Would adding a Magnificent 7 factor have improved an equity factor model’s performance in the concentrated U.S. equity markets of the last few years? Our analysis shows that the model’s risk-forecast accuracy would not have materially increased.  

It is not etched in stone that relationships between factor exposures and returns must be linear. We found machine-learning algorithms could identify nonlinear relationships and be used to construct a factor showing significant explanatory power. 

Positive vaccine news on Nov. 9 caused big moves in industry and style factors. Those hit hardest this year jumped, while previous high performers slumped. Did this mark new factors leadership and a long-awaited rotation from momentum to value?

We investigate the extent to which nonlinearities not captured by standard linear models within equity factor risk models are present. Overall, we found linear models created a robust framework to identify relationships between factor exposures and security returns through simple linear factors or transformed (e.g., polynomial) variants.

Fear of a coronavirus pandemic and ensuing economic impacts caused sharp drops in global markets after an initially mild response. We look at recent performance from a factor perspective and how quickly factor returns and volatility reverted in past crises.

The toll from the coronavirus has been felt throughout societies, leading to repercussions on the global economy and financial markets. We examine investor impact through markets’ economic exposures to China and factors and by stress testing portfolios.

Fears of a global slowdown have sent U.S. stock markets plummeting recently. Given FAANG stocks (Facebook, Apple, Amazon, Netflix and Google) have been a dominant force in driving U.S. market performance higher over the past few years, did these stocks lead the market’s downward trajectory?

Given high market valuations, some investors worry that a market pullback may be at hand. We saw markets gyrate earlier this year — what if volatility returns? How investors respond to changing market conditions may depend on their time horizons.

This Model Insight summarizes the methodology and empirical results for the fourth-generation Barra South Africa Equity Model (ZAE4). This paper includes extensive information on factor structure, commentary on the performance of select factors, an analysis of the explanatory power of the model, and an examination of its effectiveness in portfolio construction using minimum volatility and index tracking portfolios. It also includes a side-by-side comparison of the forecasting accuracy and...

This Model Insight provides empirical results for the new Barra Korea Equity Model (KRE3), including detailed information about the structure, the performance, and the explanatory power of the factors. Furthermore, these notes also include backtesting results and a side-by-side comparison of the forecasting accuracy of the KRE3 Model and the KRE2 Model, its predecessor.

In an introductory paper, we explained Systematic Equity Strategies (SES) and how they can be used as factors in a risk model.  In this paper, we use data from the Japan equity markets to define seven new SES factors and study their empirical behavior.  Our findings illustrate the important role that these factors play in portfolio construction and risk management. Our study also shows problems associated with omitting these factors from a risk model, and explain why models that...

This Model Insight provides empirical results for the new Barra Japan Equity Model (JPE4), including detailed information on the structure, the performance, and the explanatory power of the factors. Furthermore, these notes also include backtesting results and a thorough side-by-side comparison of the forecasting accuracy of the JPE4 Model and the JPE3 Model, its predecessor.

This paper provides empirical results for the new Barra Europe Equity Model (EUE4), including details on factor structure, commentary on the performance of select factors, analysis of the explanatory power of the model, and an examination of the statistical significance of the factors. Furthermore, these notes include a side-by-side comparison of forecasting accuracy for EUE4 and EUE3.

In this Model Insight, we present the volatilities and cumulative returns for every factor and currency in the GEM2 global equity model.  The analysis period runs from January 1997 through August 2009.

This report introduces the new multiple horizon versions of the Barra Canada Equity Model (CNE4) - Canada Equity Model Short Term (CNE4S) and Canada Equity Model Long Term(CNE4L). Both versions use daily returns data while accounting for serial correlations in aggregating daily factor returns to longer horizons. The new multiple horizon models provide more responsive risk forecasts than the existing model,CNE4. In addition to using higher frequency returns the new multiple horizon models also...