Multi-asset portfolio decision support: challenges and solutions

By Jan Hoenisch | 28 November 2016

Jan Hoenisch, Director of Global Partnerships at Charles River Development, moderates a discussion of challenges and opportunities facing buy-side firms managing institutional multi-asset portfolios. Panelists Dan diBartolomeo, President and Founder of Northfield Information Services; Patrick Kirchner, Managing Consultant of Citisoft; and Lee Garf, Vice President of Product Management at Charles River discuss these challenges and the role technology plays in helping firms address them.

Jan: Patrick, There's a growing focus on understanding and managing risk at several levels. Let’s start with regulatory risk.

Patrick: Regulators are scrutinising buy-side firms more closely than ever. They’re looking at the controls firms have in place throughout their investment process. Spreadsheet usage and data governance models are of particular interest.

The 2018 implementation of MiFID II will put every trade under the microscope, forcing firms to document dozens of data points for each trade. This is driving buy-side interest in risk management and compliance systems, to ensure their technology is aligned with where regulation is heading.

Dan, what about portfolio and macro risk?

Dan: The biggest issue is that central banks have been aggressively adding liquidity to markets for several years, pushing global interest rates to zero or even negative. That's uncharted waters for portfolio managers.

From a mechanical perspective, it’s problematic because most analytical models for evaluating fixed-income and derivative instruments implicitly assume that interest rates will always be positive. Once interest rates go negative, they simply don't work. Investment managers are scrambling to get the analytics revised to reflect the real-world situation that we find ourselves in.

Lee, industry analysts are also talking about technology and vendor risks.

Lee: Underscoring Pat’s earlier point, firms using outdated technologies will be unable to keep up with growing regulatory requirements. MiFID II is a good example, requiring tremendous change in systems and technology in order to manage data and compliance at many points throughout their investment process. Firms certainly have to have the right culture and processes in place, but they also have to be enabled by technology in order to scale and adapt to regulatory change.

There's also vendor risk. Many firms were blindsided by Bloomberg’s recent acquisition of Barclays POINT. Firms are now scrambling to evaluate alternate providers. It's not just POINT, several vendors, both large and small, are merging or being acquired. Asset managers have to look closely at their existing and prospective vendors and assess their long-term financial and corporate stability when making selections.

Dan, risk modelling is growing increasingly sophisticated, yet many asset managers are using risk models only for basic portfolio risk decomposition. How can risk models better inform the investment process?

Dan: Risk modelling is crucial to helping investment professionals understand the risk associated with every position they take. The implicit assumption is that I would not do a big position in a risky asset unless I thought it was going to produce a large return. Conversely, I might take a small position in a non-risky asset for a smaller amount of return. The risk model can validate that our expectations are in line with our portfolio decisions.

Let's move on now from risk management to portfolio management. Patrick, there's an increasingly vocal debate in the industry regarding active versus passive management. Can you give us an overview?

Pat: There's a lot less alpha available in global markets than there used to be. This is squeezing performance fees and resulting in outflows from active managers. They're expected to do a lot more with less.

Earlier, Dan discussed the challenges associated with risk modeling in a low interest rate environment. Low rates are also pushing managers into more risky and illiquid assets to enhance returns. So multi-asset risk platforms are more important than ever. Portfolio managers need to understand the risks associated with these complex instruments, and also determine where the best risk-adjusted returns can be found.

At the same time, it seems there's an enormous opportunity for innovation in the asset management industry. Dan, can you discuss the emerging class of factor-based investment products?

Dan: Essentially, a factor model is a list of characteristics that says, “these securities are similar”. We could be talking about the P/E ratio of stocks or the credit rating of bonds. If I understand how securities are more or less similar to one another, I understand which securities will behave more alike or more differently. It turns out, under a lot of capital market theory, that when I run the risk of having a bunch of securities behave in a common way, I’ll get rewarded for that. If I'm willing to live with those risks, I get the commensurate return associated with it. The question for investors is: given relatively low liquidity in many markets, how do we invest in a way that provides returns above the most basic type of investing, while not having a high liquidity requirement, which traditional active management does.

Traditionally, a portfolio manager would diversify a stock portfolio by company name, or issuer name in the fixed-income world. It turns out that really doesn't work, the reason being that what is driving the performance of many securities is not idiosyncratic, is not specific to a particular firm or bond issuer, it is related to some common factor or event.

We need to be able to understand what is driving these processes, whether it be interest rates, energy costs, or macro events. That's the kind of thing that's not name specific or issuer specific but has impact across a broad range of securities. Diversifying simply by owning 50 different names just isn't good enough.

Lee, how are these risk and portfolio management challenges impacting buy-side investment technology choices?

Lee: Pat mentioned doing more with less, it’s a rather pervasive issue in the industry right now. For example, firms no longer have the luxury of buying and integrating multiple disparate solutions. The cost and headache of maintaining those integrations is simply not viable. They're increasingly opting for single provider solutions with complete end-to-end functionality across the front and middle office, from portfolio construction, analytics, risk, performance measurement, all the way through to trading, post-trade and compliance.

Pat: I’ll build on Lee’s thoughts with a few additional observations. Firms are also looking for multi-asset solutions. Having separate systems for equities, rates, credits and high yield desks no longer makes sense. Buy-side solutions need to support multiple products and strategies, including smart beta, risk parity and liability driven mandates. Perhaps most importantly, risk modelling and measurement is now an integral part of the buy-side investment process, and technology platforms need to reflect that reality.

Another key technology requirement is managed data. Portfolio decision support requires enormous amounts of reference, pricing, benchmark and index data. Accurate, timely and consistent data is critical for informed decision making. Technology vendors are better positioned than their clients to handle the arduous details of data management.

Finally, technology solutions need to support both native and bespoke analytics. This requirement is critical for many firms, especially those managing esoteric derivatives or structured products.

Ian: Thanks for sharing your thoughts today, gentlemen.

 

The panellists:

Jan Hoenisch, Director, Business Development, Charles River Development

Jan leads the business development team which supports new strategic initiatives and maintains existing relationships with Charles Rivers’ numerous partners. Prior to joining Charles River, Jan was head of Product Management at ITG-net, and Platform Product Strategy at ITG. He began his financial services career with three fintech startups. Jan holds an MS in Computer Science from the University of Virginia, and an undergraduate degree in Computer Engineering from Clarkson University.

Dan diBartolomeo, Founder and President, Northfield Information Services, Inc.

Dan diBartolomeo Founded Northfield Information Services, Inc. in 1985 and serves as its President. Before starting Northfield, Mr diBartolomeo served as Director of Research of a New York investment firm, where he was responsible for investment strategy and equity, fixed-income, and derivatives research. In addition, he serves on the Board of Directors of the Chicago Quantitative Alliance and the advisory board of the International Association of Financial Engineers.

Patrick Kirchner, Director, Citisoft

Patrick has over 14 years of experience working with some of the world’s largest investment managers. He has led and participated in a full complement of consulting services from Strategic Assessment & Roadmap exercises, through Evaluation & Selection of industry leading enterprise software, and complex, multi-site implementations. Patrick’s experience crosses multiple product classes and functional areas of expertise. Prior to Citisoft, he was an Implementation Analyst for a large asset manager.

Lee Garf, Vice President, Product Management, Charles River Development

Lee Garf oversees Charles River’s Product Management organisation and is responsible for the development of client-driven product roadmaps. Prior to joining Charles River, Lee served as Head of Global Product at Altisource Labs and held leadership roles at EnerNOC and PTC.