Take a closer look at innovations and shifts in investment management and risk assessment.

  • How to model a trade war - just in case...

    The trade war between China and the US has been the single most important driver of financial market performance in the past three years, and despite the recent optimism that a “phase one” deal is within reach, there is still a distinct possibility for it to fall apart at the last minute. Similarly, the tariff decision on EU car imports has only been put on hold for another six months, keeping the threat alive for future use. This paper shows how stress tests can be a used to identify potential vulnerabilities and unwanted exposures in portfolios, and also points out strategies for diversification and loss-minimization.

    Christoph V. Schon, CFA, CIPM, Executive Director, Applied Research Research Paper No. 149
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  • A New Data-Driven Fixed-Income Risk Framework

    Modeling potential losses of a credit-risky bond portfolio based on granular, issuer-level return data is notoriously difficult. A myriad of data-quality concerns arise, driven by a vast, frequently illiquid market for which evaluated pricing is often stale, inconsistent or simply missing. Many issuers have only a small number of bonds outstanding. In fact, generally less than half of the issuers in USD high yield index portfolios have more than one bond outstanding that meets standard requirements for inclusion in a model estimation universe (sufficient maturity, etc.). Thus great care must be used to extract signal from data noise.

    Bill Morokoff, Managing Director, Research Research Paper No. 148
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  • Shortchanged by the No-Short Constraint — and Other Observations on 2019 Factor Performance

    Many quant managers are having a tough go of it this year. While one might blame factors in general, their returns do not tell the whole story (or even the bulk of the story). We think one of the major culprits in the US is that a number of factors worked better on the short side and among small-cap names, but even that does not explain all of the underperformance.

    Melissa R. Brown, CFA Research Paper No. 147
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  • What Risk-Aversion Parameter Should I Use? And Should I Care?

    The quadratic utility function balances two conflicting objectives: more return and less risk. It is a way to pick one portfolio on the efficient frontier. Investors initially assumed that the active risk aversion parameter was the same as the total risk aversion parameter, but we show that they are different and ask the question – is this still relevant today?

    Dominic Clermont, Front Office Solutions Director, Qontigo Research Paper No. 146
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  • Qontigo's New Granular Fixed-Income DTS-Style Risk Model for Axioma Risk

    Modeling potential losses of a credit-risky bond portfolio based on granular, issuer-level return data is notoriously difficult. A myriad of data quality concerns arises, driven by a vast, frequently illiquid market for which evaluated pricing is often stale, inconsistent or simply missing, while many issuers have only a small number of bonds outstanding.

    Bill Morokoff, Managing Director, Research Research Paper No. 145
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  • Q3 2019 Insights

    Market risk changed little...
    But a lot happened under the hood
    Markets around the globe wavered over the past three months, but the decade-long global bull market endured in the third quarter. Despite the market’s gyrations, risk was little changed, with most major indices seeing only a relatively small rise in risk from the end of the second quarter to the end of the third quarter. Nonetheless, a lot has happened beneath the surface.

    Applied Research Team Research Paper No. 144
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  • Minimum Variance: A Leg Up on Geopolitical Risk?

    In this paper, we take a look at how minimum variance performed vis-à-vis its core market counterpart during nine recent geopolitical risk events. The nature of these events is that they tend to push correlations towards 1.0. This may pose a problem for minimum-variance portfolios, as they are constructed by leveraging the covariance matrix in order to build portfolios with strong systematic hedges, simultaneously going long on negatively correlated factors or (in active space) long and short positively correlated ones. In these types of crises, is their ability to significantly reduce portfolio risk vis-à-vis a core benchmark hampered? If not, what kind of outperformance can we expect in down-markets, and what are the performance costs of this insurance in up-markets?

    Olivier d’Assier, Christoph Schon, and Marco Della Seta, Research Paper No. 143
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  • Is Your Smart Beta Product Scalable?

    In this paper, we use the backtester capabilities of the Axioma Portfolio Optimizer to investigate the maximum capacity of a smart beta strategy, based on the Profitability factor in the Asia ex-Japan equity market. Profitability is one of the style factors in the Axioma Asia Pacific ex-Japan fundamental factor model (v4) that has had a persistently positive return over the last several years, and has become a popular style tilt with regional managers.

    Olivier d'Assier, Applied Research, APAC Research Paper No. 142
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  • Q2 2019 Insights

    A Strong Market ... but on Thinning Ice?
    With the US remaining riskier than most benchmarks
    While equity markets were strong overall in Q2—and risk levels did not stand out—some trends were troubling and investors should be cognizant of them. This report contains a detailed analysis of what happened to top-line risk and its drivers across the globe in the quarter, as well as a detailed analysis of style factor performance. We take particular note of the unusually poor performance of a number of style factors on which many investors bet, continuing the trend of the last few quarters. It has been our experience, albeit difficult to prove statistically, that unusually anomalous factor performance may be a harbinger of a change in the market’s direction.

    Applied Research Team Research Paper No. 141
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  • What Is a Factor? Part 2: The Impact of the Long-Only Constraint

    In this paper we extend our analysis of how the construction of a factor portfolio, even using the same underlying factor definition, can have substantial impact on the returns the factor generates. The current paper digs deeper into the impact of a long-only constraint, and describes the characteristics of these portfolios as well as the associated performance. One main goal is to describe how a traditional factor-mimicking portfolio might misstate the returns a long-only manager can achieve.

    Melissa R. Brown, CFA, Esther Mezey, PhD, Ipek Onat, MSc, Dieter Vandenbussche, PhD Research Paper No. 140
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