Axioma's Best of 2017

As 2017 draws to a close, we wanted to share with you some of our most popular research insights from the past year. Stress testing and fixed income portfolio optimisation topics topped our list of downloads in 2017. In case you missed them, we've included our most read papers below, which we hope you'll enjoy.

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Please join us on January 10th for "Q4 Insights: A Look Back, A Look Ahead", our most-attended webinar of the year.
In this webinar, Melissa R. Brown, Managing Director of Applied Research, will discuss the current risk environment and how it might impact investor portfolios. She will review the major drivers of risk during the past quarter and year, including country, currency, industry and style risk. Other topics will include style factor performance and correlations across factors, individual assets and asset classes.

Best of Axioma's Research 2017


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.


Risk Resolution: A Framework for Generating Custom Risk Models

At Axioma, we often debate what constitutes a standard multi-asset class (MAC) risk model. First, there is the choice of the risk factors. On the one hand, the standard model should consist of a parsimonious number of risk factors, but on the other hand, it should capture all relevant risk factors for a well diversified portfolio.


Adding Alpha by Subtracting Beta: How Quantitative Tools Can Improve a Portfolio's Returns

Fundamental (discretionary) portfolio managers typically build their portfolios from the bottom up. That is, they identify stocks they expect to beat the market and combine them to create a portfolio. However, fundamental managers can leverage quantitative tools to help identify and lessen potential issues in their portfolio, while still maintaining their investment views and goals. In this paper, we use a “real world” portfolio to illustrate how quantitative tools can improve a portfolio’s realized returns.


Factor Correlations Revisited: How a Recent Shift in Market Focus Affected Major Factor Correlations and Portfolio Risk

Since the middle of March this year, we have seen a shift in correlations between equity and foreign exchange risk factors. In this paper, we examine how changes in the correlations of major risk factor types, in particular the relationship between exchange rates and stock markets, affected a global, USD-denominated multi-asset class model portfolio.

Stress Testing Best Practices

Whether embedded in an optimization framework or not, stress tests are critical from a risk management perspective. This note, which outlines common stress testing techniques along with some best practices, is our first installment in a series of notes involving stress tests.


Fixed-Income Portfolio Optimization

By using a risk model to analyze a portfolio, managers gain insight into risk and exposures. For example, how would an increase in spread duration in the energy sector impact the risk of a portfolio? Or what is the impact of an overweight to Financials relative to a benchmark? Fixed-income risk models allow us to quantify these questions, which in turn help managers make better decisions around on how they construct and hedge their portfolios.


Reducing Turnover and Transaction Costs With a New Class of Equity Reversal Signals Based on Volatility Differences

Short-term momentum (STM) is, perhaps, the most well-known equity reversal signal, but is limited in its real world application due to turnover and transaction costs. In this paper, we present three new equity reversal signals. Each new signal exhibits prototypical reversal behavior, and two of them exhibit roughly half the turnover associated with STM.


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