George Bonne leads equity-factor research at MSCI, where he and his team design the Barra equity-factor risk models and conduct research on innovative content used in MSCI’s analytics and index products. Prior to MSCI, George was director of quantitative research at Thomson Reuters StarMine, where he created novel alpha signals for investment managers. He previously worked at Applied Materials and KLA-Tencor optimizing the performance of semiconductor equipment. George received his doctorate in physical chemistry from Harvard University and a bachelor’s degree in chemistry from UC Irvine.
Research and Insights
Articles by George Bonne
An Artificial Intelligence-Based Industry Peer Grouping SystemReport | Jul 15, 2022 |
In this article published in the Journal of Financial Data Science, coauthors from MSCI and MIT develop and describe a data-driven system using AI tools to capture market perception and, in turn, group companies into peer clusters.
Is the Energy Trade Running Out of Energy?1 mins read Quick Take | Jun 20, 2022 |
The energy sector has become the most crowded with investors, largely due to rising valuations and short interest. We evaluate the impact of its shrinking base of companies as well as the potential implications for net-zero-aware investors.
Stock Crowding Shifts… Again1 mins read Quick Take | May 12, 2022 |
The U.S. stock market has plunged 15% to start the year, while growth stocks have fallen even farther. Many firms are suffering through historic drawdowns and a resetting of their valuations.
MSCI Security Crowding ModelReport | Feb 4, 2022 |
The MSCI Security Crowding Model extends the framework of the MSCI Factor Crowding Model to individual securities. Our primary motivation was to identify crowded stocks, which we assumed would underperform, on average, and be more susceptible to crashes. If the model is working as intended, we also assume uncrowded stocks would outperform. This would be consistent with our factor-crowding research. Because any security-level characteristic could potentially be a factor, we evaluated our...
Eyeing the Crowds from Multiple Perspectives6 mins read Blog | Jul 8, 2021 |
We observed historically notable crowding across factors, industries and stocks through the first half of 2021. Examining crowding from multiple perspectives and incorporating multiple data elements provides investors a more holistic view.
Machine Learning Factors: Capturing Non Linearities in Linear Factor ModelsReport | Mar 26, 2021 |
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.
Is There a Hedge-Fund-Crowding Factor?6 mins read Blog | Mar 10, 2021 |
Hedge funds held heavy, relatively illiquid short positions in crowded stocks before the January 2021 short squeeze. We created a risk factor that added explanatory power and may provide insights into potential short squeezes and other risks.
Are (Stock) Bubbles Rising?6 mins read Blog | Feb 12, 2021 |
How does one identify or quantify a bubble? We propose a framework for assessing the “bubbliness” of stocks and portfolios, rooted in the idea that bubbles are driven by the same forces, and share characteristics with crowded trades.
The Many Faces of SentimentReport | Dec 4, 2020 |
We extend our research into sentiment measures by introducing several more traditional and alternative datasets, analyzing their historical and recent performance individually, and as an equal-weighted combination. Our analysis indicates sentiment factors increased transparency into sources of risk and return and the potential for positive risk-adjusted returns, compared to traditional factors.
Are Momentum’s Wings Finally Starting to Melt?3 mins read Blog | Nov 13, 2020 |
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?
Straight Talk on Nonlinearities in Linear Factor ModelsReport | Jun 1, 2020 |
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.
The coronavirus market impact spreads globallyBlog | Mar 5, 2020 |
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.
Factors separated fact from fictionBlog | Oct 16, 2019 |
Technological advances have expanded the application of factors. What was the realm of quantitative investors has become more accessible, bringing greater transparency and potential insight into portfolio characteristics and performance drivers.
Back-to-school (momentum) blues?Blog | Sep 13, 2019 |
The U.S. price momentum factor, which we highlighted for elevated crowding scores and vulnerability to negative performance at the end of June, suffered sizable drawdowns in the first seven trading days of September.
Where were the (factor) crowds this summer?Blog | Aug 21, 2019 |
When factors have historically become crowded, they’ve often experienced significant drawdowns in subsequent months. Which factors were relatively crowded at the end of 2018 — and how did they perform in the first half of 2019?
More than a feeling: Quantifying consumer sentimentBlog | Jul 17, 2019 |
Among a flood of alternative data sources, consumer sentiment based on citations online stood out.
Peering Into Peer Selection: Quantifying Company SimilarityReport | Mar 15, 2019 |
Peer selection plays a central role in many aspects of finance — including valuation, financial and competitive analysis, risk and portfolio modeling and ESG scoring and alpha generation. One common method of peers identification is industry classification, such as the Global Industry Classification Standard (GICS®). Here we ask if it’s possible to identify and measure relationships between companies from a systematic analysis of various types of data, including fundamentals, news and the...
Should we be surprised by earnings surprises?Blog | Feb 1, 2019 |
Early 2019 earnings season has already contained a number of high-profile surprises, such as Facebooks's, but how predictable are these surprises, and what happens when earnings surprises return to trend?
Equity Markets in October – Has the Tide Turned?Blog | Nov 5, 2018 |
October’s market sell-off reflected investors’ concerns with the sustainability of economic growth, the longer-term impact of trade tariffs and rising interest rates. In all, it seemed to be a shift away from pro-cyclical themes. Do risks remain for those areas of the market?
Is momentum a crowded trade that is starting to unwind?Blog | Aug 29, 2018 |
The momentum factor has been on a tear the last year and a half. Is momentum a crowded trade that has started to unwind?
Why is Tesla a Short-Selling Target?Blog | Aug 13, 2018 |
Elon Musk, founder and CEO of Tesla, suggested in a series of tweets that going private could help Tesla avoid the scrutiny of quarterly reporting and pressure from short selling. Do companies targeted by short sellers share common characteristics? Could factor analysis help investors identify stocks that may become short-selling targets?
All FAANGs are Not Created EqualBlog | Aug 3, 2018 |
FAANG stocks (Facebook, Apple, Amazon, Netflix and Google) make up nearly 40% of the NASDAQ 100 index, and smaller but significant weights in many others. Commonly grouped as tech stocks or growth companies, it seems reasonable to assume they share many similar characteristics. However, when examined through the lens of performance-driving factors, their characteristics are far from homogeneous.
Anatomy of Hedge Fund PortfoliosReport | Jul 16, 2018 |
Measuring hedge funds’ positioning and potential crowding around stocks is of interest to many investors, given these funds’ reputation for outperformance. We explore the performance of hedge fund positions using MSCI HedgePlatform, which has advantages over U.S. Form 13F filings, including monthly data points, improved timeliness and full visibility of short positions.
MSCI Integrated Factor Crowding ModelReport | Jun 18, 2018 |
With the rise of factor investing, institutional investors increasingly have sought to understand whether their factor exposures are crowded. Current MSCI Barra equity factor risk models are designed to provide insight and detail to help institutional investors understand how a portfolio is positioned and what has driven its risk and return. The MSCI Integrated Factor Crowding Model is designed to complement the Barra model by providing investors with insight into how the rest of the market...
Creating a common language for factor investing3 mins read Blog | Jan 18, 2018 |
Investors need a clear and consistent way to talk about factors. For more than 40 years, MSCI has defined how investors use factors to analyze risk and return, from individual stocks to entire portfolios. Factors are important drivers of portfolio performance and are well documented in academic research. They are used to quantify how much risk and return is attributable to different countries, sectors and styles.
Introducing MSCI FaCSReport | Jan 18, 2018 |
Factors are important systematic sources of risk and return in equity portfolios. Given the pervasive use of factors via both active and indexed strategies, a standard approach is needed for defining factors and evaluating the factor characteristics of portfolios. We introduce MSCI FaCS, a classification standard and framework for analyzing and reporting of style factors in equity portfolios that is based on the Barra Global Total Market Equity Model for Long-Term Investors. Managers can use...
Why is “Fear” Missing From the “Fear Index”?Blog | May 12, 2017 |
Although global uncertainties remain high, the CBOE VIX Index — also known as the “fear index,” recently reached its lowest level since 1993. Some observers have questioned whether VIX remains a reliable indicator.