Consistent Factors: Bridging Market and Peer Group AnalysisThursday 30th March, 2017
In this installation of our series on the importance of consistent factor analysis, we dive into the Peer Group and Competitive perspective. In our previous entry, we introduced the notion of using well-known, approachable factors in assessing the recent market environment.
Building on that idea, a natural next step for investors is evaluating the performance of specific classes or peer groups of products. Investors expect that products labeled as “defensive” will likely have outperformed more aggressive competitors in a down market. Similarly, when market analysis shows favor towards “value” themes, investors expect specific products and even specific firms to do well. However, not all products within those broad groups will outperform to similar levels, and some products may even lose ground. In such instances, it’s natural for questions to arise. For example: what is different about certain value approaches that held performance back in a value rally? Or why did my manager not perform as well as their peers?
In these circumstances, investors often turn to common “style box” or “peer group” analysis. However, that can leave them wanting deeper insights. The “blurring of details” that stems from such highly generalized categorizations is directly related to the specific factor combinations used to define the groupings. These factor combinations, besides being opaque to the end user, can also prove favorable to certain managers who believe in similar, factor-related philosophies. Additionally, they have the potential to unfairly favor any lower-fee factor constructed products that share in a specific formula. As a result, broad “style box” or “style map” approaches struggle to offer a transparent, equitable and actionable approach to peer analysis.
Connecting market performance to peer group assessments
During late 2016, value-related factors, specifically Cash Flow Yield and Earnings Yield, performed strongly in US markets. Using Peer Insights, we can create specific, factor-based analysis of funds classified by Morningstar as Large Cap Value, allowing for clear contrast and comparison.
Using holdings as of the end of November 2016 as a proxy for a fund’s positioning in Q4 2016, we see that the median manager in this peer group had a Cash Flow Yield and Earnings Yield that was in line with the Russell 1000 Value index. So, despite these factors’ outperformance, the typical manager will not have had a significant exposure difference from a commonly used benchmark.
Now let’s identify the funds that did have a significantly higher Cash Flow Yield exposure in Q4, since this factor was an area of market outperformance:
Armed with the specific products that had exposures to the outperforming factor, investors can “pin” these products to understand how they compare along additional factor exposures as sector and risk perspectives:
Above we plotted two specific products similarly exposed to higher Cash Flow Yield. However, in the circled area we can see they are significantly different on the Market Cap and Market Beta exposures. One is exposed to smaller sized names but higher volatility. The other is similar to both the benchmark and the peer group. This means that despite their similarities in a value context, there are meaningful ways these two product differentiate. As a fund selector, we would likely expect these two products to have performed differently. With the help of the transparent factors, fund selectors can now dig deeper into these characteristics of the funds. They would next research possible explanations for that differential performance.
Applying consistent factors to pinpoint differentiation between peers
As demonstrated above, committing to a standard range of well-known and approachable factors allows investors to go beyond broadly identifying what’s taken place in the market. It allows them to isolate how specific peer sets have benefited. This leads to a clearer understanding of the disparate performance between products in the same peer group.
How are you translating the recent market dynamics to winners and laggards in the peer groups most important to you? In your current process, can you make direct links, factor-by-factor, into what likely drove differential performance?
The final step in this process will be to take these same measures and drill into each portfolio intrinsically. Our aim will be to understand which stocks or factors contributed most to their performance. We will explore this perspective in the next blog post.