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However, with the "Magnificent 7" stocks accounting for over 50% of S&P 500 gains in 2024 and valuations appearing stretched, many investors are seeking broader market exposure and sources of alpha beyond just these handful of companies.
Aims to remove emotional biases by relying on empirical data.
May integrate human oversight or be fully systematic.
What is Quant Investing?
The magnificent 7 accounted for over 50% of S&P 500 gains in 2024. Today, valuations arguably look stretched.
MDT, part of Federated Hermes, believes an active, systematic approach can generate excess returns across an entire market cycle.
The firm uses proprietary machine learning techniques to model various return drivers across different types of companies, tailoring forecasting methods accordingly and subjecting them all to continuous review.
Quant investors can sift through vast amounts of data collected from a variety of sources, including:
Market history
Company fundamentals
Valuation metrics
Macroeconomic data
MDT, part of Federated Hermes, can offer a differentiated proposition to investors:
At Federated Hermes, quant investing goes beyond automation.
Human Decision-Making & Oversight
Every trade is reviewed before execution.
This involves:
This approach provides a broad range of potential alpha sources, leading to more consistent performance.
Quantitative investing (quant) encompasses a broad range of strategies that use data analysis, mathematical modelling and automated transactions seeking to deliver investment returns.
MDT Advisers’ Differentiated Approach
Potential for consistency of alpha delivery with no over reliance on any single factor over the long term
May produce diversification of alpha delivery relative to traditional approaches
Full active management based on bottom-up stock selection
Sophisticated modelling techniques
Since 2001, MDT has used human expertise alongside a differentiated machine learning investment model, an approach that employs decision trees to forecast stock returns.
Decision trees offer an intuitive, transparent framework to forecast stock returns.
Decision tree models use
a series of yes/no questions following a hierarchical, tree-like structure.
Within MDT’s model, the data used to ask these questions can include fundamental data (such as data from a company’s balance sheet, or income statement) with technical data such as price trends.
A decision tree begins with a simple question about company characteristics that is asked to the entire investable universe,
By asking a series of questions in sequence, decision trees allow MDT to focus on the most important characteristics for a particular stock, and downplay those characteristics that are less important.
MDT’s approach combines expert oversight with proprietary decision-tree models, ensuring strategies remain robust, adaptive, and transparent.
Intensive Risk Management
Uses risk modeling tools and a variety of benchmark-relative investment constraints, including sector, industry and company limits.
Transparency
Clear reasoning behind portfolio holdings and investment decisions.
Continuous Improvement & Supervision
Models evolve with new data for long-term adaptability.
Example: Decision Tree in Action
Has the company been a net issuer of equity or debt?
(Factor: Quality)
Q2
Have analysts been raising estimates for EPS, revenue and cash flows?
(Factor: Analyst conviction)
NO
Further splits based on valuation and momentum metrics.
Q1
Correlation of active returns, MDT All Cap Core Strategy* vs. factor indices MSCI USA Factor Indices
Jan-2015 to Dec-2024
0.32
0.01
-0.05
0.06
-0.14
0.14
Equal
Weighted
High Dividend Yeild
Minimum Volatility (USD)
Value
Weighted
Momentum
Quality
MDT All Cap Core
Annualized performance returns (%) as of 12/31/24
† Since inception 6/15/91. *The net performance provided on this page reflects a 0.70% annual fee (the current fee schedule) deducted monthly across all historical time periods. Please refer to the disclosure pages at the end of this document as they are an integral part of this presentation. Investing in equities is speculative and involves substantial risk. Past performance is no guarantee of future results. Refer to the attached GIPS® report for additional information.
and questions branch into further questions,
eventually leading to a return forecast of every company in the investable universe relative to a benchmark.
Group 5
Q3
Is the company's peer-relative valuation improving?
(Factor: Value)
Q4
Are recent prices improving?
(Factor: Momentum)
NO
NO
NO
Group 1
Group 2
Group 4
Group 3
YES
YES
YES
YES
Magnificent 7
Rest of S&P 500
Likely overperform
Likely neutral
Likely underperform
MDT US Equity
Quant Investing’s Secret to Finding Alpha
The U.S. is the world’s largest and most dynamic stock market.
Where Human Expertise Meets Advanced Quant Models
Aims to remove emotional biases by relying on empirical data.
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