
Arup Datta
MBA, CFA
Senior Vice President, Head of Global Quantitative Equity Team
Mackenzie Investments
As institutional investors seek to diversify exposures, enhance alpha generation, and navigate market volatility, Institutional Connect is pleased to feature Arup Datta, Senior Vice President and Head of Global Quantitative Equity, Mackenzie Investments, in this speaker spotlight. Arup’s insights offer a valuable lens on the practical applications of quantitative investing and the future of systematic approaches in asset allocation.
With over three decades of experience spanning global markets and data-driven portfolio construction, Arup brings a distinctive perspective on how quantitative strategies can deliver consistent, risk-adjusted returns in an increasingly complex investment environment. At Mackenzie Investments, he leads the development and implementation of systematic strategies that merge robust research, advanced analytics, and cutting-edge technology — aligning innovation with the long-term objectives of institutional portfolios.
Arup Datta: Quantitative investing is a systematic approach to portfolio management that relies on financial theory, statistical models, data analysis and algorithms to drive investment decisions. Unlike traditional fundamental investing, it focuses on leveraging computing power and technology to analyze a broader investment universe and supports decision-making through proprietary risk and transaction cost models.
Mackenzie GQE’s approach to quantitative investing – a holistic quant approach – enhances alpha profile by integrating multiple styles, signals, and market insights into a unified, disciplined framework.
Key value-adds that we believe our quantitative investing can offer to institutional investors:
Breadth and consistency: Quantitative models can systematically analyze tens of thousands of stocks daily, uncovering broader opportunities often overlooked by traditional methods. This scalable process supports broader, more diversified alpha generation.
Transparency and repeatability: Investment decisions follow a rule-based, repeatable process that can be back-tested and monitored across market cycles, increasing confidence in the robustness of the investment objective and outcomes.
Diversified and core-oriented: Mackenzie GQE’s core approach balances value, growth and quality investment styles to provide stable, muti-style exposure, which helps reduce style drifts and increases resilience across market regimes.
Innovation and forward-looking signals: Mackenzie GQE incorporates advanced techniques such as machine learning, natural language processing in the investment process to identify emerging alpha sources and capture signals often inaccessible to traditional processes.
Risk and Capacity Management: Quant managers often build their own risk model which is honed into their process. We embed risk controls at every step using proprietary risk models and daily rebalancing. Strict AUM capacity management preserves alpha integrity, which is crucial for institutional investors concerned with scalability and execution drag.
Arup Datta: In today’s volatile and uncertain market environment, quantitative investing offers a discipline, risk-aware framework that helps investors navigate complexity with greater confidence. Unlike emotion-driven or subjective decision-making, quant strategies apply consistent rules in portfolio management, providing structure when markets are dislocated.
Some key advantages to highlight:
Discipline under pressure: quant models remove emotional biases, allowing investors to remain invested and consistent through turbulent times – reducing the risk of behavioral biases such as panic selling or style chasing.
Diversified across styles and signals: By balancing value, growth and quality, a core quant portfolio is more resilient in adapting to shifting market leadership and avoids over-reliance on any single market style.
Risk control and implementation efficiency: quant models run by rules, having the flexibility in adjusting risk factor exposures allows quant manager to be more effective in risk management during volatile market.
Alpha opportunity capture: during volatile market, dispersion across stocks tend to rise. Quant models are well-positioned to exploit this by opportunistically identifying huge dislocation and disparity in the market.
Arup Datta: Our approach to factor selection is grounded in both academic rigor and practical relevance, combining long-term empirical validation with forwarding-looking insights. Maintaining a consistent core, all weather investment philosophy, we build our stock selection model based on our four “Super Factors” – Value, Growth, Quality and Informed Investor.
- Factor selection: we source the evaluate new factors based on the following criteria:
- Economic intuition: each factor must have a sound theoretical basis or reflect an observable market behavior
- Empirical strength: factors are tested for Statistical significance and predictive power across geographies and market regimes using long-term backtest and simulations
- Diversification: select factors with low correlation to our existing signals to ensure true breadth and diversity of alpha sources
- Practical implementability: we assess the real-world viability of each signal, including turnover, alpha decay, transaction costs and capacity impact.
- Contextualization & model predictiveness: We find that firm characteristics do impact investment signal efficacy, therefore, we built the contextualization model to ensure that we are ranking stocks on metrics that are most relevant to the stock.
- Integrated process: we have an integrated process which combines alpha model with portfolio construction and implementation. Our alpha scores generated from the alpha model, are used as inputs into a portfolio optimizer, which takes into transaction cost forecasting, and portfolio constraints. This ensures optimal tradeoff between alpha, risk and liquidity at portfolio level.
- Human oversight: While our process is highly systematic, we value the importance of human overlay, including discretionary intervention during extreme market events (e.g., add value tilt during covid 19, etc.)
Arup Datta: Given our systematic investment approach, risk and liquidity management have consistently played a key role in our investment process. One advice we can offer is to diversify the source of both risk and return. This means avoiding over-concentration in any single asset, strategy, or investment style. Instead, we should try to spread exposures across a broad range of securities, investment styles and underlying risk drivers. This helps enhance the portfolio’s resilience in the face of market volatility – especially in environments when sentiment can shift rapidly due to external influences such as geopolitical events or even social media activity.