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John Reese is chief executive officer of Validea.com and Validea Capital, the manager of an actively managed ETF. Globe Investor has a distribution agreement with Validea.ca, a premium Canadian stock screen service.

When it comes to elections or economic issues, there’s always a group of experts everyone turns to for predictions and forecasts. They aren’t always right.

Forecasting is difficult even with the best available data. Few people predicted the election of Donald Trump in 2016, and yet, here we are halfway through his presidential term. Last week’s midterm elections, throwing the U.S. House of Representatives back to the control of the Democrats, was in keeping with the expected outcome, but few could have foreseen the turbulence in the markets leading up to polling day.

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How some experts manage to be more credible than others was the subject of a 2005 study by University of Pennsylvania professor Philip Tetlock. He discovered the so-called experts could explain only 20 per cent of the variability in the outcomes of their predictions. Indeed, the more famous the expert, the less accurate he or she tended to be. This was regardless of educational background, experience and access to information.

Investing involves analysis and prediction, often with undesired outcomes. The go-to “experts” in the field tend to have the outlandish ideas or use their force of personality to drown out other voices. They tend to make good sound bites.

In his book, What Works on Wall Street, the investing guru James O’Shaughnessy, founder of O’Shaughnessy Asset Management, argued that human forecasters fail because they are influenced by emotion, make inconsistent judgments, behave in short-sighted ways or are overconfident about their abilities. In turn, investors’ inability to follow a disciplined approach prevents them from beating the market.

When it comes to macroeconomic forecasting, what has happened in the past isn’t always a perfect road map for the future. Investors don’t always apply that same reasoning to the markets. They rely on technical signals, sentiment, momentum or hunches, believing they have the insight needed to make sound investment decisions. Mr. O’Shaughnessy suggests it’s simpler than that. Investors can look at long-term historical trends to develop a stock-selection process for growth and value.

But short of that, investors only need to pick a strategy and stick to it through thick and thin. It’s the emotion that gets in the way.

Another investing legend, Benjamin Graham, would say investors need to control themselves at their own game instead of worrying about beating others at theirs.

Of course, not all forecasts are wrong. We hear about the professional traders who accurately predict a company’s demise and profit off the short-sale. Pros who accurately call shifts in the near-term market direction get a lot of attention. But there are some false positives along the way. The person with the next accurate bear market call is only recognized in hindsight.

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There is some benefit to being an expert. Mr. Tetlock’s research found that ordinary forecasters working in teams would do about 10 per cent better than a crowd at predicting an outcome. But experts would do as much as 30 per cent better than that.

What some forecasters fail to factor into their analysis are the factors they don’t know – unknown unknowns. It’s impossible to predict every possible deviation in the market or to understand what you don’t even know. The best solution for investors, then is to stick to data and fundamental analysis, the things you know and can discover.

Quantitative stock-screening models take the emotion out of investing and help prevent investors from buying or selling stocks at the wrong time. That’s why we designed portfolios that track the quantitative strategies of several successful investors who believe in companies that have solid fundamentals. By focusing on what is known and removing the guesswork from the process, we can identify solid businesses that are well situated to thrive over the long term.

Here are three stocks that score highly on these models:

Orix Corp. (IX-NYSE) – This specialty lending and leasing operation scores highly on the models tracking the investment styles of Mr. O’Shaughnessy and John Neff, the notable value investor who once ran Vanguard’s Windsor Fund. It has a relatively low price-to-earnings ratio of 7.8 and long-term annualized earnings-a-share growth of 16.5 per cent.

Children’s Place Inc. (PLCE-Nasdaq) – This children’s clothing retailer scores highly on the models tracking Mr. O’Shaughnessy and Peter Lynch, former star mutual fund manager at Fidelity, and also highly using the model outline by Kenneth Fisher, CEO of Fisher Investments, in his book Super Stocks. Mr. Lynch’s model would categorize it as a “fast grower,” with a price-earnings-to-growth ratio of 0.6.

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SVB Financial Group (SIVB-Nasdaq) – This financial services company is based in the fast-growing Silicon Valley market and scores highly on the models tracking Mr. Lynch and Martin Zweig, a top-ranked growth investor during the eighties and nineties. Long-term annualized revenue growth of 18 per cent supports its earnings growth rate of 20 per cent.

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