Clear Portfolio Analytics & Communications

Did that portfolio’s factor exposure make a difference this quarter?

Wednesday 5th April, 2017

This is the final article in a four-part blog series on a factor-centric approach to understanding performance, discussing market, peer group and, below, factor exposure for portfolio analysis.

Over the past few weeks we have been examining the opportunity to reveal deeper insights through analysis of independent, well-known factors. We are now armed with a clear understanding of how factors performed in the recent equities market. We have also determined which products within peer groups have benefitted most. So we’re well placed to dive deep into the details of a specific portfolio and factor exposure within that peer group. Ultimately, our objective is to obtain detailed insights as to the portfolio’s performance versus expectations given the recent market conditions.

Value factors performed well in the US during the final quarter of 2016. In particular, Cash Flow Yield was a strong measure driving the overall outperformance of Value in Q4-2016. Across the Morningstar Large Cap Value universe, we saw several common and differentiating characteristics of products. Notable was the diversity of the Cash Flow Yield factor.

Consistent Factors: Market, Peers and Now Products

To understand the impact of this factor more deeply, let’s select a specific product within that same Morningstar Large Cap Value universe. We will apply the same consistent factor lens at the fund level to examine its specific exposure to Cash Flow Yield.

Below we have plotted an actively managed portfolio and its Cash Flow Yield versus the Russell 1000 Value Index over 2016. As of December 2016, this portfolio ranked in the top quartile of Cash Flow Yield exposure within the entire Morningstar Large Cap Value universe. We can also see that this factor exposure was fairly consistent throughout 2016.

Portfolio Factor Exposure_Cash Flow Yield
Portfolio Factor Exposure_Performance Rank
Given our previous analysis of the positive, overall performance of the Cash Flow Yield factor in the US during 2016, we would have fairly high expectations for the performance of this fund. It holds an advantageous positioning on a strong performing factor. In the exhibit to the right, we do see a top performance ranking for this fund in its universe over the past 3-6-12 months ending December 2016. But the question begs, how much of that strong performance came from simply being overweight in an outperforming factor?

 

Reveal the Role of Factors in Performance Attribution

To answer this question, we can measure the performance of a single factor using a classic Brinson attribution process. We can view both the resulting allocation and stock selection impact by creating quartiles of stocks in the US market, as ranked by their Cash Flow Yield.

Using Cash Flow Yield quartiles, we provide our fund’s 2016 factor attribution below:

  • The portfolio’s active return versus the Russell 1000 Value index (in blue)
  • The impact from allocation to Cash Flow Yield quartiles (in red), and
  • Stock selection impact within Cash Flow Yield quartiles (in green).

Portfolio Factor Exposure_Performance Attribution

The positive active return (blue) of this fund most closely tracks to the stock selection impact (green). It is clear that this fund’s positioning or allocation towards stocks of higher Cash Flow Yield provided some positive impact (red), particularly towards the end of 2016. In other words, this fund’s strong performance in 2016 was equally attributable to both strong stock selection as well as beneficial factor positioning.

We also find interesting insights by examining the contribution from each of the individual Cash Flow Yield quartiles we have created to perform this analysis. Below we show exactly how each quartile of Cash Flow Yield affected the overall fund’s allocation and stock selection.

Portfolio Factor Exposure_Cash Flow Yield by Quartiles

We see above that while the overall allocation to higher Cash Flow Yield was in the manager’s favor, they showed particular strength in selecting those stocks in the top quartile. However, stock picking was not nearly as strong in the second quartile.

Let’s talk stocks!

In the world of active management, there is always a place for talking about individual stocks. So now that we know that this fund was not only well positioned towards stocks with highest cash flow yields, and we know that this positioning positively impacted their performance, we may wish to understand which specific equities best represented this portfolio’s winners. This security-specific insight could be considered the “final” step in leveraging a comprehensive, factor-based approach. Below we have listed a sampling of the names which contributed the greatest impact to this manager’s stock selection, when considering its bias to stocks with high Cash Flow Yield.

Portfolio Factor Exposure_Cash Flow Yield by QuartilesFocusing on a specific factor enables fund evaluators to connect their analysis seamlessly from a market perspective, to a relevant peer group and down to the stocks in a specific portfolio. Using consistent, factor-based analysis, fund managers, asset owners and investment consultants can clearly understand and articulate how a portfolio’s exposures impacted its performance.

In this case we saw that Cash Flow Yield did particularly well in the US during Q4-2016. We focused on the Morningstar Large Cap Value Universe and then screened for funds with exposures to this factor. Drilling into one of those funds, we confirmed that the Cash Flow Yield positioning was impactful. We even identified the specific stocks that most contributed to this factor exposure.

The Clear Winner: A Factor-based Approach

Throughout this series to build a portfolio’s story, Style Research has put forth the consideration that all investors would benefit from applying a factor-based lens to their own evaluation process. This approach has several benefits:

  • Consistently measures the impact of factors from markets, to peer groups to individual portfolios. This eliminates the friction inherent when using different systems and methodologies at each step.
  • Elevates understanding of individual portfolios above overly simplistic categorizations; allows a clear and direct view into the performance of a fund versus performance expectations, given the risks it took during the period.
  • Provides a set of well-known, industry-standard and approachable factors – instead of overly quantified risk models – appealing to a wider audience

Author: Tom Idzal | Categories: Insights, Portfolio Analysis

What questions do you have to understand factor exposures within portfolios? Send us your comments and questions to discuss in this blog series.

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