Lessons Learned from Schwab Equity Ratings' First 10 Years

May 21, 2012

Greg Forsythe
CFA, Senior Vice President, Schwab Equity Ratings®, Schwab Center for Financial Research

Schwab Equity Ratings® were first provided to clients on May 6, 2002. We had two primary goals at inception: First, we sought to provide clients with stock research that was objective and simple to interpret. We believe the Schwab Equity Rating letter-grade system and advice guidelines have helped us accomplish this first goal from the beginning.

Five Ratings From A to F

Our second goal was for our average buy-rated stock to clearly outperform our average sell-rated stock over a full market cycle (i.e., market peak to peak, or market trough to trough). From the outset, Schwab took the bold step of posting on our website the performance track record of every stock we've ever rated. We felt it only fair to hold ourselves accountable for the performance of our ratings if we expected clients to trust and follow our advice.

How have Schwab Equity Ratings performed?

As Schwab Equity Ratings reach their 10-year anniversary, now seems like a great time to see whether our second goal has been achieved. Clients can log on to schwab.com/stocks, click on Schwab Equity Ratings® Performance and see a chart that summarizes performance since inception, along with an explanation of how these numbers were computed.

Average Schwab Equity Ratings Returns¹

Source: Schwab Center for Financial Research. Average percent return of all 52-week periods from May 6, 2002 through May 11, 2012.

We believe Schwab Equity Ratings have historically provided meaningful return discrimination on a 52-week buy-and-hold basis.

You might ask, "How good is this performance?" While other brokerage firms typically don't share their historical performance, the Institutional Brokers Estimate Service (IBES) has compiled nearly all the brokerage-firm ratings available on thousands of stocks going back in time.

Using the IBES database, Schwab tested the historical performance of stocks grouped according to the average broker rating versus stocks grouped by the five Schwab Equity Ratings. The chart below shows that our ratings have been far more effective in discriminating future 12-month performance. In fact, the highest-ranked stocks according the average broker rating have historically underperformed their lowest-ranked stocks!

Hypothetical Performance Comparison: Schwab Equity Ratings Vs. Broker Consensus Ratings

Source: IBES, Schwab Center for Financial Research, May 2002-April 2012. IBES collects analyst stock ratings (e.g., buy/hold/sell recommendations) from more than 100 brokerage firms, transforms them to a numerical 1 to 5 scale, and averages the ratings for each stock into a "consensus" rating. For these tests, Schwab established a universe of the top 3,200 market-capitalization stocks at the end of each month. Then, within the 3,200 stocks, only stocks with both Schwab Equity Ratings and IBES consensus ratings were ranked into five cohort (hypothetical) portfolios (i.e., the top 5% of stocks were ranked into portfolio #1, the next 25% into portfolio 2, the next 40% into portfolio 3, the next 25% into portfolio 4, and the last 5% into portfolio 5) based on Schwab Equity Ratings and IBES consensus ratings. Stocks in each portfolio were held constant and average total returns (including reinvestment of dividends) over the subsequent one-year period were compiled for each portfolio. No transaction costs were subtracted from returns. Returns shown are the average of each portfolio's annual returns from May 31, 2002 to April 30, 2012.

Some things don't change….

Since a stock's current price reflects collective expectations of future fundamentals, meaningful price changes occur only when investor expectations change. For example, when a company reports earnings above prior market expectations—a positive earnings surprise—the company's stock price often rises as investors adjust future earnings expectations upward. Therefore, a key element to a market-beating stock selection strategy can be "surprise anticipation." If your stock picks experience positive surprises more often than negative surprises, you have a chance to outperform the market in the long run.

Investors often use analyst earnings forecasts to gauge market expectations for individual stocks. But Schwab and many independent researchers have found that analyst forecasts of future earnings are extremely inaccurate. As a result, the chart below shows that stocks with high, average or low earnings growth forecasts performed about the same during the 1990s (even including the technology-stock bubble period) and continued to perform similarly in the 2000s. In my opinion, picking stocks on the basis of their forecasted earnings growth is unlikely to be an effective strategy in the future.

Hypothetical Stock Performance When Ranked by Forecasted Five-Year Earnings Growth

Source: IBES, Schwab Center for Financial Research. IBES collects analyst five-year earnings-per-share growth-rate forecasts from more than 100 brokerage firms and averages them for each stock into a "consensus" long-term earnings per share (EPS) growth-rate forecast. For these tests, Schwab established a universe of the top 3,200 market-cap stocks at the end of each month, then ranked them into uniform quintile cohort (hypothetical) portfolios (i.e., the top 20% into portfolio #1, the next 20% into portfolio #2, etc.) based on consensus EPS-growth forecasts. Stocks in each portfolio were held constant and average total returns (including reinvestment of dividends) over the subsequent one-year period were compiled for each portfolio. No transaction costs were subtracted from returns. Returns shown are average of each hypothetical portfolio's annual returns from December 31, 1989 to April 30, 2012.

Rather than being based on earnings forecasts, Schwab Equity Ratings' foundational strategy has always been based on "surprise anticipation." We attempt to anticipate surprise in two ways: First, we've found that investors seem to believe that successful companies will continue to succeed and that struggling companies will continue to struggle. Yet research has shown that competitive forces typically lead to long-term business success being more likely to reverse than be sustainable. So when investor expectations are extremely low for a stock, you may anticipate future surprises to be positive as the company does better than pessimistic expectations. Conversely, with high expectations you may anticipate negative future surprises, as the company falls short of optimistic expectations.

Second, we've found that investors can be reluctant to change their beliefs. For example, if a company reports strong earnings, investors typically notch up their future expectations, but seek further confirmation by waiting to see if the company can do it again the following quarter. This "anchor and adjust" process creates a tendency for short-term expectation changes to lag behind fundamental reality.

Therefore, a second powerful way to anticipate surprises is to bet on systematic underreaction to newly reported information. If recent expectation changes have been positive for a stock, you may expect more positive changes in the near future as expectations play catch-up, and by the same token, if expectations have been negative, you may expect more negative changes.

Schwab has created a matrix that encapsulates these general tendencies. As the graphic below illustrates, our belief is that stocks with low-but-rising expectation levels tend to report positive surprises while stocks with high-but-falling expectations tend to report negative surprises.

Surprise-Anticipation Matrix

…but not everything remains the same

Surprise anticipation remains the foundation for Schwab Equity Ratings. However, our research has found that some of the factors for identifying stocks most likely to surprise have changed over the years. For clarity, a "factor" is any metric, such as dividend yield or revenue growth, that can be used to compare or rank stocks relative to one another. Schwab Equity Ratings are computed by ranking stocks according to a proprietary set of stock-selection factors.

For example, the chart below compares the average information coefficient (the correlation between factor values and subsequent stock returns) of several stock-selection factors from 1991 to 2001 and March 2002 to March 2012. At inception in 2002, Schwab Equity Ratings employed factors that measured stocks' earnings quality, free-cash-flow generation, and six-month stock-price momentum. These factors were useful in predicting surprise during the 1990s, but their effectiveness has dropped dramatically over the past 10 years and they are therefore no longer an input to our ratings.

Interestingly, two of the most simple and useful surprise-anticipation factors—the earnings / price ratio and the consensus five-year earnings-growth forecast—have largely retained their significant correlation with annual returns. Note the significant negative correlation between forecasted earnings growth and subsequent returns!

Hypothetical Performance of Selected Factors on Largest 3,200 Stocks

For this test, Schwab established a universe of the top 3,200 market-cap stocks at the end of each month, then ranked the stocks into uniform quintile cohort (hypothetical) portfolios (i.e., the top 20% were ranked into portfolio #1, the next 20% into portfolio 2, etc.) based on five different factors: 1) earnings quality (cash flow from operations less net income) ÷ (market cap plus long-term debt), 2) free cash flow ÷ common equity, 3) prior six-month stock-price change, 4) four-quarter operating earnings per share ÷ stock price, and 5) IBES five-year consensus EPS growth forecast (data sources: FactSet, Compustat and IBES). Stocks in each cohort portfolio were held constant and average total returns (including reinvestment of dividends) over the subsequent one-year period were compiled for each portfolio. No transaction costs were subtracted from returns. Returns shown are the average of each portfolio's annual returns from December 31, 1990 to December 31, 2001 and March 31, 2002 to March 31, 2012.

Commitment to ongoing research

The market environment is constantly changing, often in ways that diminish stock-selection strategies that once may have been effective.

• The competition to identify potentially mispriced stocks keeps intensifying. For example, hedge funds manage far more assets than ever before.
• The computing power applied to research and trading dwarfs that used just 10 years ago.
• Regulations controlling accounting standards and information disclosures have evolved, making it more difficult to uncover proprietary information.
• Corporations and analysts have both learned to underestimate their earnings forecasts so that positive earnings surprises are much common now than in the 1990s.

As a result, we believe continuous research is critical to try to maintain the historical performance of Schwab Equity Ratings.

Implementation remains a key

Of course, Schwab Equity Ratings don't guarantee investment success; they're a tool that must be used properly and with discipline. Unfortunately, that's easier said than done.

The application of psychology to investing was a novel idea in the early 1990s. Today, behavioral-finance research is highly visible, and discoveries in this field are humbling. For example, behaviorists have found that investors are often their own worst enemy. While investors intuitively know that no strategy works all the time, psychological pain from losses (actual or perceived) is so intense that investors often abandon sound strategies at the worst possible time.

We hope the research behind Schwab Equity Ratings helps clients prevent emotions from clouding their decision-making process. Though the world keeps changing, our guidance to clients interested in managing a portfolio of individual stocks remains the same: Build a diversified portfolio by buying stocks rated "A" or "B" and avoiding stocks rated "D" or "F."

For more details on the research behind Schwab Equity Ratings and how to use them, we encourage you to read Schwab Equity Ratings® Foundations and Managing a Stock Portfolio Using Schwab Equity Ratings.

1. To calculate performance, Schwab follows a straightforward approach. First, we create five cohorts (defined as those stocks that received the same A, B, C, D or F rating on the start date). Schwab then calculates the total return for each stock in each A - F rating cohort by dividing the ending price, plus dividends paid during the period (if any), by the starting price for a particular holding period, minus one. Returns are calculated based on the market-closing prices on the holding period start date and the market closing prices on the holding period end date. Start dates and end dates are the first trading day of the week.

All stocks within a rating cohort are equal-weighted at the beginning of the performance calculation period, meaning each stock has the same value relative to any other stock. Performance is calculated assuming stocks are held for the entire holding period, unless the stock stops trading during the period due to acquisition, financial distress, delisting by an exchange or other similar circumstance. If the stock has stopped trading, the stock is assumed to have been liquidated on the close of its last trading day, without transaction costs. Proceeds, if any, are held as non-interest-bearing cash. After individual stock returns are calculated, Schwab averages the total returns for all stocks within a cohort during that time period to find the average return.  Transaction costs such as brokerage commissions, fees or other expenses have not been deducted from the total return calculations. Results would have been lower if such costs were deducted.

Model performance results have certain inherent limitations. Unlike an actual performance record, simulated (hypothetical) results do not represent actual investment performance or trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as the effect of limited trading liquidity. No representation is being made that any investor will or is likely to achieve profits or losses similar to those shown.