Research

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

  • What's in a Name? In The Case of Smart Beta, It's Hard to Tell

    Do ETF buyers, especially those seeking smart beta strategies, really know what they are getting? Is it alpha? In this paper, we focus on a few types of smart beta portfolios in order to highlight similarities and differences driven by methodology. Our results suggest a number of conclusions about how investors should be thinking about the proliferation of smart beta portfolios.

    Sebastian Ceria, PhD, Melissa Brown, CFA, Ian Webster, and Robert Stubbs, PhD Research Paper No. 74
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  • Executive Summary: A CVaR Scenario-based Framework For Minimizing Downside Risk In Multi-Asset Class Portfolios

    In this paper, which is an executive summary of an Axioma technical report, we show how to minimize downside risk in multi-asset class (MAC) portfolios. By comparing the scenario-based Conditional Value at Risk (CVaR) approach with parametric Mean-Variance Optimization (MVO) approaches that linearize all the instruments in the MAC portfolio, we show that (a) the CVaR approach generates MAC portfolios with better downside risk statistics, and that (b) the CVaR hedges return more attractive risk decompositions and stress-test numbers—tools commonly used by risk managers to evaluate the quality of hedges.

    Kartik Sivaramakrishnan, PhD, and Robert Stamicar, PhD Research Paper No. 73
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  • CoCo Risk: Practical Approaches to Measuring Risk

    CoCo (contingent conversion) bonds have seen an upsurge in the headlines lately. In a nutshell, these instruments allow banks to boost regulatory capital during periods of financial stress, but not at the expense of taxpayers; hence, these instruments mitigate the too-big-to-fail doctrine. Investors of CoCos take the brunt of losses if a bank’s capital ratio dips below a predefined level.

    Robert Stamicar Research Paper No. 72
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  • Turning Negative Into Nothing: An explanation of "adjusted factor-based performance attribution"

    Factor attribution sits at the heart of understanding the returns of a portfolio and assessing whether a manager has invested in a manner consistent with his value proposition. In this paper, we will step back and look at factor-based attribution from first principles, as well as describe a methodology that will help correct some of the underlying issues that may arise and produce misleading results.

    Research Paper No. 71
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  • More than Just a Second Risk Number: Understanding and using statistical risk models

    Although fundamental factor risk models are more commonly used and understood by portfolio managers, statistical factor risk models provide an important alternative and adaptable view on risk. In times of unusual market movements and trends that are not well modelled or captured by traditional fundamental factors, statistical risk models can be leveraged to identify these unexpected sources of risk. This paper describes how a combination of fundamental and statistical factor risk models can be exploited in any investment process.

    Christopher Martin, MFE, Anthony A. Renshaw, PhD, and Chris Canova, CFA Research Paper No. 70
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  • Multi-factor Investing: Practical Considerations for Portfolio Managers

    Factor-based and smart beta products have become a growing trend as investors look for ways to quantitatively expose their portfolios to certain historically successful investment themes while reducing the volatility that comes from betting on individual securities. The factor investing trend spawned multi-factor investment products as investors recognized that certain factors may underperform in certain market conditions and combining one or more of them can potentially limit the portfolio’s downside risk.

    Ian Webster Research Paper No. 69
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  • Axioma delivers FinTech’s first born-in-the-cloud, multi-asset class enterprise risk solution

    Following the global financial crisis of 2008, capital markets organizations have faced increasingly stringent regulatory reforms designed to make global markets safer for investors, improve transparency, reduce risk and avoid another financial meltdown. Financial institutions are actively working to enhance and future-proof risk analysis across their business and investment needs.

    Research Paper No. 68
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  • Stress Testing the Impact of Brexit On Bonds, Equities and Other Assets Using Axioma’s Multi-Asset Class Risk Tools

    How might investors be affected if the United Kingdom leaves the European Union? Here we explain how an investor may wish to distinguish between the immediate implications and long-term structural consequences of the event. We review other partially relevant historical events for guidance. Obviously, significant comparable political turning points are somewhat rare in contemporary financial markets, so finding historical precedence to assist in modeling the likely consequences for asset prices is difficult.

    Philip Jacob, Ph.D.; Diana Rudean, Ph.D.; William Morokoff, Ph.D. and Melissa Brown, CFA Research Paper No. 67
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  • A CVar Scenario-based Framework: Minimizing Downside Risk of Multi-asset Class Portfolios

    Multi-asset class (MAC) portfolios can be comprised of investments in equities, fixed-income, commodities, foreign-exchange, credit, derivatives, and alternatives such as real-estate and private equity. The return for such non-linear portfolios is asymmetric with significant tail risk. The traditional Markowitz Mean-Variance Optimization (MVO) framework, that linearizes all the assets in the portfolio and uses the standard deviation of return as a measure of risk, does not accurately measure risk for such portfolios. We consider a scenario-based “Conditional Value-At-Risk” (CVaR) approach for minimizing the downside risk of an existing portfolio with MAC overlays.

    Kartik Sivaramakrishnan and Robert Stamicar Research Paper No. 66
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  • Managing Securitized Product Risk - Exploring the Danger Zone From Valuation Cliffs to Waterfalls

    In this whitepaper, we will explore how to discover the hidden risks associated with securitized products. We will work through a specific example of a typical model pipeline for valuing securitized products and share a case study of a CRO tasked with vetting a fixed income relative value strategy and compiling a risk report that clearly shows securitized product risk. We will also introduce some of the tools that Axioma can provide to buy-side firms to meet this challenge.

    Will Gajate Research Paper No. 65
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