Cornerstone Growth – Strategy Introduction and Out of Sample Results

Last week, I wrote about the cornerstone value strategy from James O’Shaughnessy’s first edition of What Works on Wall Street, published in 1996. This week I’ll introduce the cornerstone growth quantitative investing strategy and show out of sample backtesting results, net of taxes and fees. The strategy buys the top 50 stocks (by 12-month price performance), rebalanced annually, that have the following characteristics:

  • 5 consecutive years of earnings growth
  • Price-to-sales ratios of less than 1.5
  • Have a market cap larger than $150 M (in 1996 $, about $235 M today), which he calls “All Stocks”

As of October 23, 2017, 3645 of 6084 stocks in the Compustat database (~60%) are large enough to be considered.

Cornerstone Growth vs Large Stocks, Nominal Returns (12/31/51 - 12/31/94)
Cornerstone Growth vs Large Stocks, Nominal Returns (12/31/51 – 12/31/94)

Backtesting results were promising (and significantly better than the cornerstone value strategy), although these numbers do not reflect transaction costs, taxes, or slippage.

The out of sample backtest below includes 0.25% slippage for all transactions and are shown for various starting capitals, trade fees and tax brackets (with a 1-year rebalance period, we can sell (winning stocks) on day 366 and take advantage of lower long-term capital gains tax rates). For losing stocks, you typically want to sell them on day 364 to be able to use them as short-term capital losses, which can be used to offset any short-term capital gains you have, which are taxed at a higher rate (therefore, offsetting them is advantageous; this is one method of tax loss harvesting). Although this is a good idea for implementation of this strategy, tax loss harvesting was not utilized in the backtest below.

The backtest is also composited weekly, meaning each year’s return is the average return of 52 different portfolios. So if the return for the strategy in 1999 was 10%, that’s the average of 52 portfolios — 1/1/1999 to 1/1/2000, 1/8/1999 to 1/8/2000, 1/15/1999 to 1/15/2000, etc.

The benchmark this time is the SPDR S&P 500 ETF SPY (which includes dividends so the returns are total returns). Returns are shown as excess returns over buying and holding SPY.

Cornerstone Growth vs SPY, Excess Total Returns (01/09/99 - 10/23/17)
Cornerstone Growth vs SPY, Excess Total Returns (01/09/99 – 10/23/17)

With no transaction costs, the amount of starting capital doesn’t affect the excess return. If you’re paying $4.95 or $6.95 per trade, you would have needed to start with at least $10,000 to outperform buying and holding SPY. If you’re paying $19.95 a trade, you’d have needed $15,000 to start depending on your tax bracket.

The top excess return shown (for $0 trades and 10/15% tax bracket) resulted in an excess return of 413%, turning $15,000 into an astonishing ~$113,000 over ~18 years instead of ~$42,000 for buying and holding SPY.

Backtesting also indicates a slightly smaller drawdown (~50%) for the cornerstone value strategy than SPY (~55%) over this time period.

Cornerstone Growth vs SPY, Nominal Returns & Risk Statistics (01/02/99 - 10/23/17)
Cornerstone Growth vs SPY, Nominal Returns & Risk Statistics (01/02/99 – 10/23/17)

Based on the weekly composited portfolios, this strategy performs better during down markets (when SPY is decreasing) than up markets.

Cornerstone Growth vs SPY, Weekly Composited Portfolio Nominal Returns (01/02/99 - 10/23/17)
Cornerstone Growth vs SPY, Weekly Composited Portfolio Nominal Returns (01/02/99 – 10/23/17)

So the key takeaways:

  • Free trades are awesome (like with Robinhood).
  • For the most part (with the exception of low starting capital/high transaction fees/high tax bracket), cornerstone growth outperformed buying and holding SPY out of sample (1999 to 2017), and significantly outperformed the cornerstone value strategy.

As of 10/23/17, the top 5 stocks for the cornerstone growth strategy (highest 12-month price performance meeting the criteria from above) are LGIH, SKX, THO, CDW, & CBZ.

This strategy screen is available to my group on Portfolio123, where you can customize it or implement it as is. If you just want the stock picks, you can subscribe on Patreon below.

Cornerstone Value – Strategy Introduction and Out of Sample Results

In the first edition of What Works on Wall Street, published in 1996, James O’Shaughnessy outlines the framework for the cornerstone value quantitative investing strategy. The strategy buys the top 50 yielding stocks, rebalanced annually, among a universe of stocks he calls “market leaders.” (Although dividend yield is no longer a good value indicator for stocks).

Market leaders are defined by the following:

  • They’re large (their market cap is greater than the universe average). These stocks are also called “Large Stocks”, which he used as his benchmark for this strategy.
  • They have more common shares outstanding than the universe average.
  • They have cash flows that exceed the universe average.
  • They have sales that are >=1.5x the universe average.
  • They are not a utility.

His universe was simply the Compustat database (the same used by Portfolio123). As of October 10, 2017, 441 of 6088 stocks in the database (~7%) are “market leaders.”

From the 1st Edition of What Works on Wall Street
Cornerstone Value vs Large Stocks, Nominal Returns (12/31/51 – 12/31/94)

Backtesting results were promising, although these numbers do not reflect transaction costs, taxes, or slippage.

The out of sample backtest below includes 0.25% slippage for all transactions and are shown for various starting capitals, trade fees and tax brackets (with a 1-year rebalance period, we can sell (winning stocks) on day 366 and take advantage of lower long-term capital gains tax rates). For losing stocks, you typically want to sell them on day 364 to be able to use them as short-term capital losses, which can be used to offset any short-term capital gains you have, which are taxed at a higher rate (therefore, offsetting them is advantageous).

The backtest is also composited weekly, meaning each year’s return is the average return of 52 different portfolios. So if the return for the strategy in 1999 was 10%, that’s the average of 52 portfolios — 1/1/1999 to 1/1/2000, 1/8/1999 to 1/8/2000, 1/15/1999 to 1/15/2000, etc.

The benchmark this time is the SPDR S&P 500 ETF SPY (which includes dividends so the returns are total returns). Returns are shown as excess returns over buying and holding SPY.

Each color represents a different starting capital
Cornerstone Value vs SPY, Excess Total Return (01/09/99 – 10/14/17)

With no transaction costs, the amount of starting capital doesn’t affect the excess return. If you’re paying $4.95 or $6.95 per trade, you would have needed to start with at least $10,000 to outperform buying and holding SPY. If you’re paying $19.95 a trade, you’d have needed $15,000 or $20,000 to start depending on your tax bracket.

The top excess return shown (for $0 trades and 10/15% tax bracket) resulted in an excess return of 236%, turning $15,000 into ~$72,000 over ~18 years instead of ~$42,000 for buying and holding SPY.

Backtesting also indicates a slightly larger drawdown (~63%) for the cornerstone value strategy than SPY (~55%) over this time period, which brings into question whether someone would be able to psychologically tolerate this strategy.

Cornerstone Value vs SPY, Nominal Returns & Risk Statistics (01/09/99 - 10/14/17)
Cornerstone Value vs SPY, Nominal Returns & Risk Statistics (01/09/99 – 10/14/17)

Based on the weekly composited portfolios, this strategy performs better during down markets (when SPY is decreasing) than up markets…

Cornerstone Value vs SPY, Weekly Composited Portfolio Nominal Returns (01/09/99 - 10/14/17)
Cornerstone Value vs SPY, Weekly Composited Portfolio Nominal Returns (01/09/99 – 10/14/17)

…so using a market timer to exit the market improves the drawdown but erases the alpha.

Cornerstone Value vs SPY, Nominal Returns & Risk Statistics w/ 50/200 day SMA Cross Market Timer (Exit) (01/09/99 - 10/14/17)
Cornerstone Value vs SPY, Nominal Returns & Risk Statistics w/ 50/200 day SMA Cross Market Timer (Exit) (01/09/99 – 10/14/17)

However, using the same market timer to add a low beta filter (if the market timer is signaled at a rebalance date, only repurchase stocks if their 3-year beta is in the bottom 10% of stocks in the universe) may preserve alpha while decreasing drawdown.

Cornerstone Value vs SPY, Nominal Returns & Risk Statistics w/ 50/200 day SMA Cross Market Timer (Lowest Decile Beta Filter) (01/09/99 - 10/14/17)
Cornerstone Value vs SPY, Nominal Returns & Risk Statistics w/ 50/200 day SMA Cross Market Timer (Lowest Decile Beta Filter) (01/09/99 – 10/14/17)

So the key takeaways:

  • Free trades are awesome (like with Robinhood).
  • For the most part (with the exception of low starting capital/high transaction fees/high tax bracket), cornerstone value outperformed buying and holding SPY out of sample (1999 to 2017).
  • This strategy can be implemented on its own or in conjunction with other strategies I’ve discussed, such as market timing.

As of 10/14/17, the top 5 stocks for the cornerstone value strategy (highest yielding among market leaders) are ETP, CTL, MBT, EPD, & ETE.

This strategy screen is available to my group on Portfolio123, where you can customize it or implement it as is. If you just want the stock picks, you can subscribe on Patreon below.

Health vs. Wealth: Drinking, Eating, Smoking, and Gambling Stocks

Over the past 17 years, investing in vice stocks (the S&P 500 stocks within the following GICS sub-industries) delivered almost triple the annual return than SPY (S&P 500 index fund):

  • Brewers – 30201010
  • Distillers & Vintners – 30201020
  • Soft Drinks – 30201030
  • Tobacco – 30203010
  • Casinos & Gaming – 25301010
  • Restaurants – 25301040

For this time period, the number of stocks in these sub-industries in the S&P 500 ranged between 14 and 20. I’ve abbreviated these as BeSToGaR (Beer, Spirits/Soft Drinks, Tobacco, Gaming, Restaurants).

Only investing in the top 3 of these stocks (as ranked by the 2 factors from a famous formula) and rebalancing every 3 months pushes the CAGR a few percentage points higher, though at the expense of a larger drawdown.

Widening the net to include stocks within the Russell 3000 (also top 3 with a 3 month rebalance) also improves performance.

Adding the drug retail (GICS 30101010) and food retail (GICS 30101030) is another iteration to consider. (BeSToGaRR; extra R for Retail).

Investing in vice stocks; Performance chart of the BeSToGaR/R quantitative investing strategy.
Performance chart of the BeSToGaR/R strategy.
Investing in vice stocks; Performance statistics of the BeSToGaR/R strategy.
Performance statistics of the BeSToGaR/R strategy

To replicate or refine this quantitative investing strategy, click here.

Trending Value: Breaking Down a Proven Quantitative Investing Strategy

$10,000 invested into the trending value strategy in 1963 became over $69M in 2009. The strategy was published in 2011 and has continued to work since.

What I’m about to introduce to you is not black magic. And I say that because if you’re a realist like me, anytime someone comes to you with something that sounds too good to be true, it’s almost always too good to be true (or a pyramid scheme). Update: see my post attempting to answer the skeptics.

But this strategy is rigorously backtested and rooted in common sense. It isn’t about finding correlations between obscure financial metrics and stock performance to formulate a otherwise seemingly random strategy.

Every metric in this strategy is commonly used by millions of investors every day; but when they are combined in a specific way, the results can be extraordinary.

Nominal Return, Trending Value vs All Stocks (1964-2009)
Nominal Return, Trending Value vs All Stocks (1964-2009)
The trending value strategy was developed by James O’Shaughnessy and detailed in his book What Works on Wall Street as one of the best performing strategies, using a combination of value and growth metrics, terms you’ve probably heard of or seen marketed in ETFs or mutual funds.

Value investing is a well-known investment strategy that aims to select stocks that the market has undervalued – that is, the stock’s price is lower than what its fundamentals suggest it is actually worth.

O’Shaughnessy begins by backtesting strategies using one value metric at a time. For example, a strategy that is only invested in the stocks in the top decile (lowest 10%) of price-to-earnings ratios (P/E) and rebalanced every year. And likewise using price-to-book ratio (P/B), price-to-sales ratio (P/S), and price-to-cash flow ratio (P/CF). He also looks at enterprise value to EBITDA (earnings before interest, taxs, depreciation and amortization) ratio (EV/EBITDA), which was the single best performing value factor he backtested. (For each of these 5 factors, low values are better).

Another factor he looked at was shareholder yield (SHY), which is buybacks (how many stocks are repurchased by the company (i.e., decrease in number of outstanding shares)) plus dividends divided by market capitalization. (For shareholder yield, higher is better). The results for the top decile of these factors (lowest (or highest for SHY) 10%, rebalanced annually) are below (with all stocks for comparison).

Performance of the Top Deciles of Various Value Factors of the Trending Value Strategy (1964-2009)
Performance of the Top Deciles of Various Value Factors of the Trending Value Strategy (1964-2009)

By themselves, all of these factors beat the overall stock market. But combining the factors, coming up with a composite score and investing in the top decile of composite scores, yields even better results. To develop the composite scores, a ranking for each factor is given to each stock in the universe of stocks. So the stock with the lowest P/E gets a score of 100, the stock with the lowest SHY gets a 1, and so on (this can be done with the PERCENTRANK function in Excel (or 1 – PERCENTRANK for SHY, since higher numbers are better), or much more seamlessly using a more powerful tool like Portfolio123).

The ranks for each factor of a stock are added up for its composite score. O’Shaughnessy looked at 3 different value composite scores: value composite 1 (VC1) used the factors described above except SHY, value composite 2 (VC2) add SHY to VC1, and value composite 3 replaces SHY with just buyback yield. The returns for top decile of each of these composite scores is below (rebalanced annually).

Performance of Value Composites VC1, VC2, and VC3 (1964-2009)
Performance of Value Composites VC1, VC2, and VC3 (1964-2009)

Each value composite is a significant improvement over any individual factor. Composites are more powerful than just screening for the best values of the individual factors because a stock that may be deficient in one metric but excellent in the others would get eliminated from consideration by screening (e.g., a stock in the top decile of VC2 may not necessarily be in the top decile for all of the individual factors).

To implement the trending value strategy, you simply invest in the top 25 stocks sorted by 6-month % price change (the “trending” part of the name) among the top decile of stocks ranked by VC2 (O’Shaughnessy chose VC2 over VC3 because of its slightly higher Sharpe ratio, a measure of risk-adjusted return).

The universe of stocks is limited to those with a market capitalization of more than $200M (in 2009 $) to avoid liquidity problems with trading smaller stocks. It’s a buy and hold strategy that is rebalanced annually with the following exceptions. If a company fails to verify its financial numbers, is charged with fraud by the Federal government, restates its numbers so that it would not have been in the top 25, receives a buyout offer and the stock price moves within 95% of the buyout price, or if the price drops more than 50% from when you bought it and is in the bottom 10% of all stocks in price performance for the last 12 months, the stock is replaced in the portfolio.

So what’s the catch? There are a few:

  1. The Data: While most of the metrics described are freely available from any number of online sources, some (e.g., buyback yield) aren’t as easy to come by, and I still haven’t found a free way to obtain all of the data for all of the stocks at once.
  2. Psychology: While the trending value strategy has never underperformed the market for any rolling 5-, 7-, or 10-year periods between 1964 and 2009, it has underperformed the market for rolling 1-year periods 15% of the time, and 3-year period 1% of the time. If you hit a few years with less-than-stellar performance, are you going to stick it out and trust the strategy, or are you going to jump ship to bonds (as many people did in 2009, missing out on the huge subsequent rebound) or another trendy strategy that seems to be performing better at the time?
  3. Commissions (for small-time investors): At $10/trade and 25 trades per year, you need a portfolio of $100,000 to keep your commissions to a reasonable 0.25%.
You can learn how to implement the trending value strategy here, so number 1 is solved. Number 2 is on you. And number 3 is covered here.