When scouring the investment universe for unique opportunities, advisors often rely on quantitative screening systems to narrow down the range of possibilities. These tools do the jobs nobody wants: combing through thousands of companies, crunching millions of numbers from financial statements, and calculating standard valuation measures to rank those companies.

Advisors tend to have different approaches to quant systems, ranging from the basic (simply validating existing holdings) to the more complex (searching less-travelled parts of the market for new investment ideas).

By using a quant system, advisors can identify which stocks meet predetermined criteria, such as those that

  • have market caps greater than $1 billion;
  • have seen higher than 10% average EPS growth over the last five years; and
  • are currently trading at less than 12x earnings.

Nothing takes the place of quant screens to reduce workload, but they tend to suffer from a major flaw: they’re backward-looking. Estimating where a stock will go based on where it’s just been is always risky. This approach can easily be ruined by shifts in market sentiment and other macro factors. Some quant systems attempt to be more forward-looking by backtesting investment criteria over longer periods.

The aim is to show how a certain set of criteria might have performed over the longer term under varying market conditions. But that so-called time-tested approach also fails because, no matter how far you look back, accounting volatility always obscures the rearview mirror. In fact, the farther you go back, the hazier the picture gets.

Accounting volatility

Accounting volatility is created when accounting rule changes impact the way companies present their results. When a rule changes, companies often recalculate their results for the previous year under the new approach and then use that method going forward.

That behaviour is like recalibrating a measuring stick. The same company in the same year will have two sets of results. So which gets used in the quant program? More importantly, how did the change in accounting rules disrupt the trend line, and how useable are the results for backtesting investment criteria?

The upshot is the company now has two trend lines: one stretching backwards from the date of the change, and one stretching forward, calculated using a different measuring stick.

Now multiply that out, and consider that major rules changes occur in accounting regularly. That spawns multiple trend lines (beginning and ending at different dates), which overlap and create permutations of results under varying measuring sticks. Lastly, factor in Canada’s switch to International Financial Reporting Standards (IFRS) three years ago, which resulted in the most massive upheaval in reported results investors have ever seen.

IFRS marked a shift in the substance of accounting, a change in the focus of what was supposed to be measured. To simplify, IFRS
rules put more emphasis on attempting to fair value assets and liabilities based on management estimates. The old accounting rules were more centred on measuring earnings power and separating income from capital.

The result of IFRS is that, on average, Canadian companies are reporting higher assets, liabilities, profit margins, net income and operating cash flows. Thanks to IFRS, the trend is no longer your friend. Backtesting quantitative investment criteria beyond four years is useless, given the changes IFRS ushered in. Even the auditors, who are the biggest proponents of IFRS, warn against comparing pre- and post-IFRS figures.

While the big IFRS hump may be moving slowly into the distance, the slate of upcoming changes to IFRS rules stretches years into the future. With big expected changes to accounting for leases, revenue recognition, insurance contracts, financial instruments and more, there’s little hope investors will get a reprieve from accounting volatility anytime soon.

Some quant adherents say that as long as the same accounting measuring stick is used for all companies in the same year, the accounting distortions will be somewhat equal and companies can be measured on a relative basis. That idea doesn’t hold up because companies are often given significant choice as to when and how they implement new accounting rules; and their different choices mean results aren’t comparable to peers’ in any given year.

These management choices can have major impacts on how companies calculate assets, income and cash flows (see “Accounting choices impact reported cash flows,” AER February 2014), and cannot be picked up or screened out by quant-based systems.

Looking at quant screens

There are good and bad ways to employ quant screens. They’re great for crunching large amounts of data and identifying new investment ideas. But, because of accounting volatility and backward-
looking bias, they can’t be used to effectively backtest investment criteria or to set up a quant-based investing model.

Before setting criteria to search for new investment ideas, advisors should consider a few factors. First, not all sectors should be treated the same. For instance, a low return on assets in the service sector may be highly attractive in a more capital-intensive segment like industrials.

Second, advisors should set wider ranges in their criteria to ensure accounting volatility isn’t missing good opportunities or rewarding sectors that benefit more from IFRS changes. CGA-Canada published a study last fall warning investors to be particularly mindful of the finance, management, retail, transport, professional services and real estate sectors.

It’s also important to monitor accounting issues on a continuous basis for insight into where any margins of safety need to be widened. Once a screen has identified a new investment idea, the real work begins. The company has to be fully investigated and advisors can then turn to the fundamental analysis tools at their disposal.

Be wary of quantitative screening tools


  • Great for crunching large amounts of data
  • Good for identifying potential investment ideas


  • Major flaw of being backwards-biased
  • Not able to handle constantly changing accounting rules and volatility


  • Don’t treat all sectors the same
  • Don’t use to backtest investment theories or build models
  • Always do the fundamental follow-up work on a stock
  • Use wider margins of safety when setting investment criteria