Navigating Barriers in Systematic Factor Investing: Strategies for Success

When institutional investors decide to venture into Quantitative Investment Strategies (QIS) systematic factors, they often encounter various obstacles that require careful consideration and strategic solutions. The specific challenges can vary based on the investors’ unique characteristics and investment objectives, but some of the primary hurdles are consistent across the board. In this blog, we will explore these challenges and highlight how Premialab’s powerful data can help overcome them, enabling institutional investors to excel in the world of factor investing.

Challenges and Solutions

Data Availability and Quality

A crucial foundation for the success of QIS systematic factor investing is reliable and high-quality data. Institutional investors often struggle to find the precise, granular data needed to incorporate their chosen factors into their investment strategies. Ensuring data accuracy and consistency across multiple sources can be a daunting task.


: Premialab addresses this challenge by sourcing data from a variety of reputable providers, meticulously cleansing and standardizing it, and making it easily accessible to investors. This streamlined process eliminates the headache of data procurement and management, delivering dependable and granular information to institutional investors.

Model Complexity

QIS systematic factor investing is inherently complex, involving intricate quantitative models and algorithms. Institutional investors may face difficulties in implementing and managing these models effectively, as it demands specialized skills and resources. Developing, testing, and maintaining robust factor models can be a considerable undertaking.


: Premialab’s technology provides powerful data and visualization tools that simplify the implementation and management of complex QIS systematic factor models. With a user-friendly platform, investors can easily customize and implement factor models according to their specific requirements. Ongoing support and guidance ensure efficient model development, testing, and maintenance.

Investment Governance

Institutional investors frequently operate under stringent investment governance policies and procedures. Integrating QIS systematic factors into existing governance frameworks may necessitate adjustments and approvals from multiple stakeholders. Ensuring alignment with regulatory requirements and internal governance guidelines can be a time-consuming process.


: Premialab’s technology seamlessly integrates with institutional investors’ existing governance frameworks. The platform facilitates compliance with regulatory requirements and offers robust reporting and monitoring capabilities. This ensures that QIS systematic factor investing aligns seamlessly with the investment governance policies and procedures of institutional investors.

Risk Management

Factor investing introduces unique risk management considerations. Institutional investors must closely monitor and manage factor exposures and potential risks, including factor crowding, model risk, and factor decay. Implementing effective risk management practices specific to factor investing may require additional expertise and resources.


: Premialab’s technology incorporates advanced risk management tools and methodologies tailored to factor investing. The platform empowers investors to monitor and manage factor exposures and risks effectively, offering real-time risk analytics and alerts. This proactive approach enables institutional investors to mitigate risks such as factor crowding, model risk, and factor decay.

Performance Evaluation

Assessing the performance of factor-based strategies can be challenging due to the need for appropriate benchmarks and performance attribution methodologies. Institutional investors may struggle to accurately evaluate the skill of their factor selection and the impact of factor timing on portfolio performance.


: Premialab’s technology offers sophisticated performance evaluation tools customized for factor-based strategies. The platform provides advanced performance attribution methodologies, enabling investors to compare factor returns against relevant benchmarks. This robust toolkit empowers institutional investors to make informed decisions and accurately assess the performance of their factor-based portfolios.

Cultural Resistance Lastly, institutional investors may encounter cultural

resistance when adopting factor-based investment approaches. Tradition, familiarity with traditional investment strategies, and a reluctance to deviate from established norms or benchmarks can hinder the adoption of QIS systematic factors.


: Premialab’s technology helps overcome this by demonstrating the value and potential benefits of factor investing. Through data-driven insights, powerful visualizations and success stories, the platform assists institutional investors in understanding the advantages of adopting QIS systematic factors and building confidence in their investment decisions.


While institutional investors may face several formidable hurdles when entering the world of QIS systematic factor investing, the growing popularity of this approach and its potential benefits are compelling motivators. With the right resources and support, these challenges can be effectively managed, and the potential rewards can far outweigh the obstacles.

Premialab’s technology offers a comprehensive solution to the main challenges encountered by institutional investors in QIS systematic factors. By providing granular, reliable data, simplified model implementation, robust risk management tools, and advanced factor analytics capabilities, Premialab empowers institutional investors to confidently navigate the world of factor investing.

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