Fast reading
- The MDT Advisers team uses machine learning to parse through vast amounts of data and seek a multitude of equity opportunities in an unbiased way.
- The investment team designs, oversees, and continuously looks for ways to improve upon the various tools in its investment process.
- The entire approach is transparent and the reasoning behind investment decisions is clear.
Once associated primarily with institutional investors, quantitative investing has become more accessible to retail investors in the last 20 years through ETFs and mutual funds. It’s an approach that relies on mathematical models, statistical techniques and computer algorithms to digest large datasets, identify patterns, and help managers make investment decisions.
And while this type of investing typically involves advanced modeling techniques – including tools within the expanding fields of machine learning and artificial intelligence – that doesn’t mean humans aren’t involved.
Federated Hermes MDT Advisers (MDT), for instance, uses machine learning to parse through vast amounts of data and seek a multitude of equity opportunities in an unbiased way. The investment team designs, oversees, and continuously looks for ways to improve upon the various tools in its investment process. The entire approach is transparent and the reasoning behind investment decisions is clear.
A potential advantage of quant investing is the ability to achieve greater diversification by investing across a range of styles.
“Our quant process is not a ‘black box,’ and trades are reviewed by members of the investment team prior to implementation,” says Scott Conlon, investment director for Federated Hermes MDT Advisers, the active quantitative equity arm of Federated Hermes.
Conlon says the firm believes its quant approach is clearly defined, testable and, in many ways, more transparent than that of traditional fundamental investors.
“When analyzing a traditional stock-picking portfolio manager, it’s sometimes difficult to determine that their methodology can be repeated with success over time. For instance, you could have a portfolio manager who benefited from a one-off, short-lived hunch that proved successful,” Conlon says. While past success is never a guarantee of future results, quantitative investing seeks to provide a repeatable process.
Diversification, back-testing and flexibility
One potential advantage of quant investing models is that they are testable using historical market data, allowing investors to understand how a particular strategy may have worked over a long period of time, and what the outcomes may have been to an investor in terms of return and risk, Conlon says.
Another potential advantage of quant investing is the ability to achieve greater diversification by investing across a range of styles. Traditional fundamental strategies often incorporate a specific focus that aligns with the manager’s philosophy, such as quality, value, small cap or dividends, to narrow the field of potential investments. If the environment for one of those styles is out of favor, returns may suffer.
By contrast, Conlon says quant strategies can be built more flexibly. MDT aims to build portfolios that invest in many different types of companies with varying return drivers, so that the portfolio has the potential to not just outperform over time, but to deliver more consistent performance in many market environments.
Additional avenues to risk management
The quant investing process also offers portfolio managers additional avenues to manage investment risk, when compared to traditional fundamental approaches. For example, MDT’s quantitative managers don’t necessarily have a view on which sectors or factors – i.e., value, growth, small cap, energy – will outperform at any given time. Therefore, they use sophisticated risk modeling to try to avoid the risks of being overconcentrated in a particular sector or factor. Instead, the portfolios’ active risks are allocated to stock picking.
“Stock forecasts and portfolio positions are updated daily, enabling our strategies to adapt to take advantage of timely market opportunities. This active approach is designed to help ensure our clients’ portfolios always reflect our most current, best, bottom-up ideas,” says Conlon.
It's quant. But not as you know it.
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