In risk management a lot of focus and attention is (rightly) put on models and methodologies used to compute ex-ante risk measures. And in the context of a multi-asset class universe which is vast by nature, perfect data (market data, terms and conditions provided by the user) and bug-free algorithms are not always possible. Therefore, one of the key challenges for risk managers is to ensure that any risk analytic produced is sound and reliable.
In this paper, we examine the historical interaction of equity and bond-market returns—both in the recent past and over the last 70 years—in an effort to identify the main triggers of shifts in their relative directions.
Understanding changes in risk estimates can be key, especially in times of crisis when volatilities spike and correlations point in the same direction, eliminating the diversification that was supposed to protect a portfolio.
The best risk model is the one most closely aligned to your strategy. In some cases, using a single integrated regional model may help you achieve better results. We offer a range of Equity Factor Risk Models – US, Developed Markets ex-US, and Emerging Markets – connected as a Linked Model for more flexible and tailored risk forecasting and attribution.
Foreign-exchange rates can be very volatile. Investors looking to bet on markets outside their own base currency must decide whether to embrace or mitigate the additional risk. In this paper, we propose a stress-testing framework that can help investors with the decision whether “to hedge or not to hedge”, given their assumptions on expected returns and cross-asset correlations.
In this research piece, we demonstrate the value of the Axioma Worldwide Equity Linked Factor Risk Model (WWLM4-MH or ‘Global Linked Model’) for solving two very common analytical problems when managing global portfolios. Global equity mandates are often broken into specialist mandates segregated by geography.
In this paper, we take a closer look at the pairwise interactions of some of the asset-class pairs and review how they affected the risk of a global multi-asset class portfolio over the past 14 months, with a particular focus on the most recent environment.
In a surprising turn of events, most equity markets finished 2020 with sizable gains—and the fourth quarter unquestionably did its part. Benchmark risk continued to slide in Q4—except for a blip in November—but still ended the year higher than where it started. Factor returns went wild in Q4 and many regions saw outsized returns for the year.
Sector-allocation decisions form an integral part of many investment processes, both in equity and fixed income portfolio management. Most benchmark providers in both asset classes provide a wide range of sector sub-indices, and many risk models contain sector factors. By comparing Axioma’s new Factor-based Fixed Income Risk Model with a more traditional approach, we demonstrate that while sectors do play a role in credit investment management, they do so to a much lesser extent than one might expect.
There is no denying the impact of climate change — and associated regulatory realities — on the business of investment management. For portfolio managers, it is essential to understand how to successfully adapt and prepare for what some call the “mother of all correlated risks”. Here we expose — in three parts — what portfolio managers need to know when switching to a fully Paris Aligned Benchmark (PAB) portfolio from a current market-cap weighted (CWB) portfolio.
This study explores the impact of the reclassification, from a risk-oriented perspective, on the STOXX® Global 1800 and STOXX® Europe 600 indices. We focus our analysis on the highest two tiers of the classification: Industry and Supersectors.
Style-factor risk premia have been well-documented (and harvested) in the equity world for decades but have proven far more elusive for bonds. The new Axioma Factor-based Fixed Income Model (FFIM) demonstrates that style factors not only do exist in credit, but that they also carry discernible risk premia, which, in turn, can be utilized for systematic, smart-beta investing.