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The RBC Quantitative Investments Team has members in both Toronto and Vancouver, Canada. The team is comprised of investment professionals with a diverse range of skills, specializing in both quantitative research and portfolio management. We look at an enormous amount of data across many different investment signals, applying a proprietary approach to factor construction and risk modelling that is executed in a disciplined and consistent manner. Our portfolios are designed to achieve the optimal risk-return profile, backed by empirical research.

Proprietary modeling

Benefit from a quantitative discipline and proprietary quantitative modeling that seeks to deliver consistent positive returns with low volatility over the long term.

Low volatility

Our low-volatility strategies may be suitable for conservative investors looking for diversification, income and moderate returns.
  • Quantitative-driven processes can respond swiftly and systematically to market inefficiencies
  • Informational inefficiencies exist as investors do not exploit, in a timely manner, all information relevant to security prices
  • Behavioural biases exist as investors are prone to overreacting, herding, avoiding regret, and preferring lottery-like profiles
  • Traditional, time-tested fundamental investment principles – such as value and growth investing – can exploit these anomalies
  • A disciplined, systematic process can apply these principles efficiently

We use proprietary quantitative modeling to build portfolios that seek to deliver consistent, positive incremental returns over the long term.

Our investment process is rooted in company-by-company factor analysis. The process is disciplined and repeatable. To optimize our portfolios, we incorporate stock, sector and country forecasts.

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Research

There is a dedicated focus towards research. We are committed to continuous improvement, developing new quantitative tools and investment capabilities, and ultimately continuing to deliver exceptional quantitative solutions for our clients.

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