In a market crowded with active equity strategies, it can be difficult for investors to identify funds that consistently outperform the market through pure stock-picking. While most managers use either a quantitative model or fundamentals-based approach, we believe combining the benefits of both – within a liquid and transparent ETF structure – may support attractive outcomes over time.
At a glance:
- Our approach combines both quantitative and fundamental approaches.
- Quant signals and fundamental insights complement each other, leading to potentially superior outcomes when combined.
- ETFs are an effective and efficient way to harness alpha opportunities via their liquid, transparent structure.
Our approach to active ETF strategies utilises both quantitative and fundamental research
Active ETFs are rapidly gaining momentum in Europe, offering investors liquidity, transparency, and alpha-seeking opportunities. However, the choice of available strategies in active ETFs is deceivingly narrow, with many managers choosing to hug the benchmark, applying their research to only slightly over- or under-weight the main index constituents.
In seeking greater alpha potential through conviction, clients can look to the wider active mutual fund universe, where there is more variety in terms of approaches deployed. Some managers lean heavily on quantitative models, relying on data-based signals to identify opportunities across a large set of stocks. Other funds are built primarily on fundamental analysis with portfolio decisions driven by the bottom-up insights and discretion of individual managers or teams.
At Columbia Threadneedle Investments, we believe both approaches have strengths. Quantitative models can bring discipline, consistency and scalability. Fundamental research can incorporate context, nuance and an understanding of company-specific risks that financial metrics alone may not capture. As diversification is a well‑established principle of portfolio construction – seeking to combine uncorrelated sources of return and reduce risk – the same logic applies when selecting sources of alpha. Our QR Series Equity Active ETFs seek to combine the potential benefits of quant and fundamental approaches in search of superior outcomes for investors.
A combined strategy requires a clearly defined process that codifies how quantitative insights and fundamental judgment interact – and how conflicts between the two are resolved.
What ‘quant’ actually means in an active ETF
In the context of modern active ETFs, quantitative research is often misunderstood. While some merely associate it with factor-based investing or a static set of rules that simply tracks pre-defined characteristics, in fact there is much more to it. To illustrate its sophisticated, yet intuitive nature, a quantitative framework can be used to analyse and rate stocks in customised peer-groups using tailored criteria for each. Or put simply, it compares apples to apples, in a way that matters to each category.
We call this quant approach ‘industry-aware’ – a name that recognizes that each group of stocks is driven by a distinct set of economic and financial dynamics. And as the unique characteristics of stocks change day-to-day, the model can update its assessment of constituents relative to their peers daily, allowing for the entire universe to be objectively rated in response to shifting conditions.
How fundamental research strengthens the process
Quantitative models may excel at identifying patterns and relationships across large datasets. What they cannot always capture in real time is how a company’s prospects may change as business models evolve, competitive pressures intensify or strategic priorities shift.
This is where fundamental research complements and strengthens quant. Experienced sector specialists and analysts can bring company-level insight, helping to validate quantitative signals and highlight emerging downside risks that may not yet be fully reflected in data. In a combined framework, fundamental research does not replace the model or introduce discretionary stock-picking. Instead, it provides an additional layer of scrutiny, to forecast likely underperformance, which would be best avoided.
When fundamental insight comes to life: Omnicom
A practical way to see this interaction is through companies that remain positively rated by quantitative models over extended periods, yet fundamental analysis might raise some red flags. Omnicom, an advertising, marketing and corporate communications company, may provide a useful illustration.
From 2019 through 2023, Omnicom exhibited characteristics that our quant model tends to favour – significant market share, consistent cash generation and business attributes aligned with long-term quality and stability. As a result, its quantitative signals remained supportive over this time, reinforcing conviction in the stock.
However, as industry dynamics and company-specific circumstances evolved, fundamental research offered a different perspective. Specifically, our fundamental analysis focused on how changing market conditions and the corporate management’s strategy would affect the company’s future return potential. Based on this deep analysis, the team’s outlook was unfavorable due to increasing competition aided by AI. It resulted in a rating of ‘Strongly Underperform’ which would exclude the stock from the portfolio in our QR Series US Equity Active ETF strategy. Omnicom underperformed during the period where this fundamental research rating would have had a ‘veto’ effect on its holding in the portfolio. It is interesting to note that the quant model subsequently downgraded the stock but it was the fundamental research that identified the risks to the outlook first.
A further step we take at Columbia Threadneedle Investments is the collaboration between the quantitative and fundamental research teams, where they are constantly learning from each other and working to continuously improve their approaches.
By allowing quantitative signals to be tested against evolving fundamental insight, the process ensures that portfolios reflect current realities rather than past data solely. This dynamic supports the pursuit of attractive alpha opportunities with effective downside risk mitigation.
This example is provided for illustrative purposes only and does not indicate future performance or outcomes.
From research to decisions: A structured, transparent process
Bringing these elements together requires a clear and repeatable process. One way to think about this is as a continuous loop: Research, Rank and Recalibrate (Figure 1).
Figure 1:
CT QR Series Equity Active ETFs – investment process overview
1. Research | 2. Rank | 3. Recalibrate |
|---|---|---|
Analyse and rate the universe | Include only the strongest performing stocks | Monitor and rebalance |
With a proven, customised quantitative model and complementary fundamental insights, we analyse and rate the investible universe to identify stocks with strong potential to outperform. | Leveraging these combined ratings, we rank the stocks from ‘strong buy’ to ‘strong sell’. We exclude those expected to underperform to reduce the universe by up to two thirds, including only the stocks where we hold strong conviction and those aligned to Article 8. | We rebalance the portfolio every six months with sector, regions and countries benchmark aligned. Holdings are reviewed daily to minimise any emerging downside risk. |
Source: Columbia Threadneedle Investments, 31 January 2026. For illustrative purposes only.
Why this matters inside an ETF structure
This approach helps avoid both ‘black box’ opacity and ad hoc decision-making. This transparent and rules-based approach aids liquidity of an ETF – an important consideration for European investors using ETFs as core building blocks.
Not all active ETFs are the same and understanding how the underlying strategy is executed is essential to selecting the right fund to fulfill the investor’s objectives. We believe that the combination of quant models and fundamental research is an effective approach for investors seeking superior outcomes.
