The CFA Institute European Investment Conference is a focused, interactive conference for Europe’s leading investment professionals. The 2017 CFA Institute European Investment Conference will bring portfolio managers, analysts, chief investment officers, and CEOs together in Berlin on 16–17 November.
Not long ago, bright graduates seeking investment careers were guided solely toward research and front-office roles and steered away from functions dismissed as necessary but unglamorous middle-office positions — the descriptor “middle-office” evoking the staid and stable lifestyle of most hobbits in J.R.R. Tolkien’s “Middle-earth.”
But spectacular advances in computer-processing power, visualization methodologies, and other innovative techniques are now eroding boundaries among risk, performance, and investment decision-making professionals.
Understandably, the demand for an enhanced understanding of risk and performance comes from clients still punch drunk from the financial crisis. But the demand for more effective risk and performance quantification is equally driven by internal organizational imperatives and regulation. Lindsey Matthews, CFA, of UBS Delta, told the audience at the European Investment Conference to go out and challenge traditional middle-office organizational models. “The analysis of risk and analysis of performance need to be brought back together,” he said. “Mixing people up” is one solution.
A Consistent View of Risk and Performance
To demonstrate that asset managers need to relate risk and performance, Matthews began with an example of a European Investment Bank (EIB) bond that is evaluated very differently by professionals from each discipline. To value this bond, risk officers look at tracking error in both sovereign and supra-national categories, whereas performance officers examine relative performance only in terms of sovereigns. Performance and risk teams use different sets of factors, sectors, categories, and views of the world to understand risk and performance leading to inconsistencies in many organizations. A portfolio manager may be erroneously assumed to be outperforming (and unjustly receive a bonus) if the wrong metric is employed.
“Decision making is about allocating risk to exposures, combining those exposures with some model of how the market might move,” Matthews said. So understanding where your model is appropriate and where it is useful is essential to ensure you are taking your risks with true conviction. With the right framework and models, scenario testing and simulations can then be better deployed to help avoid potential icebergs.
Visualizing Fixed-Income and Equities Risks and a Critique of Modern Portfolio Theory
Using such appealing visualizations as a correlation triangle — dynamically tying together portfolio volatility, tracking error, and benchmark volatility — Matthews emphasized the potential of such factor models to explain risk. Naturally, the success of any feedback loop employing these models depends on accurately isolating some meaningful factors and their correlations.
In equities, factor models can map exposures to the market, the sector and region, style buckets, and idiosyncratic components. For fixed income, they can map sensitivities to curve changes, shapes of rate curves, inflation curves, and individual issuer spread curves on which factor models (increasingly) are constructed and linked to multi-asset portfolios combining equity and fixed-income exposures.
More controversially, Matthews took a swipe at modern portfolio theory (MPT), making a more relativist argument for alternative techniques to try and pin down individual security and portfolio risk. “A lot of MPT was about reduction of dimensionality and making problems tractable,” Matthews said. “But we now have in our pocket more computing power than was used to land on the moon.” If we were starting today with a blank sheet of paper, would we all be looking at correlations and recent volatility defined via standard deviation? Possibly not. Yet MPT has stood the test of time and many cycles. More novel metrics and approaches, even those Matthews referenced involving big data and Benson-Zangari algorithms, have their own pros and cons.
Matthews also shared some prescient thoughts on investing in fixed income in a rising rate environment, recommending watching out for the easily ignored impact of carry. Finally, he explored the esoteric and dynamic relationship between correlation and hedging, which prompted him to propose some interesting fixes to assist decision making.
So, the middle-office arena, once overlooked by aspirant investment bankers, now offers its staff opportunities to more actively contribute to investment decision making across asset classes than ever before. With innovative techniques at hand and as conflicts raised by multiple systems and integrations within banks are resolved, we may soon see a consistent framework for risk, performance, and decision making.
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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.
Photo credit: Harry Richards