MSCI MONTHLY UPDATE
Transcript of MSCI MONTHLY UPDATE
MSCI MONTHLY UPDATE
NOVEMBER 2014
INSIDE THIS ISSUE
US Market BriefOctober volatility drives success for large cap active managers
Global Risk MonitorGlobal market volatility reaches three month high
Research SpotlightUnderstanding macroeconomic risk and its impact on asset allocation
MSCI MONTHLY MARKET VIEW2
SUPERIOR STOCK-PICKING ALLOWS FOR FURTHER DIFFERENTIATION BETWEEN TOP AND BOTTOM MANAGERS.
October marks the most volatile month
for the US equity market since 2012, as
fears of a sharp slowdown in the global
economy, particularly in Europe and
China, pushed the market lower early in
the month. However, stocks turned
sharply upward during the second half
of October as healthy third-quarter US
corporate earnings, combined with
stimulus efforts from the Bank of Japan
and the European Central Bank, helped
boost investor confidence in the US
economy. Additionally, major MSCI USA
indexes rebounded with the MSCI USA
Large Cap Index hitting its 5-year high
at the end of October (Figure 3). This
pronounced volatility resulted in market
dislocations that benefited skilled stock
pickers, in particular large-cap active
managers, who were able to further
differentiate themselves from the pack.
US MARKET BRIEFOCTOBER VOLATILITY DRIVES SUCCESS FOR LARGE CAP ACTIVE MANAGERS
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VIX levelFIGURE 1:
OCTOBER 2014 3
US MARKET BRIEF
MSCI USA Large Cap, Mid Cap and Small Cap IndexFIGURE 3:
Dispersion of active fund performanceFIGURE 2:
August ‘07
October ‘08August ‘11
April ‘14
October ‘14
October was a turbulent month for active mutual fund managers. Dispersion of active fund performance, a proxy for market shocks, reached a YTD high in October and stands out as one of the largest dispersions over the last ten years, surpassing a previous elevated dispersion of active fund performance in April of 2014 (Figure 2).
MSCI MONTHLY MARKET VIEW4
US MARKET BRIEF
Q1 Q2 Q3 October YTD
Large cap -17 -73 -133 98 -124
Large cap value -74 -59 -25 -73 -227
Large cap growth -79 -80 -33 16 -170
Small cap -36 -5 83 -158 -115
Small cap value -5 16 143 -175 -13
Small cap growth -22 -212 39 -102 -298
Total market 7 -59 -134 -73 -255
Total market value -56 -41 -145 -97 -338
Total market growth -66 -65 -83 -14 -228
Mutual fund active performance by strategy¹ (in bps)TABLE 1:
Contribution (in bps) Active exposure (% rank)
Top Bottom Top Bottom
Asset turnover 3 -7 68% 56%
Profitability -1 -13 61% 24%
Growth -2 1 57% 29%
Residual volatility 0 0 50% 41%
Sentiment 2 -2 47% 42%
Size 72 27 46% 49%
Long-term reversal 3 -13 45% 73%
Momentum 5 -2 45% 57%
Prospect -4 7 44% 59%
Leverage 2 1 43% 66%
Earnings quality 2 -2 43% 77%
Beta 4 -6 41% 55%
Value -1 -2 37% 74%
Liquidity 25 10 35% 45%
Top Bottom Difference
Active return 307 -200 507
Investment styles 114 -9 123
Industries 26 -34 60
Stock specific 170 -156 326
Investment style decompositionLarge cap top vs bottom mutual fund attribution (in bps)TABLE 2:
Market dislocation allowed top managers to further differentiate themselves from the bottom ones as stock specific returns accounted for 326 bps of differences for October, indicating superior stock-picking skills of the top managers. Investment styles continued to be a meaningful portion of the return difference this month with 123 bps in contribution (Table 2).
1 YTD Performance is calculated as of October 31, 2014.
Large cap managers recouped some of their losses from previous quarters, outperforming their benchmarks by 98bps in October. On the other hand, small cap managers experienced one of their worst months, bringing their YTD performance into a negative territory (Table 1).
OCTOBER 2014 5
US MARKET BRIEF
US Total MarketFIGURE 4: Difference
Total market Small cap
August September October August September October
Prospect 0.6 0.6 1.9 0.1 1.8 0.5
Industry momentum 1.1 0.8 1.4 (1.6) 0.6 0.8
Asset turnover (0.2) 1.7 1.0 1.0 1.7 1.1
Profitability (0.6) (0.4) 0.7 0.5 0.5 1.3
Short-term reversal (0.2) (2.9) 0.5 (0.2) (2.2) 0.7
Value (0.3) (1.4) 0.4 0.1 (2.7) (0.4)
Sentiment 1.1 (0.5) 0.3 1.5 0.4 0.7
Beta (0.1) (1.4) 0.2 0.2 (1.3) 0.3
Momentum 0.6 1.7 0.1 0.9 1.8 (0.1)
Residual volatility (0.1) (0.4) (0.1) (2.5) (0.6) (2.2)
Growth (0.4) 1.7 (0.3) 0.3 1.2 (0.1)
Leverage (0.1) (2.1) (0.8) (0.9) (2.3) (1.8)
Earnings quality (0.8) 1.6 (1.0) 1.0 1.4 2.1
Size (0.2) 2.7 (1.8) (1.1) 1.1 (0.9)
Liquidity 1.9 (0.5) (2.3) 4.5 (1.9) (0.9)
Long-term reversal (2.5) (0.6) (2.5) (1.7) (1.2) (1.3)
Seasonality 1.9 (0.7) (2.5) 0.1 0.2 (1.0)
Relative performance of growth-oriented styles and quality-oriented styles exhibited “two regimes” in October. Growth-oriented styles underperformed significantly against quality-oriented styles in the first half of the month but recouped most of the underperformance because of a rebound in Momentum and Beta and a decline in Size (Figure 4 and Table 3).
A few factors have experienced outperformance for the past three months, including Prospect and Industry Momentum in total market cap and Asset Turnover, Profitability and Earnings Quality in Small Cap.
Risk-adjusted performance of selected investment styles¹TABLE 3:
MSCI MONTHLY MARKET VIEW6
US MARKET BRIEF
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Prospect 0.3 1.5 2.1 0.9 1.6 (0.8) 2.5 (2.7) (0.6) 1.9
Industry momentum (0.1) (0.0) 0.3 1.8 1.0 0.1 0.4 2.3 1.2 (0.3)
Asset turnover 1.8 0.4 (0.4) (0.3) (1.1) (0.2) 0.7 (0.1) (0.8) 0.7
Profitability 0.4 2.2 0.8 1.3 0.6 0.5 0.8 1.3 2.0 0.3
Short-term reversal 2.2 (0.1) 0.8 0.7 0.5 0.7 (0.9) 0.0 0.9 (0.3)
Value 0.6 0.6 0.9 (0.6) (0.3) 0.5 (0.8) 0.1 0.4 0.4
Sentiment 0.3 1.7 1.3 (0.3) 0.7 1.0 0.0 (0.5) (0.3) (0.4)
Beta 0.2 0.7 (1.0) 0.2 0.7 0.4 0.4 0.8 0.0 (1.1)
Momentum 0.4 0.1 0.5 0.8 1.5 (0.2) 0.1 (1.0) (0.1) (0.4)
Residual volatility 0.5 0.5 1.1 (0.0) (0.3) 0.3 (0.8) (1.3) (1.1) (0.6)
Growth 0.4 1.2 0.6 (0.9) (0.2) (1.9) 0.3 (0.7) (1.8) (1.8)
Leverage 0.5 (0.8) (1.3) (0.2) (0.2) (1.2) (1.3) (0.3) (0.5) 0.3
Earnings quality (0.6) 1.4 0.9 0.1 (0.9) (0.1) 0.1 0.0 (1.7) (2.5)
Size (2.1) (0.9) (2.2) (2.3) (1.7) (1.4) (2.3) (0.9) (1.9) (0.9)
Liquidity (3.0) (1.9) (1.3) (1.7) (1.4) (2.6) (1.5) (1.4) (1.7) (1.1)
Long-term reversal (1.0) (0.3) (1.1) (0.3) (0.8) (1.4) (1.1) 1.9 (0.7) (2.1)
Seasonality (0.3) (1.9) (0.4) (1.2) (1.0) (0.3) (1.2) (2.0) (0.3) (1.1)
Investment style risk-adjusted performance by sector (October 01 through October 31, 2014.)TABLE 4:
The outperformance of the Prospect factor in both total and small cap space indicates that investors have likely unwound their popular trades during the month (stocks that experienced large positive returns over the last 3-5 years) to avoid being caught during the market downturn. The unwinding was especially pronounced in IT, Utilities and Energy sectors (Table 3 and Table 4).
Quality-oriented styles such as Asset Turnover, Profitability and Earnings Quality performed well for the month in both total market and small cap space with the exception of performance of Earnings Quality in the total market space. Interestingly, Profitability and Size factors had consistent performance across all sectors (Table 4).
While highly profitable companies have outperformed across all sectors, small cap names outperformed their large cap peers across all sectors. The consistent outperformance of the small cap stocks across sectors may be a result of their smaller exposure to regions with weak macroeconomic data (Europe, Japan and EM) and continued solid US corporate earnings (Table 4).
OCTOBER 2014 7
US MARKET BRIEF
Leverage factor underperformed in both total market and small cap space for the third month in a row. Especially in small cap space, leverage was the second worst performer in October (Table 3). The longer-term trend indicates that since mid-July, investors have been avoiding highly-levered companies, reflecting on-going concerns of the timing of the interest rate hike (Figure 5).
LeverageFIGURE 5:
Ting FangVice PresidentClient Consultant
Ting's responsibilities include client education & training, product implementation & on-boarding, as well as custom-projects design & execution based on client’s specific needs and objectives. Ting holds an MBA from Fordham University in New York.
Mehmet BayraktarManaging DirectorEquity Analytics Research
Mehmet is responsible for driving the research agenda for Barra Equity Models globally. Prior to MSCI he was Head of Research and Chief Economist at IS Asset Management, the largest asset management firm in Turkey. Before IS Asset Management, Mehmet was the lead portfolio manager for European and UK quant equity portfolios and the GS Dynamic Asset Allocation Fund in the Quantitative Investment Strategies group at Goldman Sachs Asset Management. He holds an MBA and MSc in Finance and Economics from the University of Chicago and London School of Economics and Political Science respectively.
ABOUT THE AUTHORS
Stanislav RadchenkoExecutive DirectorEquity Analytics Research
Stan is a Senior Researcher focused on exploring Systematic Equity Strategy (SES) factors in risk models, building new sector models and establishing macro linkages in equities. Prior to MSCI, he was co-head of research and lead portfolio manager for the US equity funds at Quantitative Investment Strategies group at Goldman Sachs Asset Management. He began his career as an assistant professor at University of North Carolina teaching econometrics. Stan holds a Phd in Economics from Rutgers University.
MSCI MONTHLY MARKET VIEW8
GLOBAL RISK MONITOROCTOBER 2014
GLOBAL MARKET VOLATILITY REACHES THREE MONTH HIGH
October 2014 saw more turbulence than the previous two
months. For the risk factors monitored, we observed 33 return
exceedances, versus 21 in September and 8 in August (see
Figure 1). All risk factors reached their three-month high
volatility and some risk factors hit a one-year high volatility (see
Tables 1 and 2). However, though we saw increased volatility
levels in October, there were no obvious events that caused the
volatility outbreak — as opposed to July 17, 2014 when
Malaysian passenger jet crashed in Ukraine, leading to a high
number of exceedances for that date (see Figure 1).
Taking a closer look at the S&P500, we saw the ratio of implied
volatility (VIX) to reactive historical volatility estimate increase at
the beginning of October 2014, and decrease below its long term
average toward the end of the month (see Figure 2). In fact, the
S&P500 was swung up and down on October 7, 8, and 9, causing
the historical volatility to increase. In reaction, implied volatility
increased sharply during these days (Figure 3). A few days later,
however, the implied volatility returned to its initial level. Since
10/17/2014, no further major outbreaks of implied volatility have
been observed, and the S&P500 has been gaining in value.
Daily returns exceeding two times forecast volatilityFIGURE 1:
RISK FACTOR SURPRISE DAYS
Date range: May 01, 2014 to October 31, 2014
OCTOBER 2014 9
SOURCE Prior month¹ Prior 3 months² Prior year³
Return Avg. vol. Min. vol. Max. vol. Return Avg. vol. Min. vol. Max. vol. Return Avg. vol. Min. vol. Max. vol.
US govt 2Y -7.43 2.32 2.04 2.54 -3.51 2.05 1.81 2.54 18.67 1.80 1.36 2.54
US govt 10Y -14.56 3.99 3.76 4.17 -23.87 3.79 3.51 4.17 -27.81 4.13 3.43 5.39
EUR govt 2Y 1.79 1.17 1.08 1.28 -9.56 1.16 1.05 1.28 -19.52 1.54 1.05 2.17
US 3m Eurodollar Fut 3m
-1.01 0.40 0.32 0.45 -0.95 0.31 0.24 0.45 -1.69 0.38 0.23 0.75
Risk forecast of daily absolute changes in rates (bps) over prior month, prior three months, and prior year (decay = 0.97)TABLE 1:
FORECAST VOLATILITYVOLATILITY STATS FOR EWMA (DECAY FACTOR OF 0.97)
1 Prior month date range: October 01, 2014 - October 31, 2014. 2 3 month date range: August 01, 2014 - October 31, 2014. 3 One year date range: November 01, 2013 - October 31, 2014 Highlighted prior month volatilities indicate that the volatility level reached its minimum/maximum value of the last three months or twelve months. The relevant three-month/ twelve-month minimum/maximum values are highlighted as well.
The US 2Y and 10Y government yields, investment grade and high yield credit spreads, VIX, and WTI decreased over the month. All these risk factors, except for the US 10Y government yield, reached a one-year high volatility (see Tables 1 and 2).
GLOBAL RISK MONITOR
SOURCE Prior month¹ Prior 3 months² Prior year³
Return Avg. vol. Min. vol. Max. vol. Return Avg. vol. Min. vol. Max. vol. Return Avg. vol. Min. vol. Max. vol.
CDX NAIG OTR -1.04% 2.86% 2.51% 3.00% -0.77% 2.50% 2.13% 3.00% -12.49% 2.12% 1.52% 3.00%
CDX NAHY OTR -3.32% 2.41% 2.05% 2.57% -0.25% 2.12% 1.79% 2.57% -2.90% 1.88% 1.44% 2.57%
EUR/USD -0.82% 0.38% 0.31% 0.42% -6.36% 0.31% 0.23% 0.42% -7.84% 0.34% 0.23% 0.50%
MSCI USA 2.29% 0.80% 0.61% 0.90% 4.35% 0.65% 0.50% 0.90% 14.65% 0.65% 0.49% 0.90%
MSCI EM 1.07% 0.71% 0.63% 0.76% -4.66% 0.61% 0.51% 0.76% -1.77% 0.68% 0.47% 0.89%
Eurodollar 3m Vol 27.94% 6.10% 5.34% 6.84% 23.62% 5.75% 4.74% 6.84% -6.45% 6.05% 4.67% 8.22%
VIX -13.98% 8.24% 6.64% 9.28% -17.23% 7.33% 5.87% 9.28% 2.04% 6.39% 4.82% 9.28%
WTI 1m -11.41% 1.33% 1.20% 1.44% -17.75% 1.11% 0.79% 1.44% -16.58% 0.99% 0.71% 1.44%
Risk forecast of daily relative (log) changes over prior month, prior three months, and prior year (decay = 0.97)TABLE 2:
1 Prior month date range: October 01, 2014 - October 31, 20142 3 month date range: August 01, 2014 - October 31, 20143 One year date range: November 01, 2013 - October 31, 2014
The MSCI USA Index was particularly sensitive to market turbulence in October, resulting in its highest volatility of the past year and experiencing four negative and two positive return exceedances. Despite this, the MSCI USA Index gained 2.29 percent over the month of October (see Table 2).
MSCI MONTHLY MARKET VIEW10
This figure shows the ratio of VIX to Historical Volatility as well as the ratio of Long-Term VIX to historical volatility. In the first ratio historical volatility is calculated using an exponentially weighted moving average (EWMA) with a decay factor of 0.97. In the second ratio, Long-Term VIX is the 252 days moving average of the VIX and Long-Term Historical Volatility of the S&P500 is the equally weighted historical volatility of S&P500 returns over the same time.
CDX NAIG OTR
Five-year North American Investment Grade CDS Index Spread Level, constructed by MSCI using the most liquid five-year North American Investment Grade CDS Index and smoothed over a period when a new series becomes on-the-run.
CDX NAHY OTR
Five-year North American High Yield CDS Index Spread Level, constructed by MSCI using the most liquid five-year North American High Yield CDS Index and smoothed over a period when a new series becomes on-the-run.
EUR two-year government bond
Euro government two-year Zero Rate, constructed by MSCI from on-the-run German Bunds.
EUR/USD
Mid quote for EUR/USD Foreign Exchange Rate snapped at 1100 EST. Appears in the report each month
Eurodollar three-month volatility
Implied volatility time series of three months at-the-money options on Eurodollar interest rate futures.
Europe two-year government bond
Euro two-year Zero Rate, constructed by MSCI from on-the-run German Treasury bonds..
MSCI emerging market index
Time series of MSCI Emerging Market Equity Index using end-of-day closing prices.
MSCI EM Europe Index in EUR
The MSCI Emerging Market Europe equity index using end-of-day closing prices quoted in Euros.
MSCI USA Index
Time series of MSCI USA equity index using end-of-day closing prices.
US 10-year government bond
US Government 10-Year Zero Rate, constructed by MSCI from on-the-run US Treasury bonds.
US three-month Eurodollar Futures three-month rate
Interest rate of three-month interest rate futures calculated by MSCI based on CME Eurodollar futures quotes on three-month deposits.
US two-year government bond
US Government Two-Year Zero Rate, constructed by MSCI from on-the-run US Treasury bonds.
VIX
Time series of the CBOE Market Volatility Index using end-of-day closing prices.
WTI
One-Month Crude Oil: One-Month CME light sweet crude oil time series. One-Month tenor constructed as a Constant Maturity Future time series by interpolating the first two nearterm CL futures contracts.
GLOBAL RISK MONITOR
RISK FACTOR DEFINITIONS
FIGURE 3: EVOLUTION OF IMPLIED AND HISTORICAL VOLATILITY OF S&P500 INDEX THROUGHOUT THE YEAR
This figure compares the implied volatility of the S&P 500 (VIX) to an EWMA volatility estimate with a decay factor of 0.07.
FIGURE 2: RATIO OF IMPLIED VOLATILITY TO HISTORICAL VOLATILITY OF THE S&P500 INDEX
VIX toHistorical volatility
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S&P500Index
OCTOBER 2014 11
UNDERSTANDING MACROECONOMIC RISK AND ITS IMPACT ON ASSET ALLOCATION
Visit msci.com/resources/research_papers
KEY BENEFITS OF MSCI MACROECONOMIC RISK MODELING
n Connects asset allocation strategies to investor views of the economy
n Models the relationship of macroeconomic events to asset prices
n Allows investors to evaluate the likelihood of emerging macroeconomic trends, which enables more responsive asset
allocation tactics
n Accounts for horizon in the investment decision process, informing strategies for the management of long-term risk
n Provides an economic rationale for risk factor premia, using macro risk factors to model expected cash flows and
discount rates
Since 2009, many institutional investors have introduced
macroeconomic scenarios in their asset allocation process.
The 2008 global financial crisis has proven to have a
long tail, and investors want to manage the risks raised
by macroeconomic events with an eye on long horizon
investments.
Economic growth (real GDP) and inflation are the key
macroeconomic drivers of asset returns with their impact
apparent only over long horizons. And what about drivers
of risk? MSCI defines macroeconomic risk as the change
in asset value due to persistent shocks to the real economy
(meaning growth and inflation).
Using a set of new models, MSCI can forecast the long-term
impact of macroeconomic shocks on asset prices, examining
those prices relative to asset cash flows and discount factors.
In this Research Spotlight, we have compiled a short guide to
all white papers published on Macroeconomic Risk. For each
paper, you will find the full title, the credited authors, a short
abstract, and a quick hyperlink to the full publication.
Starting in 2012, MSCI Research began exploring the
impact of macroeconomic events on asset valuation and
strategic asset allocation. The white papers summarized
in this Research Spotlight explain the core findings in a
continuing series, and are the basis of our growing suite of
‘macro models.’ Based on this innovative research, MSCI
offers Macroeconomic Consulting for institutional investors
interested in a macro framework for portfolio construction.
MSCI MONTHLY MARKET VIEW12
UNDERSTANDING MACROECONOMIC RISK AND ITS IMPACT ON ASSET ALLOCATION
OCTOBER 2012RISK MANAGEMENT AND MACROECONOMIC UNCERTAINTY: SHORT-TERM CONSEQUENCES OF LONG-TERM RISK
Kurt Winkelmann
During a strong global equity market in 2012, the daily VIX
suggested that risk levels were declining, while estimates of
equity risk premia indicated higher levels of uncertainty. In
this paper, first in a series on macroeconomic themes, we
explore reasons for these mixed signals and examine the
various challenges of measuring risk. We propose that many
risk management issues can be addressed by understanding
the drivers of asset valuation.
READ MORE OR GO TO MSCI.COM TO DOWNLOAD
NOVEMBER 2012MACRO-SENSITIVE PORTFOLIO STRATEGIES: HOW WE DEFINE MACROECONOMIC RISK
Kurt Winkelmann, Ludger Hentschel, Raghu Suryanarayanan and Katalin Varga
Macro-sensitive portfolio strategies rely on how we measure
the relationship between asset prices and macroeconomic
risk. In this paper, we define macroeconomic risk as the
change in asset value due to persistent shocks to real
economic growth. How might investors allocate assets in
response to large macroeconomic shocks? We return to
the basics of asset pricing and analyze the impact of macro
shocks on both asset cash flows and discount factors.
READ MORE OR GO TO MSCI.COM TO DOWNLOAD
MARCH 2013MACRO-SENSITIVE PORTFOLIO STRATEGIES: MACROECONOMIC RISK AND ASSET CASH-FLOWS
Kurt Winkelmann, Raghu Suryanarayanan, Ludger Hentschel and Katalin Varga
We find that cash flows earned by different equity portfolios
can respond differently to persistent macroeconomic shocks
to real output, with results emerging over longer horizons.
Portfolios with cash flows that exhibit a greater long-run
response to macro shocks can command a higher expected
return over time, which is compensation for risk – in this case,
the risk of a persistent shock to trend growth in real GDP.
READ MORE OR GO TO MSCI.COM TO DOWNLOAD
APRIL 2013MACRO-SENSITIVE PORTFOLIO STRATEGIES: PRICING AND ANALYZING MACRO RISK
Kurt Winkelmann, Raghu Suryanarayanan, Ludger
Hentschel and Katalin Varga
Previous papers in this series show that cash flow betas
relative to economic growth vary by asset class and portfolio
type. In this paper, we show that assets with higher cash
flow betas receive a higher long-term return, which is
compensation for the macro risk exposure. We find that long-
term portfolio risk can be attributed to persistent shocks to
real GDP and inflation, demonstrating that portfolios tilted
towards risk premium strategies receive a higher return than
the market portfolio.
READ MORE OR GO TO MSCI.COM TO DOWNLOAD
JUNE 2013MACRO RISK AND STRATEGIC ASSET ALLOCATION: DECONSTRUCTING RISK PARITY PORTFOLIOS
Kurt Winkelmann, Raghu Suryanarayanan, Ludger Hentschel and Katalin Varga
In previous papers, we show how portfolio returns vary in
correlation to macroeconomic shocks, implying that “high cash
flow beta” assets receive a premium. In this paper, we apply
the same framework to strategic asset allocation, analyzing
a risk-parity portfolio. We conclude with a methodology for
designing and testing macroeconomic shocks.
READ MORE OR GO TO MSCI.COM TO DOWNLOAD
OCTOBER 2014 13
UNDERSTANDING MACROECONOMIC RISK AND ITS IMPACT ON ASSET ALLOCATION
If you’d like to read more about any of these subjects, please visit msci.com/resources/research_papers for the full versions of these research papers.
SEPTEMBER 2014CHINA: HARD LANDING OR GENTLE DESCENT?
Kurt Winkelmann, Raghu Suryanarayanan, Katalin Varga and Jahiz Barlas
With global investors concerned about an imminent hard
landing in China’s economy (and its potential long-term
effects global growth and global equity returns), we employed
the MSCI Macroeconomic Model to examine the factors
driving this possible event. Our model indicates that an
imminent hard landing in China is unlikely, since GDP growth
in China could meet the official target of 7.5 percent by
the end of 2014; moreover, the MSCI Asset Pricing Model
indicates that Chinese real growth risk is a small contributor
to long-term global equity risk.
READ MORE OR GO TO MSCI.COM TO DOWNLOAD
NOVEMBER 2013THE END OF QUANTITATIVE EASING: TAPERING AND ITS
EFFECT ON BONDS AND EQUITIES
Attila Agod, Ludger Hentschel, Raghu Suryanarayanan and
Kurt Winkelmann
In late 2013, investors remained uncertain about the tapering
of the Fed’s quantitative easing policy. Using the MSCI
Macroeconomic Model, we explore how evolving economic
conditions might motivate the Fed to start tapering. We
combine this analysis with the Barra Integrated Model to
test how economic improvements and tapering might impact
stock and bond markets.
READ MORE OR GO TO MSCI.COM TO DOWNLOAD
APRIL 2014INDEX PERFORMANCE IN CHANGING ECONOMIC ENVIRONMENTS: A MACROECONOMIC FRAMEWORK
Abhishek Gupta, Altaf Kassam, Raghu Suryanarayanan and
Katalin Varga
After the turmoil of 2008, institutional investors started
accounting for macroeconomic conditions in their asset
allocation decisions. For investors designing macro-sensitive
portfolios, this paper offers a framework based on 40+ years of
MSCI Factor and Sector Index history, plus long-term analysis
based on forecasts from the MSCI Macroeconomic and Asset
Pricing Models. We model historically plausible growth and
inflation regimes and show how our factor and sector indexes
differ in their response to changes in these regimes.
READ MORE OR GO TO MSCI.COM TO DOWNLOAD
UPCOMING RESEARCHFROM MSCI
n “Dynamic Allocation to Factor Indexes: Framework and Implementation”
n “Factoring’ in the Emerging Markets Premium. Exploring Factor Indexes in Emerging Markets”
n “Application of Regulatory Stress Scenarios: CCAR”
n “Predictive Stress Test Diagnostics: Methodology and Use Cases”
MSCI MONTHLY MARKET VIEW14
MSCI WOMEN’S LEADERSHIP FORUM
New York
MSCI NORDIC RESEARCH CONFERENCE
Stockholm
MSCI PORTFOLIO MANAGEMENT RESEARCH SEMINAR SERIES
Kansas City
MSCI ASIA PACIFIC ASSET OWNER SUMMIT
Tokyo
We are pleased to invite you to the MSCI Women’s Leadership Forum featuring celebrated World Cup Soccer Star, Brandi Chastain.
Brandi will lead a discussion over lunch in the boardroom. She will discuss the importance of developing leadership skills, finding --and becoming-- role models and giving back to one's team and community. She will offer a blueprint on how to play fair, win (and lose) with grace, and above all, how to have a good time doing it.
MSCI will be hosting a one day seminar where senior executives from MSCI research along with industry practitioners will present and discuss the latest thinking on factor investing in the context of sustainable investments and asset allocation to the private assets looking at these effects from both a short and long term horizon.
Gain insight from MSCI’s latest research and see how this is driving innovations designed to help you stay on the leading edge.
Topics:
The Need for Innovation: Navigating the Changing Investment Landscape
It’s all about factors: Introducing the New US Equity Model Series
This is a unique opportunity to exchange ideas with MSCI’s Asia Pacific Asset Owner community. The audience this year will be comprised of representatives from MSCI’s Asia Pacific client base ranging from senior levels of management, including C-level representation, to ensure the discussions will have the scope and depth with key learnings. The Summit topics will engage delegates in exchanges on current concerns affecting investment and risk management of the APAC asset owner community
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EVENTS NOVEMBER
2014
I GET A LOT OUT OF THE MSCI EVENTS. THERE ARE ALWAYS NEW IDEAS AROUND COMPLEX TOPICS AND I GET TO MEET MY PEERS. WHAT I ENJOY THE MOST IS THE SHARING OF IDEAS.
Dr Don HansonManaging DirectorPlato Investment Management
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OCTOBER 2014 15
EVENTS NOVEMBER
2014
NEW INNOVATION FROM MSCI
Barra Models Joining the expansive lineup of MSCI’s market-leading Barra equity models, the new Barra US Total Market Model, Barra Asia-Pacific Equity Model and Barra China International Equity Model have been enhanced to include Systematic Equity Strategies. These models represent a new era of tools that contribute towards advancing the standard for measuring and managing risk.
Barra US Total Market Model
Key features include:
Enhanced existing style factors based on Systematic Equity Strategies and introduces new factors based on News Sentiment, Implied Volatility and Short Interest.
n Premier datasets from MSCI’s comprehensive database and additional leading quantitative data sources.
n Multiple models with factor sets and responsiveness aligned with different investment horizons and strategies ranging from portfolio construction to trading.
n Deep daily history back to the 1970s.
Barra Asia-Pacific Equity Model and Barra China International Equity
Key features include:
n Style factors based on Systematic Equity Strategies using data from leading vendors.
n Dual factor structure that captures the unique dynamics of Asia ex-Japan and Japan.
n Full daily model updates, Volatility Regime Adjustment and Optimization Bias Adjustment.
n History back to January 1995.
Launching a series of Asian single-country models leveraging the regional model’s innovations and factor set:
n China International (ex-China A)/Hong Kong
n Taiwan
n India
n Malaysia
n Thailand
Barra Portfolio Manager We continue to add new functionality to this powerful portfolio construction tool designed to streamline the workflow of any investment process. Enhancements include:
n New High Volume Reporting allows for end –to-end reporting using pre-generated or customized reports.
n Inclusion of the latest version of the Barra’ Optimizer - Open Optimizer 8.0. Packed with new functionality, this powerful optimizer engine now includes Constraint-Aware Roundlotting, Risk Parity Portfolio Construction and Transaction Cost Control.
n The ability to customize new factor structures of risk models that match your own investment philosophy.
n Access to the full history of Barra global and regional risk models, including our flagship Barra Global Equity.
n Model, Barra European Equity Model, Barra Asia-Pacific Equity Model and new Barra US Equity Model.
Barra Integrated Model BIM analyses individual markets to uncover the local factors that drive risk in that market. New features include:
n New local F1 Models for China Offshore and Nigeria – new fixed income models expand coverage to include bonds from the China offshore and Nigerian markets.
n Updated local F1 models for the Philippines, Taiwan and Thailand – these fixed income models use the latest curve methodology including a switch to a government bond-based model for the Government STBs and basing the Swap Spread STB factors on the local swap curve.
n Updated and Enhanced Equity Implied Volatility model – expanded coverage includes eight additional markets.
BarraOne A new version of our global, multi-asset platform for total plan risk and performance is now available.
New features include:
n BIM303: The next generation Barra Integrated Models with updated equity and fixed income models, expanded equity coverage and longer history for the latest alternative models.
n Workflow improvements: A series of enhancements to simplify common user workflows, including simplifying the Macro Factor workflow.
n OIS coverage enhancements: Delivery of full OIS curves and removal of current restrictions on OIS modelling.
n Increased structured product coverage: handling of multi-currency structured products modelled with Intex cash flows.
MSCI MONTHLY MARKET VIEW16
RiskMetrics CreditManager Designed to relieve clients from the burden of data collections and operations, this latest release comes with a host of new features including:
n A more intuitive navigation structure and layout with advanced searching and sorting capabilities to speed up searching in large data tables such as obligors, exposures or market data.
n An enhancement to the Asset-Based Rule for estimating R-Squared for unlisted obligors that enables clients to define additional rule parameters at the obligor level. A Research Technical Note explains the enhanced rule and provides recommendations for its configuration on country and industry levels.
n A new Pricing Diagnostic Report which includes Zero Coupon Bonds and Book Mode.
Performance Analytics We continue to add to our suite of performance attribution models that help clients identify sources of portfolio performance and make more informed investment decisions. New features include:
n Multi-Asset Class Performance Attribution: A dedicated Multi-Asset Class attribution model with flexible multi-asset class grouping.
n Fixed Income Performance Attribution Model: Improved spread return calculation, Multi-level grouping to slice and dice results and for the spread attribution to match the investment process.
n Alignment with risk analysis in BarraOne : User-imported FX Rate functionality, Specified Base Value can now be utilized in Performance Analytics, Improved Visualization, Daily Performance dashboards with flexibly defined dashboards, Multi-Asset Class attribution dashboards introduced, Nested attribution dashboards for traditional and cascading Allocation-Selection attribution, Top/bottom charts for both assets and factors in Factor-Based attribution, Multi-level dashboards for Fixed Income Attribution, Deeper analysis of term structure and spread management decisions in the Fixed Income Attribution dashboards.
New MSCI Factor Indexes MSCI Factor Indexes are rules-based indexes that capture the returns of systematic factors that have historically earned a persistent premium over long periods of time- such as Value, Low Size, Low Volatility, High Yield, Quality and Momentum.
The new MSCI Core Real Estate Factor Indexes seek to reflect the performance characteristics of a range of investment styles and strategies in the listed real estate space (such as small size, volatility and high yield) using transparent and rules-based methodologies. These indexes often use weighting methods other than market capitalization.
MSCI Core Real Estate and Core Real Estate Factor Indexes:
The MSCI Core Real Estate Indexes, based on the MSCI ACWI Investable Market Indexes (IMI) (the "Parent Index"), are designed to reflect the performance of stocks in the Parent Index engaged in the ownership, development and management of specific core property type real estate. Specifically, these indexes exclude companies, such as real estate services and real estate financing companies, that do not own properties.
MSCI Equal Sector Weighted Indexes
These indexes re-weight GICS sectors equally at each index rebalance. Between rebalances, however, sector weights will fluctuate based on their relative performance (as determined by the sector's constituents). As MSCI Equal Sector Weighted Indexes assign equal weights to each sector (unlike traditional market cap weighted indexes), this approach may result in avoiding potential sector concentration.
MSCI Liquid Real Estate Indexes
The MSCI Liquid Real Estate Indexes, based on the MSCI ACWI IMI Index, are constructed by combining MSCI Core Real Estate Volatility Tilt Indexes and Markit iBoxx inflation-linked Indexes. This combination of indexes aims to deleverage the listed real estate index in order to reduce the impact of leverage used by listed real estate companies on the return and achieve a risk/return profile closer to the unlevered return on underlying properties.
MSCI World Low Carbon Leaders Index:
The MSCI Global Low Carbon Leaders Indexes address two dimensions of carbon exposure - carbon emissions and fossil fuel reserves - providing benchmarks for portfolios limiting exposure to carbon risk. The indexes also aim to minimize tracking error to the underlying free float market capitalization weighted Parent Indexes in order to maintain risk and return characteristics similar to the Parent Indexes. The MSCI Global Low Carbon Leaders Indexes utilize MSCI ESG CarbonMetrics data from MSCI ESG Research Inc.
1 95 of the top 100 investment managers in the world are MSCI clients [Based on P&I AUM data as of December 2013 and internal MSCI data as of September 2014]. 2 Over USD $9.5 trillion in assets is estimated to be benchmarked to MSCI indexes [As of March 31, 2014, as reported in June 2014, by eVestment, Lipper and Bloomberg]. 3 40 of the top 100 hedge funds use RiskManager [Based on ‘The Hedge Fund 100” from Institutional Investor in June 2014 and internal MSCI data as of June 2014]. 4 10 of the top 10 global asset managers are MSCI clients [Based on P&I and MSCI data, as of September 2013. 5 HedgePlatform is now used by over 50 fund of funds, including 17 of the largest 20 [“The Hedge Fund 100Institutional Investor, , June 2014.] 6 IPD delivers over 200 Indexes each year in 30+ countries [As verified by IPD research, www.ipd.com]. 7 5,000 asset owners use InvestorForce to power their performance measurement and reporting. 8 800 clients with $15 trillion in AUM depend on MSCI ESG Research. The information contained herein (the “Information”) may not be reproduced or redisseminated in whole or in part without prior written permission from MSCI. The Information may not be used to verify or correct other data, to create indexes, risk models, or analytics, or in connection with issuing, offering, sponsoring, managing or marketing any securities, portfolios, financial products or other investment vehicles. Historical data and analysis should not be taken as an indication or guarantee of any future performance, analysis, forecast or prediction. None of the Information or MSCI index or other product or service constitutes an offer to buy or sell, or a promotion or recommendation of, any security, financial instrument or product or trading strategy. Further, none of the Information or any MSCI index is intended to constitute investment advice or a recommendation to make (or refrain from making) any kind of investment decision and may not be relied on as such. The Information is provided “as is” and the user of the Information assumes the entire risk of any use it may make or permit to be made of the Information. NONE OF MSCI INC. OR ANY OF ITS SUBSIDIARIES OR ITS OR THEIR DIRECT OR INDIRECT SUPPLIERS OR ANY THIRD PARTY INVOLVED IN THE MAKING OR COMPILING OF THE INFORMATION (EACH, AN “MSCI PARTY”) MAKES ANY WARRANTIES OR REPRESENTATIONS AND, TO THE MAXIMUM EXTENT PERMITTED BY LAW, EACH MSCI PARTY HEREBY EXPRESSLY DISCLAIMS ALL IMPLIED WARRANTIES, INCLUDING WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. WITHOUT LIMITING ANY OF THE FOREGOING AND TO THE MAXIMUM EXTENT PERMITTED BY LAW, IN NO EVENT SHALL ANY OF THE MSCI PARTIES HAVE ANY LIABILITY REGARDING ANY OF THE INFORMATION FOR ANY DIRECT, INDIRECT, SPECIAL, PUNITIVE, CONSEQUENTIAL (INCLUDING LOST PROFITS) OR ANY OTHER DAMAGES EVEN IF NOTIFIED OF THE POSSIBILITY OF SUCH DAMAGES. The foregoing shall not exclude or limit any liability that may not by applicable law be excluded or limited.
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Risk and Peformance:msci.com/products/risk_management_analytics
msci.com
MSCI is a leading provider of investment decision support tools to over 6,000 clients worldwide, ranging from large pension to boutique hedge funds. We offer a range of products and services – including indexes, portfolio risk and performance analytics, and ESG data and research – from a number of internationally recognized brands such as Barra, RiskMetrics and IPD. Located in 23 countries around the world, and with over 2,600 employees, MSCI is dedicated to supporting the increasingly complex needs of the investment community with groundbreaking new products, high quality data, superior distribution and dedicated client support.
INDEXES
MSCI has been at the forefront of index construction and maintenance for more than 40 years, launching its first global equity indexes in 1969. Today, MSCI offers a family of more than 160,000 consistent and comparable indexes which are used by investors around the world to develop and benchmark their global equity portfolios.
PORTFOLIO CONSTRUCTION
Equity and multi-asset class portfolio analytics products help asset managers and owners measure, manage, and optimize their risk and performance across multiple portfolios. Robust analytics are powered by the range of
equity, fixed income, derivative and alternative investment risk and return attribution models.
RISK AND PERFORMANCE
Multi-asset, position-based risk and wealth management products and reporting services enable clients to measure and quantify portfolio risk across security types, geographies and markets. MSCI's offering is well known for its Value at Risk methodologies, as well as being a leading provider of credit liquidity and counterparty risk systems.
ABOUT MSCI
95
investment managers in the world are MSCI clients.1
100of the top 75
global asset managers are MSCI clients.3
100of the top
10
global asset managers are MSCI clients.6
10of the top40
hedge funds use RiskManager.4
100of the top
170
IPD delivers over
indexes each yearin
30+ countries.7
600
$15 trillion clients with
in assets under management depend on MSCI ESG Research.5
$9.5 trillion Over
in assets is estimated to be benchmarked to MSCI indexes.2
4,500InvestorForceto power their performance measurement and reporting.8
asset owners use
MSCI IN NUMBERS