John P. Reese

About the Author John P. Reese

John P. Reese is considered an expert in the systematic investing methodologies of legendary investors, including Peter Lynch, Ben Graham, Warren Buffett and many others. He has been active in the development of fundamentally-based quantitative models since the mid-90s. His commentary and research on Seeking Alpha will include stock ideas, strategy related pieces, value investing concepts, behavioral finance related posts, systematic and modeling methods as well as other long term investing concepts. John is founder and CEO of Validea.com and also co-founder of Validea Capital Management, a separate account asset management firm serving individuals and institutions. John sub-advises the National Bank Consensus American and International Equity Funds offered in the Canadian market. He holds two U.S. patents in the area of automated stock analysis and is considered an expert in the field of quantitative stock selection using the strategies of investing legends. John is a columnist for TheStreet.com, Forbes.com and Canada's Globe & Mail and is co-author of “The Guru Investor: How to Beat the Market Using History’s Best Investment Strategies". He holds a master's of business administration from Harvard Business School and a degree in computer science from MIT. A more complete biography can be found here: http://en.wikipedia.org/wiki/John_P._Reese

When It Comes To Stocks, Trust Fundamentals – Not Forecasts

  • Forecasts are everywhere in the stock market, but more often than not they are wrong.
  • Trust a stock's fundamentals and financials – not forecasts – when analyzing equities.
  • Here are five fundamentally and financially sound stocks that get high marks.
 

"Analyst Predicts Apple Will Buy Tesla For $75 Billion."

"Bad news: Stocks Likely To Fall Further."

"The Fed Expects A Strong US Economy In 2015."

What do all these have in common? First, they are all recent headlines from financial news outlets. Second, they are all probably just as likely to be erroneous predictions as they are likely to be on the money, if history is any guide. That's because forecasters have a pretty dicey collective track record.

For proof, just look at the Survey of Professional Forecasters historical data, available on the Federal Reserve Bank of Philadelphia's web site. In a May 2008 report, for example, the group said the average predictions for U.S. gross domestic product growth in the third and fourth quarters of 2008 were 1.7% and 1.8%, respectively. In reality, they turned out to be -4.0% and -6.8%. At that point, the average forecast for the average 2009 unemployment rate was 5.6% – in reality, unemployment ranged from 7.8% to 10.1% throughout the year.

Forecasters also often miss the mark when it comes to predicting stock market returns. In a February 2000 SPF report, for example, the mean forecast for annual stock returns over the next decade was 9.1%. Over the next 10 years, the S&P 500 ended up well in the red, however.

Contrarian guru David Dreman also did a lot of research into the topic of analysts' earnings forecasts. In his book Contrarian Investment Strategies, he wrote that "there is only a 1 in 130 chance that the analysts' consensus forecast will be within 5 percent for any four consecutive quarters. …To put this in perspective, your odds are ten times greater of being the big winner of the New York State Lottery than of pinpointing earnings five years ahead."

Then there's the work of University of California Berkeley Professor Philip Tetlock. His 2005 book Expert Political Judgment: How Good Is It? How Can We Know? examines a seven-year study Tetlock conducted in which supposed experts and non-experts were asked to predict an array of political and economic events. His findings: While the "experts" tended to beat the non-experts, the best human forecasters "were hard-pressed to predict more than 20 percent of the total variability in outcomes" of events. Tetlock, now at the University of Pennsylvania, found that algorithms – statistical models – were better forecasters. Relatively crude algorithms could predict 25% to 30% of the total variability in outcomes, while more sophisticated algorithms came in at 47% – more than twice as accurate as human experts.

Fundamental Analysis

Now, all of this isn't to say that human forecasters are always wrong. There are some good ones out there. But many of the headlines you'll see cite prognosticators with dubious track records who are making highly subjective, often speculative predictions. Trusting them can get you into big trouble.

So who or what can you trust? The numbers. That's how great investors like Warren Buffett, Peter Lynch and Benjamin Graham have been so successful. They don't play hunches or make big bets on speculative macroeconomic forecasts – they look at fundamentals and financials. And because any one number can mislead, they look at a range of fundamentals to get an overall sense of a stock's attractiveness – profitability metrics, valuation, debt load and beyond.

My Guru Strategies, which are based on the approaches of Buffett, Lynch, Graham, Dreman and other investing greats, look at a diverse array of fundamentals when selecting stocks. Fundamental strategies like these won't be right on every pick. But if you use a good one and stick with it, you're likely to be right more often than you're wrong. In the stock market, doing that usually produces very strong returns – and, I believe, put you in a much better position than you'd be if you based picks on macroeconomic forecasts and analysts' estimates.

With all that in mind, here's a look at a handful of stocks that get high marks from our fundamental-focused strategies.

AmTrust Financial Services Inc (NASDAQ:AFSI): Amtrust ($4.6 billion market cap) is a multinational property and casualty insurer specializing in coverage for small businesses. It offers workers' compensation insurance, extended warranty coverage, specialty middle-market property and casualty insurance and a host of related products and services.

Amtrust gets strong interest from several of my models, including the model I base on the writings of James O'Shaughnessy. When looking for growth stocks, this approach looks for firms that have upped earnings per share in each year of the past five-year period, which Amtrust has done. The model also looks for a key combination of variables: a high relative strength, which is a sign the market is embracing the stock, and a low price/sales ratio, which is a sign it hasn't gotten too pricey. Amtrust has a red-hot 12-month relative strength of 89, and its P/S ratio of 1.1 comes in well below this model's 1.5 upper limit.

Quanta Services Inc (NYSE:PWR): Like many oil industry-related stocks, Quanta struggled amid the oil price plunge. But my Kenneth Fisher-inspired model thinks that's made the firm, a provider of specialty contracting services that offers infrastructure solutions primarily to the electric power and natural gas and oil pipeline industries, a bargain. It likes Quanta's 0.75 price/sales ratio, 2% debt/equity ratio, and 5% three-year average net profit margins.

OmniVision Technologies, Inc. (NASDAQ:OVTI): OmniVision designs and markets high-performance semiconductor image sensors. Its OmniPixel and CameraChip products are highly integrated single-chip CMOS image sensors for mass-market consumer and commercial applications such as mobile phones, notebooks and webcams, digital still and video cameras, security and surveillance systems, entertainment devices, and medical imaging systems.

OVTI ($1.5 billion market cap) gets strong interest from my Peter Lynch-based model. The Lynch strategy considers it a "fast-grower" – Lynch's favorite type of investment – thanks to its impressive 42% long-term earnings per share growth rate. (I use an average of the three-, four-, and five-year EPS growth rates to determine a long-term rate; in OVTI's case the five-year is unavailable, so I use an average of the three- and four-year rates.) Lynch famously used the P/E-to-Growth ratio to find bargain-priced growth stocks, and when we divide OVTI's 15 price/earnings ratio by that long-term growth rate, we get a PEG of 0.36. That comes in well under this model's 1.0 upper limit.

Chart Industries, Inc. (NASDAQ:GTLS): Chart ($1 billion market cap) makes highly engineered equipment used in the production, storage and end-use of hydrocarbon and industrial gases. It meets the fundamental criteria of the model I base on the writings of Benjamin Graham, who is known as "The Father of Value Investing." The firm has a 2.1 current ratio, beating the model's 2.0 target, and more net current assets ($317 million) than long-term debt ($204 million), meeting another key Graham-based financial test. It trades for under 15 times three-year average earnings (13.6) and the product of its P/E and price/book ratio (1.2) is under 22, passing two Graham-based valuation tests.

Sodastream International Ltd (NASDAQ:SODA): While it has become a big name in recent years, this firm began introducing solutions to the beverage market in 1903 with a system that enabled consumers to carbonate water at home. Today, it is the world's largest manufacturer, distributor and marketer of home carbonation systems, with machines being sold in over 60,000 retail stores, in 45 countries worldwide.

Israel-based Sodastream ($400 million market cap) gets strong interest from my Peter Lynch-based strategy. The Lynch-based model likes its 47% long-term EPS growth rate and 0.3 PEG ratio.

  • Talking about trusting numbers, Benjamin Graham himself wrote:
    “Operations for profit should be based not on optimism but on arithmetic.”

    Benjamin Graham – also known as The Dean of Wall Street – was a scholar and financial analyst who mentored legendary investors such as Warren Buffett, William J. Ruane, Irving Kahn and Walter J. Schloss.

    Warren Buffett once wrote a detailed article explaining how Graham’s record of creating exceptional investors (such as Buffett himself) is unquestionable, and how Graham’s principles are everlasting. The article is called “The Superinvestors of Graham-and-Doddsville”.

    Buffett describes Graham’s book – The Intelligent Investor – as “by far the best book about investing ever written” (in its preface).

    Graham’s first recommended strategy – for casual investors – was to invest in Index stocks.
    For more serious investors, Graham recommended three different categories of stocks – Defensive, Enterprising and NCAV – and 17 rules for identifying them.
    For advanced investors, Graham described various “special situations”.

    The first requires almost no analysis, and is easily accomplished today with a good S&P500 Index fund.
    The last requires more than the average level of experience, intuition and talent. Such stocks are not amenable to impartial quantitative analysis, and require a case-specific approach.

    But Defensive, Enterprising and NCAV stocks can be reliably detected by today’s data-mining software, and offer a great avenue for detailed objective analysis and profitable investment.

    For example, given below are the actual Graham ratings for Chart Industries Inc (GTLS), with no adjustments other than those for inflation.

    Defensive Graham investment requires that all ratings be 100% or more.
    Enterprising Graham investment requires minimum ratings of – N/A, 75%, 90%, 50%, 5%, N/A and 137%.

    Chart Industries Inc – Graham Ratings
    Sales | Size (100% ⇒ $500 Million): 234.20%
    Current Assets ÷ [2 x Current Liabilities]: 65.03%
    Net Current Assets ÷ Long Term Debt: 230.77%
    Earnings Stability (100% ⇒ 10 Years): 100.00%
    Dividend Record (100% ⇒ 20 Years): 0.00%
    Earnings Growth (100% ⇒ 30% Growth): 69.69%
    Graham Number ÷ Previous Close: 97.02%

    Not all stocks failing Graham’s rules are necessarily bad investments. They may fall under “special situations”. Graham’s rules are also extremely selective. Graham designed and backtested his framework for over 50 years, to deliver the best possible long-term results. Even when stocks don’t clear them, Graham’s rules give a clear quantifiable measure of a stock’s margin of safety.

    Thank you.