How is the Allview approach of embracing autonomous investment team views and a differentiated approach to generating alpha reflected in our approach to investment risk management? Our co-heads of Investment Analytics, John Hockers and Randy Mangelsen give their views.

 

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Martha Delgado: I’m Martha Delgado, sales director for International Business Development at Allspring, and you’re listening to On the Trading Desk®. Today, we’re talking about risk management here at Allspring Global Investments and its applications within Allspring’s Allview approach. Joining us are Randy Mangelsen and John Hockers, co-heads of Investment Analytics for Allspring. Randy and John, thanks for being here.

Randy Mangelsen: Thanks for having us, Martha.

John Hockers: Yeah, happy to be here.

Martha: Great. So I’d like to start with a question for you, Randy, that’s focused on how your team views risk management. In looking at your team’s org chart, I see that your team reports to the Office of the CIO (chief investment officer). Why do you feel it is important to be part of the investment function rather than outside of investments?

Randy: That’s a great question. Our approach to investment risk management reflects Allspring’s commitment to autonomous investment teams and differentiated approaches to generating alpha, the Allview approach that’s been discussed on past podcasts. It also is a structure and philosophy that stretches back to 2005, so we have a long track record with it. We function as the eyes and ears of the Office of the CIO, providing transparency and an independent evaluation of portfolio risk that serves as a complement to each team’s embedded risk management efforts. We have the same goal, as each team does, to provide positive client outcomes that are consistent with what the client should expect from any given strategy. That doesn’t always mean we try to reduce risk. In fact, we have encouraged teams to take more risk in some cases where it was appropriate for the strategy. But the proximity to investment teams and our history of collaboration alongside with credible challenge has earned us a level of access and trust that would be hard to recreate with separate reporting lines. We have found the balance of partnership and control, with the risk mitigation authority owned by the Office of the CIO, has been an effective approach and one that really resonates with clients.

Martha: Great. So, John, what types of risks does the Investment Analytics team monitor?

John: Thanks for the question, Martha. Our primary role is to focus on investment risks. Those are risks that our investment teams create while managing portfolios for clients. We divide investment risk into three main buckets: market risk, counterparty risk, and model risk. Market risk is covered by three different groups within Investment Analytics. We have an Equity Risk team, a Fixed Income Risk team, and a Multi-Asset Class Risk team. Combined, these 3 teams have a total of 18 different team members. The analysts on these teams are each assigned specific investment managers to work with, so that they can build a deep, long-lasting relationship with those teams. On the technology front, we use advanced multi-factor risk models to help forecast benchmark-relative risks in each investment strategy, along with detailed attribution analysis that helps us understand what worked, what didn’t work, and what a team can do differently going forward. Armed with these tools, we work with the investment teams to help make all of their risks transparent to everyone involved. Whether it’s an intended risk or an unintended risk, we want everyone to know what the risks are in the portfolios going forward. Counterparty risk is handled a bit differently. When our managers trade, they need to use broker/dealers or counterparties to gain access to securities. We manage the default risk of these counterparties by conducting in-depth credit analysis before we make them available on our platform and then we follow up that with annual financial reviews and daily news monitoring to ensure that that creditworthiness stays strong throughout the life cycle. The third type of investment risk that we cover is model risk. This is the risk that our quantitative investment teams create when they develop complex algorithms and code to manage investments in a systematic way. Our model validation and governance team reviews all of these complex quantitative models to ensure that they behave as intended.

Martha: Thank you, John. And how is the management of these three types of investment risks important to Allspring?

John: Well, great question, Martha. Thank you. Clients hire us to take investment risks in an effort to beat our benchmarks. Said another way, investment risk management can help our portfolio managers deliver that consistent risk-adjusted alpha that our clients expect. I think it’s important to remember, too, that we’re here to really manage risk, not reduce risk. As Randy alluded to earlier, we can’t deliver on the client expectations that we have if we remove all of the risk from a portfolio. So our role is really to optimize that risk—sometimes increasing it and sometimes reducing it—to focus on the areas where our investment teams have a competitive advantage or an edge versus the market. I’ll end with one last point. I think our investment risk management processes also help facilitate a strong culture of accountability—accountability to our clients, to our senior leadership group, and to our Allspring shareholders.

Martha: Thank you, John. So in addition to risk management and oversight, your team also provides analytics and tools to support investment teams. Randy, what are some of the things you’re doing on the analytics front and why do you feel that that’s an important part of risk management?

Randy: Well, as I mentioned earlier, we have found that gaining the trust of the investment teams is one of the keys to effective risk management. Part of the reason we’ve been able to build that trust is because of our dual mandate of risk management and analytics. A huge part of that is the ad hoc risk analysis and performance attribution that John talked about, but we have also expanded to include functions more directly dedicated to analytics. For example, our Portfolio Analytics team provides, among many other things, detailed peer-relative analysis that helps investment teams better understand how their performance compares to peers and why it might be different. They can look for trends across the industry or even identify common exposures or concentrations across managers. Our ESG Risk Analytics team helps portfolio managers understand risks and opportunities stemming from environmental, social, and governance topics and support carbon-reduction initiatives for clients, regulators, and Allspring as a whole. Our Portfolio Construction Research team partners directly with investment teams to build or reposition portfolios that allow them to achieve particular exposures in a risk-efficient manner. And our Scientific Learning team works to uncover insights from traditional and alternative data sets using machine learning techniques to supplement traditional research along with developing proprietary data sets and factors to support a variety of investment needs. For example, the team partnered with our Global Credit Research team to develop ESGiQ, a proprietary ESG framework that uses statistical techniques to derive commonality from vended data and combines it with name-level fundamental research to deliver a unique forward-looking assessment. What we’ve found is that beyond the relationship benefits that such partnership provides, we can also serve as an alternative resource to teams while allowing them to remain focused on their core investment processes.

Martha: Thank you both very much. With the time that we have left, do you have any parting thoughts for our listeners?

John: Yeah, I’d like to highlight something that Randy mentioned earlier. He mentioned that our team is the eyes and ears for senior management. I would also say that we’re the eyes and ears in the organization for our clients. We’re here to be that watchful eye over our clients’ investment portfolios. So if I think our listeners take one thing away, I think that’s the point they should take away. It’s that we’re here to be that watchful eye, looking over their portfolios on their behalf.

Martha: Thank you so much, John and Randy, for being with us today and sharing your insights.

John: Thank you, Martha.

Randy: Thank you. It was a pleasure.

Martha: And that wraps up this episode of On The Trading Desk®. If you’d like to read more about market insights and investment perspectives from Allspring Global Investments, you can find them at our firm’s website, allspringglobal.com. To stay connected to On The Trading Desk® and listen to past and future episodes of the program, you can subscribe to the podcast on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. I’m Martha Delgado. Thank you for listening.

Disclosure: Alpha measures the excess return of an investment vehicle, such as a mutual fund, relative to the return of its benchmark, given its level of risk as measured by data. Alpha is based on historical performance and does not represent future results.

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