Research

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

  • Q1 2018 Insights

    Farewell Low Volatility…
    Are we now closer to a trough or a peak?

    After falling to historically low levels at the end of 2017 volatility surged in the first quarter, driven mainly, but not exclusively by market risk. Against this backdrop, interestingly, style factors remained quite well-behaved.

    Melissa R. Brown, CFA Research Paper No. 112
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  • How Brexit Changed Financials’ Spots

    Since the UK’s decision to leave the European Union, investors have fretted over the impact of Brexit on the UK and European economies. At a high level, the UK and European financial sectors showed large negative returns before the vote and strong positive returns after. Risk peaked around the referendum date, only to decline abruptly afterwards. The question is, what were the main factors impacting this reversal in performance in each region and what were the contributors that led to the rise and decline in risk?

    Diana R. Rudean, PhD Research Paper No. 111
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  • The Many Faces of Japanese Style Portfolios

    This is the second paper in a series of looking at portfolio construction methodologies for designing style factor portfolios in the Asia-Pacific region written by Olivier d'Assier, Axioma's Head of Applied Research for APAC. In this paper, Olivier focuses on the Japanese market to construct three variants of a long-only active factor portfolios on the following five style factors from Axioma’s Japan fundamental medium horizon risk model (AXJP4 – MH): Dividend Yield, Momentum, Growth, Profitability, and Value. He then compares each variant on the basis of the implicit costs of constraints on the portfolio’s ability to gain a pure exposure to the target factor.

    Olivier d'Assier Research Paper No. 110
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  • Multi-period portfolio optimization with alpha decay

    This research paper appeared in The International Journal of Financial Engineering and Risk Management Special Issue on Applications of Optimization in Finance.

    The traditional Markowitz MVO approach is based on a single-period model. Single period models do not utilize any data or decisions beyond the rebalancing time horizon with the result that their policies are "myopic" in nature. For long-term investors, multi-period optimization offers the opportunity to make "wait-and-see" policy decisions by including approximate forecasts and long-term policy decisions beyond the rebalancing time horizon. We consider portfolio optimization with a composite alpha signal that is composed of a short-term signal that has a high IC but decays rapidly, and a long-term alpha signal that has lower IC but more persistence. We develop a simple two stage multi-period model that incorporates this alpha model to construct the optimal portfolio at the end of the rebalancing period. We compare this model with the traditional single-period MVO model and show that the multi-period model generates portfolios that are likely to have a better realized performance.

    Kartik Sivaramakrishnan, Vishv Jeet and Dieter Vandenbussche Research Paper No. 109
  • The German Coalition Quandary: Reprise or reprice?

    In this paper, Christoph takes a look at the ongoing German coalition discussions as well as the recent market environment in Europe, marked by a number of notable elections in 2017 that include the Dutch general election, the French presidential election, and the UK general election. Ahead of the general vote by Social Democratic constituents in the first week of March 2018, Christoph analyses several potential outcomes to German political parties’ last-minute failure to form a coalition. Using recent European elections for historical correlations, Christoph applied transitive stress testing capabilities in Axioma Risk to estimate the impact of such a shock on a euro-denominated multi-asset class model portfolio. The first calibration period covered the run up to the French presidential and UK general elections, during which the EUR/USD exchange rate and global stock markets were positively correlated; the second calibration period showed similar correlations between equity and FX risk factors, resulting in a stronger market reaction to the exchange rate shock. Both stress tests showed severe developed stock market losses; however, exchange rate changes were very different in each scenario.

    Christoph V. Schon Research Paper No. 108
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  • Q4 2017 Insights

    If “The Market Climbs a Wall of Worry” What Happens When the Market Stops Worrying?
    2017 was a remarkable year, with stocks around the globe extending steep gains, while volatilities plunged to levels at or near historic lows, even in the face of a long list of geopolitical and economic events worldwide. We identified last year’s winners and losers and analyzed the factors driving this large drop in risk worldwide. Finally, we highlighted some positives, negatives and confounding data that may provide insights into the direction and volatility of markets in 2018.

    Melissa R. Brown, CFA Research Paper No. 107
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  • An Aussie Sense of Style

    In this paper, Olivier d'Assier, Axioma's Head of Applied Research for APAC, takes a close look at the compromises involved in constructing a viable smart beta product. In his analysis, Olivier focuses on the key portfolio construction issue of how to balance a desire for target-factor purity with a goal of achieving a high exposure to the target factor. Can we have both? 

    Olivier d'Assier Research Paper No. 106
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  • A Cvar Scenario-Based Framework For Minimizing Downside Risk In Multi-Asset Class Portfolio

    In this research paper published in The Journal of Portfolio Management, we consider a scenario-based conditional value at risk (CVaR) approach for minimizing the downside risk of an existing portfolio with multi-asset class (MAC) overlays. MAC portfolios can be composed of investments in equities, fixed income, commodities, foreign exchange, credit, derivatives, and alternatives such as real estate and private equity. The return for such nonlinear portfolios is asymmetric with significant tail risk. The traditional Markowitz mean–variance optimization (MVO) framework, which linearizes all the assets in the portfolio and uses the standard deviation of return as a measure of risk, does not always accurately measure the risk for such portfolios. We compare the CVaR approach with parametric MVO approaches that linearize all the instruments in the MAC portfolio on two examples involving the hedging of an equity portfolio with index puts and the hedging of a callable bond portfolio with interest rate caps, and show that the CVaR approach generates portfolios with better downside risk statistics; and further, it selects hedges that produce more attractive risk decompositions and stress test numbers—tools commonly used by risk managers to evaluate the quality of hedges.

    Kartik Sivaramakrishnan and Robert Stamicar Research Paper No. 105
  • When It Comes to Momentum, Don't Cramp My Style

    This paper looks at the impact of common constraints on a long-only Momentum-based strategy. The idea is to show how these constraints drive differences in portfolio characteristics, risk and return. The analysis is geared toward helping factor-based managers gain more insight into the potentially harmful impact of portfolio constraints, which may also prove to be unnecessary. The paper also looks into the risk characteristics (other than momentum)  of relatively unconstrained portfolios, to help managers understand past and future performance drivers of a momentum-tilted portfolio.

    Melissa R. Brown, CFA Research Paper No. 104
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  • For Style Factors, One Size Does Not Fit All

    In this article published in The Journal of Investing, Melissa R. Brown challenges the notion of “one size fits all” in regards to style factor performance. She explains how using style factors as measures of both risk and return are commonly incorporated into an alpha-generating process, but that any factor will come with associated volatility. The purpose of this article is to highlight how use of style factors as either alpha generators or for risk management should vary based on investor objectives.

    Melissa R. Brown, CFA Research Paper No. 103