Quantitative Investments
Deeper analysis, building value with multi-factor models
Multi-factor, data-driven analysis for long-term growth
Historically, companies with strong fundamentals backed by increased investor interest often outperform. To identify these companies, the team combines fundamental and quantitative analysis and multi-factor models. This data-driven approach helps avoid risks by anchoring investment decisions in hard data and the Team’s own independent analysis.
This comprehensive approach to return/risk analysis and portfolio construction increases the potential for consistent, long-term outperformance. The Quantitative Investments Team implements fundamental insights systematically using a multi-factor model that selects stocks with solid fundamentals, attractive valuations, and growing investor interest.
As part of its investment process, the team constructs truly efficient portfolios using multi-factor alpha/risk models and benchmark agnostic optimization to significantly reduce total risk without sacrificing total return.
The team constantly researches and evaluates new ideas and model concepts based on economic and business fundamentals for inclusion in their models.
Benefits
Investment philosophy
We believe that a quantitative approach to return/risk analysis and portfolio construction can lead to consistent long-term outperformance
Implementing fundamental insights systematically can bring consistency repeatability to performance
Investment process
Company evaluation:
Profitability, earnings quality, management quality, valuation, momentum, sentiment and ESG are all assessed
Sector models:
Customized models for key Canadian sectors such as Energy, Precious Metals & REITs
Risk assessment:
Risk analysis through factor, macroeconomic and fundamental perspectives
Portfolio optimization:
Enhanced by controlling position limits, systematic risk factors, tracking error, turnover, liquidity and trading costs.
Portfolio review:
Disciplined investment decisions based on model recommendations and independent analysis
Meet the Quantitative Investments team
Jae Park
Jae brings over two decades of software development experience to BMO Asset Management Inc. Previously, Jae was a senior developer at Mercer where he developed and maintained pension lines of software applications. He also worked as an actuarial systems developer at Towers Watson and as a software developer at Morneau Shepell, and was responsible for developing a variety of pension valuation applications and human resource administration applications. Jae holds an undergraduate degree in actuarial science from the University of Western Ontario.
Gabriel Bortes
Gabriel joined BMO Asset Management Inc. in 2009 as a senior business architect with over two decades of experience in the financial services industry. Previously, he was a senior design and development engineer at Barclays Global Investors for over nine years where he developed systems for various business groups. Before joining Barclays, Gabriel worked as a developer for other tier-one financial institutions. He studied Software Engineering at Watford College, Watford, England, and Cognitive Science & Intelligent Computing at the University of Westminster, London, England.
Ozgur Akturk, CFA, M.Fin, PMP
Ozgur joined BMO Asset Management Inc. in 2009 as head of business architecture for the Quantamental Solutions Group. He has over two decades of experience in the investment industry. Prior to joining the firm, Ozgur was a Senior Design and Development Engineer at Barclays Global Investors for close to nine years in the Toronto office where he designed and developed systems and automation processes that cover a broad range of investment areas. He holds a Bachelor of Science in Industrial Engineering, a Masters of Finance and has also received the CFA and Project Management Professional designations.
Albert Yao, CFA, M.S.
Albert joined BMO Global Asset Management on July 2022, and is responsible for research and operations. He has over 3 years of experience in investment analysis. Prior to joining BMO, Albert was an investment engineering at CPP Investments where he provided investment analytics capabilities for equity balancing program as well as private equity performance attribution. He also contributed to Fundamental Forecasting pipeline project during his time at CPP Investments. Albert has a Bachelor of Applied Science in Engineering Science major in Mathematics, Statistics, and Finance from University of Toronto, followed by a Masters of Management in Analytics from McGill University. In addition, he is a CFA charterholder and a member of the CFA Society of Toronto.
Yadwinder Garg, CFA, M.S.
Yadwinder joined BMO Global Asset Management in January 2018 and focuses on investment strategy research and operations. He has over 10 years of experience in investment analysis. Prior to joining BMO, Yadwinder was a researcher at Research Affiliates LLC in Newport Beach where he was involved in back testing, research, design and portfolio analytics of smart beta and systematic active equity strategies. Yadwinder holds a Bachelor of Science in Electrical Engineering from the Indian Institute of Technology Kanpur and a Masters of Computational Finance and Risk Management from the University of Washington. In addition, Yadwinder is a CFA charterholder and a member of the CFA Society of Toronto.
Sachal Mahajan, CFA, M.S.
Sachal joined BMO Global Asset Management in December 2021 and focuses on the management of our active strategies in Canada, US and Global markets. He has over 14 years of investment experience. Sachal has worked as an equity portfolio manager for State Street Global Advisors and OMERS with experience managing long only, long-short and low volatility portfolios. Prior to joining BMO, Sachal was a portfolio manager at CPP Investment Board managing and designing systematic strategies for pension portfolios. Sachal holds a Masters in Science in Physics from the Indian Institute of Technology Kanpur and a Masters in Quantitative Finance from the University of Waterloo. In addition, he is a CFA charterholder and a member of the CFA Society of Toronto.
Lu Lin, M.Fin, M.S.
Lu Lin has been Head of Quantitative Investments at BMO Global Asset Management (GAM) since October 2023 and in the finance industry since 2009. She has expertise in quantitative and strategic modelling spanning all asset classes. Lu joined BMO in January 2021 as Head of Market Risk Models where she led and was accountable for bank wide market risk modelling and counterparty credit risk modelling. Lu subsequently moved to BMO GAM in February 2023 as Head of Strategy and Optimization for Synthetic Asset Management. During that short time frame Lu was instrumental in taking the lead on implementing the BMO Strategic Equity Yield Fund Valuation tools (Numerix), model calibration of the tools, organization and risk oversight of the Seed capital book and working on strategic risk and balance sheet initiatives for the Wealth Enterprise. Prior to joining BMO, Lu held senior roles in Global Risk Management as Head of Market Risk Modelling, Head of Counterparty Credit Risk and XVA Modelling. Lu earned a Master of Quantitative Finance at ETH Zurich as well as a Master of Finance at the University of Lugano.
Ariel Liang, CFA, M.S., LL.M.
Ariel is responsible for equity portfolio management and research. She joined the company in 2018. Ariel began her career in the investment industry in 2005. Prior to joining BMO, she was a quantitative researcher at RBC Global Asset Management, where she designed quantitative investment strategies. Prior to that, she was an associate portfolio manager for the Canada Pension Plan Investment Board and an investment analyst for the Ontario Teachers’ Pension Plan.
She holds a Master of Mathematical Finance and a Global Professional Master of Laws from University of Toronto. Ariel also has a M.A. in economics from Simon Fraser University and a B.B.A. in finance from Nankai University. In addition, she is a CFA charterholder and a Certified Financial Risk Manager.
Contact us
To learn more please contact us at [email protected].