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Systematic investing

By combining the power of big data, data science, and deep human expertise to modernize the way we invest, systematic investing is unlocking new ways to seek consistent portfolio outcomes amidst a world of unpredictability.

Systematic Investing

In today’s uncertain markets, we all need more predictable investment outcomes.

By combining the power of data-driven insights, investment science, and disciplined portfolio construction to modernize the way we invest, systematic investing is unlocking new ways to seek consistent outcomes amidst a world of unpredictability.

Systematic investing begins with data-driven insights

In the digital age, we have access to vast amounts of data, from traditional sources like company financial statements and economic reports to more complex unstructured sources like company news stories, web traffic, social media sentiment, consumer geo-location data and even satellite imagery.

By harnessing highly sophisticated analytics techniques like machine learning and artificial intelligence, we transform this sea of raw data into useful investment information—providing insights faster, at greater scale, and with more granularity than traditional methods.

Next, we deploy rigorous scientific testing to learn if these investment insights actually have the potential to help forecast future returns.

This process includes a comprehensive examination of empirical evidence by seasoned investment experts—testing different combinations of variables and comparing the results to known outcomes. This ability to validate insights means portfolio decisions are firmly evidence-based and not dependent on human conviction alone.

Finally, when an insight is shown to be valuable, we employ a disciplined portfolio construction process to implement it. Our investment experts use computers to model the many complex trade-offs involved—finding a balance between expected return, risk, correlation and cost—to guide any allocation decisions.

At every step, the systematic process is designed to help deliver more targeted investment outcomes

Whether it’s seeking risk-managed growth through equities… generating income and maintaining ballast with bonds… integrating sustainability and ESG insights into portfolios… or accessing new sources of diversification and return with alternative strategies…

Systematic investing is unlocking new ways to navigate a world of uncertainty. 

What is systematic investing?

Systematic investing, often called quantitative investing, is an investment approach that emphasizes data-driven insights, scientific testing of investment ideas, and advanced computer modelling techniques to construct portfolios.

Different by design

The quantitively-driven process of systematic investing expands what is possible when investing—from searching for investment insights, constructing portfolios, seeking to ultimately delivering more targeted outcomes to investors.
Tech breakthrough
Human X Machine
Fundamentally sound investment ideas are validated by quantitative testing—amplifying human decision making but keeping behavioral bias in check.
Engineered for Scale
Technology-driven process helps scale investment insights across vast sets of securities—creating highly diverse portfolios while minimizing hidden concentration risks.
Risk management
Robust risk management
Employing our own innovations and technology in seeking to manage risk and generate consistent results over the long term.

Transforming how we see the world

Just think about how much data is out there and how it escalates rapidly. In 2022, saw 3.16 billion visits on average per month, while Alibaba generated over US$94 billion in e-commerce sales. And every minute of every day, we have about 97 million WhatsApp messages, and 500 hours of new videos on YouTube.  And it goes on.

The funny thing is, we don’t just want data or information. Instead, we want to know what it all means, why it matters to us, and to be able to use the insights we have to predict outcomes

At BlackRock, our systematic investing platform has been doing this for over 35 years with a track record of innovation, creativity and reinvention. Our diverse team of 200+ financial professionals, academics and data scientists, blends the best of humans and machines to unlock new ways to generate differentiated outcomes

They harness cutting-edge technology such as AI and machine learning to review 800-plus data signals, assessing the fundamentals, sentiment, macro, and ESG characteristics of thousands of securities, at scale, and on a daily basis. They can then analyze and combine traditional inputs along with unconventional data sources in faster and more effective ways than any human could ever do.

So, how does this work in the real world?

Since 2007,  we have been using natural language processing techniques to capture local text in the form of regulatory filings, news articles, broker reports, social media updates, and other sources to gather timely, nuanced views about a company’s outlook at scale

For example, our model can identify early investment signals by using sentiment analysis, tracking the number of positive and negative words included in a document, and assigning an overall sentiment score based on word counts.

Our approach also constantly evolves. We now apply transformer-based large language models like ChatGPT. These can process long sequences of elements – such as words in a sentence – accounting for the relationship between each individual word with other words, and focusing on the most important points.

And language is not a barrier as we can read text with 7 major languages, which allows us to get local context.

Another source of AI-led alpha might come from the physical world. Here, we can use AI as a tool to compile and analyze location-specific data – such as GPS signals from cell phones, and more to track consumer traffic. Or we can track trucking routes across a country, based on a view that heightened traffic may be a proxy for increased company fundamentals like future sales.

AI and data availability also allow us to better understand corporate intentions and macro dynamics. For example, in the US we tracked millions of online job postings to gauge the health of a company or to target future growth areas based on the skill-sets in demand. The rate of hiring can also be a proxy for activity at the company, industry, or country level.

Yet despite this outlook, machines will not take over. Human input and analysis is a critical component, and fundamental and classic information still have a major role to play. We call this a human-machine-team approach to investing.

Investing evolved

Transforming how we see the world

Watch the video to understand how we integrate big data and machine learning/artificial intelligence with human insights to select stocks and deliver income.

BlackRock Systematic Global Equity High Income Fund

Income icon
Targeting to deliver a high income
Sources income from equity dividends and an index options covered call strategy.
Human and machine icon
Integrating human insights, big data and machine learning
Stocks are selected using a research-driven, technology-led approach designed to better predict future stock returns and dividends.
Voltality icon
Low volatility through flexible management of beta
Seeks to deliver a higher yield at a lower volatility relative to global equities with the potential to achieve capital upside.

Our recent accolades1

It is our honour to be awarded Best Fund Provider - Equity Income for the BlackRock Systematic Global Equity High Income Fund.

Equity income

Fund performance

Why BlackRock?


Empowered by data and technology

We use vast datasets and technological innovation to find investment insights amidst market complexity.


Guided by science

We vigorously test and validate ideas through a deliberate scientific method to continuously refine and redefine our approach.


Enlightened by experience

We draw on 35 years of experience, augmented by intellectual curiosity and diverse thought, to inform our investment process every step of the way.