Professor Francois-Eric Racicot doesn’t mince words about the need to pay close attention to measurement errors in financial return models. “This is an extremely important subject, because when you measure your data badly, all your conclusions are biased,” says Racicot, an expert in financial econometrics, or the application of mathematics and statistical methods to financial data.
Racicot has shown how this problem affects the management of hedge funds – aggressively managed portfolios that are often associated with a high degree of leverage and borrow to achieve the aim of high targeted returns. But, he adds, measurement errors also plague financial return models used in a great many other areas of finance and economics, such as corporate finance.
So Racicot isn’t at all surprised to hear that as researchers like him investigate new ways to identify and track the effect of measurement errors, portfolio managers, bank managers, and managers of financial and economic risk are taking a keen interest in the results.
“The methods I am proposing improve the estimation of two variables,” explains Racicot, who has taught finance for more than ten years. “The first of them helps you select the assets; the second tells you the risk of fluctuation. In the world of portfolio management, it has a practical benefit in helping you select the assets to put into your portfolio.”
Racicot has published several graduate-level texts in quantitative finance and financial econometrics and is a member of the editorial board of several highly-regarded journals. He contributes to the CGA-Canada Accounting and Governance Research Centre at the Telfer School. He is also a research associate at the Corporate Reporting Chair at l'Université du Québec à Montréal (UQAM).
Racicot says he has recently demonstrated that his methods are also pertinent to the measurement of accounting errors, “and scientifically, the results have been even better than the ones on hedge funds.”