Peer & Competitive Analysis
Comparing Fundamental Active, Smart Alpha, and Smart Beta Funds with Objective Factors
Learn how factor-based analysis of funds can identify underlying – and often unexpected – differences in similarly labeled funds. In a previous Style Research article, Bernie Nelson discussed key criteria for an effective factor-based analytical framework. In this new case study, Bernie puts this approach into practice, analyzing three funds labeled “US Large Value.” A deeper, more detailed comparison using transparent factors reveals distinctions in stock diversification, sector exposures, and specific styles – and shows how these funds are more different than their descriptions would indicate.
The DOL Fiduciary Rule adds pressure on asset managers and financial advisors already encumbered by increasing competition and ongoing regulatory change. That’s why factor-based analysis is so valuable. Analyzing funds based on individual factor exposures provides the level of insight, detail, and transparency that enables managers to respond not only to the new rule but to demonstrate greater product differentiation and deliver better customer service.
Fund sellers need to ensure their funds are positioned effectively against competitors. Fund buyers need to understand fully what exposures and risk might be within products they are buying or holding.
How does your style factor framework stack up? Check against these six criteria for selecting factors to create equity product differentiation.
Author: Style Research | Categories: Peer & Competitive Analysis
A year on from last June’s shock Brexit referendum result, negotiations have begun on the terms of Britain’s exit from the European Union. Shortly after the 2016 vote, we discussed the likely economic impact of Brexit, the investment factors anticipated to emerge most strongly, and how managers were positioned to respond. In this update, we review the past twelve months’ activity in three ways:
- How has the UK market behaved – which sectors and factors performed best over the period?
- How are domestic UK equity funds oriented, and how have they changed since last year?
- Which funds performed best, and what drove their returns?
How do you compare a fundamental active manager, a quantitative active manager, and a smart beta product?
Professional fund buyers and fund sellers don’t just look at historic performance or fees to differentiate equity products. Fund buyers demand more visibility into what they are buying or holding. What is the future potential for return and risk? Will buying or holding this product match their investment preferences and fit into their existing portfolio? Will the fund provider continue to manufacture a consistent product? Fund sellers also know that clear portfolio insights are essential to deliver their key messages and help them stand out from the crowd. They need proof statements to help them win business and retain clients. As in any market, other than competing on price, sellers must differentiate – or they will die. Read More
Discover ways to distinguish funds on our recent webinar recording
Style Research held a webinar on factor analytics, presented by our COO, Dr. Peter Hopkins, an expert in portfolio analysis and investment research. Peter focused on how a factor-based approach can pinpoint differentiation between funds, even those that might seem similar. He also discussed how analyzing factors consistently – connecting market, peer group and individual portfolio performance – leads to a clearer investment picture backed by objective and unambiguous metrics. The webinar is geared toward investment professionals grappling with the proliferation of factors and lack of adequate analytics. You can access the recording here.
As factor-based investment products and strategies become increasingly prolific and sophisticated, it’s paramount for associated analytics to evolve at the same pace. Dr. Peter Hopkins, COO of Style Research, recently addressed this topic at the AIMSE Europe Consultants Conference, held on April 25th, 2017. Peter discussed new methods to incorporate a consistent, factor-based approach across market performance, peer group comparisons and individual portfolio analytics to differentiate investment products.
Differentiating Products Using a Factor Framework: presentation by Dr Peter Hopkins of Style ResearchMonday 24th April, 2017
Dr Peter Hopkins, COO of Style Research has been invited as an expert speaker at the AIMSE London Consultants Conference this month. The event is Tuesday, April 25th, 2017 at the Courthouse Hotel in London.
His session “Differentiating Products Using a Factor Framework” will cover:
- A brief history of factor investing and how it has evolved over the last several decades
- A look at popular factors and their recent behaviour across global equities
- A Case Study review focusing on a custom peer group of Large Cap Global managers, using a factor-based view of the market
- An examination of specific funds within this group, using a factor framework to highlight differentiations
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.
As Q1-2017 draws to a close, the investment community is preparing for the upcoming performance review season. During these investment performance reviews, investors are seeking objective and comprehensible stories that ultimately serve to either shake or strengthen their investment manager relationships. However, performance reviews are not solely about measuring performance to the third basis point. Investors are also incorporating context and perspectives about what has happened in various geographic markets and how that led to specific classes or peer groups having outperformed. Performance review season is ultimately about creating, delivering and gaining confidence around a story. It is a complex process and, unfortunately, today there exists a widespread problem.