Our new framework links financial markets to macroeconomic factors, focusing on cash flows, discount rates, growth and inflation. It helps investors in their capital-market assumptions, risk management and asset allocation, using the MSCI Macro-Finance Model. 

Since ChatGPT's debut less than 18 months ago, artificial intelligence has dominated headlines, and excitement and apprehension now surround its entry into the world of finance and investment. But just what are the expectations and misconceptions?

Key insights from the recent MSCI Institutional Investor Forum highlight how forces of disruption are driving asset owners to evolve their assessment of risks and how developments in AI can further blend quantitative and qualitative investment analysis.

We are witnessing the rise of private assets to the core of many asset allocations and have entered a new period of heightened macro uncertainty. Both could require a fundamental evolution of the asset-allocation process.  

This Model Insight introduces the MSCI Fixed Income Factor Model (FI400), MSCI’s fourth-generation fixed income factor model suite. The model represents the key drivers of risk and return in the modern fixed income markets. It combines detailed representations of individual fixed income markets and sectors integrated into a global, multi-asset class framework. Together, these components provide information that can drive more informed investment decisions and client interactions, forming a...

Private assets face demands for transparency amid greater interest from investors seeking to understand risks, performance and how these investments compare to public securities. We speak with Peter Shepard, Head of Fixed Income, Multi-Asset Class and Private Asset Research and Brian Schmid, Global Head of Product Management and Applied Research at Burgiss.

MSCI’s Barra Private Real Estate Model (PRE2), Barra Private Equity Model (PEQ2) and MSCI Private Infrastructure Model (PIN1) have advanced the understanding of investments in global private assets. Private assets were once considered low-risk investments uncorrelated with most public assets due to the smoothness in private asset valuations. With innovative statistical methodology, the MSCI private asset models reveal the intrinsic risk in private assets, show large exposures to systematic...

Investors taking stock of the coronavirus fallout and recent market volatility have begun exploring tail-risk-hedging strategies as a way to protect against further drawdowns. What are the potential costs and benefits of hedging against tail risk?

Stock and bond prices dropped together during the recent coronavirus sell-off, leading to fears that U.S. Treasurys were no longer the safe haven they had been in previous crises. Did it mark the end of an era of flight to quality?

What may be happening to the value of portfolios of private assets during the COVID-19 crisis? We used MSCI’s private-equity model, which integrates data on private assets from our partner Burgiss, to try to shed some light.

With the outbreak of the COVID-19 pandemic, the U.S. equity market turned sharply downward. We performed a reverse stress test considering various scenarios that potentially explain current valuations.

For most of the past two decades, a benevolent relationship between bonds and equity has prevailed as a central pillar of asset allocation. Falling equity markets consistently coincided with falling interest rates, providing an effective hedge between bond and equity allocations. Now, talk of weaker central-bank policy or a risk of deflation has many asset allocators focused on the future of the rates-equity correlation. 

Factor investing has brought disruptive change to the asset management industry. First established to systematize stock selection, factor investing now takes many forms and spans many asset classes.

Factor investing is now going multi-asset class: to factor-based asset allocation and systematic strategy factors that push beyond equity selection.

Fixed-income markets have weathered a series of financial crises since 2008, forcing institutional investors to discard old assumptions and seek a risk management framework suited to the new, ever changing environment.

The low interest rate environment continues to send institutional investors on a search for yield. But with the Federal Reserve signaling an increased pace of tightening in 2017, many are reducing interest rate exposure and seeking higher yields in credit instruments.

This Model Insight describes the introduction of private asset models into the time-series-based RiskMetrics’ RiskManager. The framework consistently combines the Barra Private Asset Models, based on low-frequency private asset returns, alongside the high-frequency models of other asset classes.

As investors shift toward global, multi-asset class strategies from narrower mandates, the number of dimensions to manage is rapidly increasing. This complexity requires seeing both the forest and the trees. Investors need a multi-asset class view of the markets, but they also need to understand the unique drivers of risk and return within each market.

This paper describes BIM303, a new version of the Barra Integrated Model (BIM). This new version incorporates the latest Barra equity models, includes several new and updated Barra fixed income models, and completes the history of the private equity and private real estate components. Other local models that form the complete BIM are the same as those in BIM301, the previous integrated model. BIM303, like BIM301, comes in versions for multiple horizons: Short, Long, and Extra Long.

Private real estate and other real assets have become a major component of many institutional investors’ portfolios in recent years, but risk management has lagged. A wide range of proxies and assumptions have stood in place of a solid risk management framework, with perhaps the most common risk model being … nothing.

Private equity is both “private” and “equity.” The valuations look smooth from quarter to quarter, but in the long run, private equity shows a strong relationship with equity and is exposed to many of the same systematic factors that drive traditional assets.

Many institutional investors have been favoring private real estate over bonds, drawn by its steady income stream and higher yields. While the short-term income may be bond-like, the long-run behavior of the asset class is much more cyclical and growth-sensitive.

Growth Drives Long-run Risk and Return

The home bias of real estate investing is starting to change. The world’s largest Sovereign Wealth and Pension Funds are leading the change with explicit global real estate investment mandates seeking to exploit the richer global opportunity set and its diversification benefits. In this Research Insight, we use the Barra Private Real Estate Model (PRE2) to examine the drivers of risk and return in the international real estate markets, and find that fragmentation of the global markets has led...

The recent outperformance of global equities has some investors wondering whether they should reduce their allocations to hedge funds. The announcement from CalPERS to end its hedge fund program cited low returns and high fees, but is that the whole picture?  Sorting out sources of hedge fund performance is particularly important given the recent focus of many institutional investors on factor-based investing.  In this Research Insight, we identify the role that factor exposures...

In this Model Insight, we present the latest Barra Private Equity Model (PEQ2), which represents a major advance in understanding the drivers of risk and return in global private equity. We find a high degree of systematic risk in private equity, but also large opportunities for global diversification and active risk when compared with public equity. Incorporated in the Barra Integrated Model, PEQ2 provides a unique, like-to-like view of private equity investments among all asset classes...

Global private real estate represents significant opportunities for investors, but also major challenges, similar to global equity 30 years ago. A lack of information, and the smoothness of appraisal-based valuations, have left investors and risk managers guessing about the behavior of global real estate: a wide-range of speculation is commonplace, including the view that real estate is a low-risk, high-return diversifier. In this Model Insight, we shed light on this misunderstood asset...

Infrastructure is challenging to model because, as a highly illiquid asset class, it lacks frequent, transaction-based data.   In this Market Insight, we look at two examples: the equity-like Sydney Airport and a bond-like investment in UK power-transmission lines.  We examine different ways to capture their risks using MSCI’s multi-asset class risk model, the Barra Integrated Model.  In both cases, characterizing the investments in terms of their exposures to...

This Model Insight describes the integration of Barra Equity Factor Models into RiskManager’s VaR and stress-testing capabilities. Like the RiskManager pricing models, a Barra factor model explains the return of each asset in terms of the underlying characteristics that drive that return. Factor models extend to equities the many advantages of RiskManager’s pricing models and time-series methodology. After explaining the motivation for using factor models for VaR and...

Investors face the challenge of understanding changes in risk. Did a recent increase in risk come from turnover into more aggressive positions, a spike in market volatility, or a loss of diversification? Which of the investor's positions drove the change? Which parts of the market became more risky? A related issue is understanding differences among risk models. Do such differences indicate a weakness of one of the models, or do they provide insight into the evolving structure of the...

In this paper, we present a daily factor model that forecasts daily volatility of variance for VIX Futures Contracts.

This document describes the new Barra Global Equity Model, GEM2, and provides an in-depth comparison with the model it replaces, the Global Equity Model (GEM). With GEM, originally released in 1989, Barra pioneered the use of factor models for the forecasting of global equity portfolio risk. In the nearly 20 years since the launch of GEM, changes have occurred that warrant the introduction of a completely new model. These changes fall into two categories.First, additional data sources are...