.

*** See page 98 of Siegel’s book Stocks for the Long Run 5/E: The Definitive Guide to Financial Market Returns & Long-Term Investment Strategies.

# For an excellent summary of the strengths and pitfalls of back testing, I recommend reading James O’Shaughnessy blog post: The Power of Back Testing Investment Strategies. For those of you that are unfamiliar with O’Shaughnessy, he is the author of the classic investment book: What Works On Wall Street, Fourth Edition: The Classic Guide to the Best Performing Investment Strategies of All Time.

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