Asset managers globally can no longer ignore fund liquidity risk management.

The U.S. Securities and Exchange Commission’s liquidity rule is designed to protect investors from incurring significant transaction costs when the assets in their mutual funds are not liquid enough to sustain funds’ redemption policies.

Expected Shortfall (ES) replaced Value at Risk (VaR) under the Basel Committee’s Minimum Capital Requirements for Market Risk in 2016. However, whether ES can be backtested is still an open and critical question. We have recently shown that ES can be only approximately backtested, because any ES backtest is sensitive to VaR predictions. This paper proposes a new ES backtest that has the minimum possible sensitivity to VaR predictions, which makes it an appropriate validation tool for ES-based...

Market liquidity around the globe has changed drastically over the past decade, due to a combination of regulatory, technological and investment changes. Relative trading volumes on many primary trading venues have dropped by about 50% since their peak in 2009. To ensure the investability and replicability of MSCI equity indexes, we regularly monitor the liquidity of index constituents, apply liquidity screening criteria and review index construction rules and liquidity measures. Methodology...

For the year ending December 31, 2016, we analyzed the 12-month risk forecast accuracy of four categories of simulation models available in RiskMetrics RiskManager: Monte Carlo, historical, filtered historical and weighted historical.

A year marked by Brexit and Trump is ending with widespread uncertainty.

Markets fear that a defeat of constitutional reforms proposed in Italy’s Dec. 4 referendum would end the government of Prime Minister Matteo Renzi, who has promised to resign if they fail. The reforms aim to make it easier for governments to implement their programs. A failed referendum could produce political instability, which could complicate efforts to recapitalize the country’s struggling banks, impede the government’s ability to reform the economy for the long term and increase risk...

The U.S. Securities and Exchange Commission’s new liquidity rules mark the most ambitious ever initiative against investor dilution — the unfair costs an investor may suffer when assets are not liquid enough to meet redemption requests.

Slow growth and a shortage of safe assets have led major central banks to maintain monetary policies that include short-term interest rates near or below zero. The policies, which aim to encourage businesses and consumers to borrow and spend, have lowered bond yields, distorted yield curves, shifted the composition of central banks’ balance sheets toward riskier assets and sent savers in search of yield. The persistence of low growth and a lack of inflation also have led investors to wonder...

Scenario propagation is the second stage of predictive stress testing practices, following scenario definition. This paper illustrates common pitfalls and suggests best practices for a robust propagation of the shockwave of a prospective scenario onto all relevant risk factors of a financial portfolio. The central observation: Risk managers must guard against “noise” in the predictions. Diagnostic statistics can reduce noise and ensure meaningful predictions. Key best practices include: the...

The aftermath of the 2008 global financial crisis taught the risk industry that expert judgment and economic insight may help investors anticipate and avoid exposure to major financial downturns by using forward-looking models, such as predictive stress tests. But there is no consensus on how to create these scenarios. In this paper, we portray MSCI best practices for stress testing in a flowchart that guides risk managers through a series of steps that lead to a structured way of stress...

Stress testing has experienced a resurgence of interest in the wake of the 2008 financial crisis. The lessons from that period, perhaps more than any previous one, taught the risk industry that expert judgment and economic insight may help investors anticipate and avoid exposure to major financial downturns by using forward-looking models.

For the July 2016 backtesting review, MSCI began by analyzing how each of four types of simulation models available in RiskMetrics RiskManager—Monte Carlo, historical, filtered historical and weighted historical—performed over the year ended June 30, 2016.

The decision by a majority of U.K. voters to leave the European Union shines a light on fissures between perceived winners and losers from globalized markets and highlights for investors the importance of factoring the consequences of inequality and popular discontent into their views. The latest edition of MSCI’s “Scenarios, Stress Tests and Strategies” examines the potential impacts on institutional portfolios of a tide of populist sentiment across Europe and the U.S.

For this year’s backtesting review, MSCI began by analyzing how each of four types of simulation models available in RiskMetrics RiskManager—Monte Carlo, historical, filtered historical and weighted historical—performed over the year ended December 31, 2015.

Heading into 2016, MSCI examined 12 stress points globally to be used in quantifying the effect on portfolios of a range of shifts in markets, liquidity and the macroeconomy. These stress points include the prospect of additional interest-rate hikes by the Federal Reserve, weakness in the eurozone and a deceleration in Chinese economic growth.

The persistent decline in Chinese equities and commodity prices this summer renewed investor concerns about a possible economic hard landing in the Asian giant.

The decline in Chinese equities and commodity prices this summer renewed investor concerns about a possible economic hard landing in the Asian giant. In particular, the 8.5% market plunge on August 24 spread fear into global markets that continues to this time.

Risk measures, such as Expected Shortfall and Value at Risk, are designed to calculate the risk of a portfolio. But different risk models may work better than others for different asset classes and in varying time horizons. The MSCI Model Scorecard provides an innovative tool designed to help select the best risk model in terms of Expected Shortfall (ES) and Value at Risk (VaR) predictivity.

Risk measures, such as Expected Shortfall and Value at Risk, are designed to calculate the risk of a portfolio. But different risk models may work better than others for different asset classes and in varying time horizons. The MSCI Model Scorecard provides an innovative tool designed to help select the best risk model in terms of Expected Shortfall (ES) and Value at Risk (VaR) predictivity.

Expected shortfall (ES) has attracted controversy as a measure of a portfolio’s risk since it was introduced in 2001. One reason for this was that some critics suggested ES could not be backtested. Last year, however, MSCI proposed a way of backtesting expected shortfall. This development is especially important in the light of the Basel Committee on Banking Supervision’s recent decision to adopt ES in place of VaR. The ability to backtest expected shortfall also has broader...

Stress Testing the Greek Exit Scenario Using MSCI RiskManager This Product Insight uses MSCI RiskManager to examine the potential effects of a Greek exit from the euro, explaining the detailed assumptions behind our stress test design. We make use of RiskManager's predictive stress test tool, which starts with user-defined hypothetical shocks on a few core risk factors (singled out as the drivers of the global crisis) then propagates shocks on all markets. In this current exercise, we employ...

After the global financial crisis of 2008, investors and regulators realized that liquidity risk in multi-asset class portfolios could no longer be overlooked. Too many risk models had assumed ample funding and low trading costs, which contributed to the meltdown.

When RiskMetrics, now a part of MSCI, announced Value-at-Risk (VaR) as its stated measure of risk in 1996, it initiated an industry standard for institutional risk management that was quickly adopted by the Basel Committee on Banking Supervision for its internal capital adequacy models.

In this white paper, we join the debate over Expected Shortfall versus VaR by introducing three model-independent, nonparametric back-test methodologies for Expected Shortfall, which we find more powerful than today's standard Basel VaR test. Our three Expected Shortfall back-test's generally require the storage of more information, but we find no conceptual limitations nor computational difficulties. In fact, one of the proposed back tests does not require any additional storage of data from...

This Research Insight introduces MSCI’s LiquidityMetrics, a suite of multi-asset class risk analytics for measuring and managing portfolio liquidity. The LiquidityMetrics framework is based on comprehensive descriptions of the liquidity of single assets, called Liquidity Surfaces, encompassing bid-ask spreads, market impact, trading immediacy, market depth and trading activity. In addition to position level liquidity profiling, LiquidityMetrics allows users to analyze portfolio liquidity in...

This Model Insight introduces the MSCI Bond Liquidity Measure (BLM), a model-based estimate of bond bid-ask spreads for a broad universe of quoted and non-quoted bonds. The BLM provides both a liquidity scoring metric and a way to quantify potential transaction costs. Applications of BLM include portfolio construction, risk control, risk limits, regulatory compliance, and liquidity provisioning.  Furthermore, BLM opens the way  for the consistent assessment of liquidity...