Excellence. Responsibility. Innovation. Q2 216 Hermes Investment Office Market Risk Insights Each social formation, through each of its material activities, exerts its influence upon the civic whole; and each of its ideas and ideals wins also its place and power. Patrick Geddes sociologist and urban planner In our second Market Risk Insights of 216, we again try to add some colour to the current environment. The markets were skittish in the first quarter, as we predicted. Even the sociologist quoted above, as familiar as he was with human interaction, would have been shocked by the speed with which the mood of the market changed, seemingly much faster than in the past. Oil alone fell nearly 3%, rallied some 27%, dropped over 22%, recovered almost 6%, before falling a final 8%; an exhausting time for market observers. Oil volatility spiked 81% by mid-february, while collapsing back below its starting level of 48% towards the end of the quarter. But it wasn t just oil, all risky assets were chucked about. This makes it even more challenging for investors and fund managers to navigate the markets. We cannot underestimate the risks of real-world scenarios. But as investors we must bear some risk in order to generate returns, and must broaden and deepen our understanding of risk beyond traditional measures to capture the full picture. Figure 1: Oil: price v volatility 5 45 1 9 Risk is best considered a multi-headed hydra, one that changes shape dramatically through time depending on market conditions. As such, understanding the impact of market risks requires close analysis of the risks at hand. Oil price 4 35 3 25 2 31 Dec 15 14 Jan 16 Oil price (LHS) 28 Jan 16 Oil volatility (RHS) 11 Feb 16 25 Feb 16 1 Mar 16 31 Mar 16 8 7 6 5 4 Oil volatility index Summary Key risks highlighted in this report: Volatility will spike again this quarter Correlation risk has not disappeared Liquidity risk could easily progress from being a concern to a problem We group our thinking into five key aspects of market risk: Source: Hermes, Bloomberg, CBOE as at 31 March 216. Recent work by UBS supports the notion that sentiment was much more persistent in the pre-financial crisis era than it is today, with the regularity of nervous peaks shrinking from nine-to-12 months to as little as three months today. 1. Volatility 2. Correlation risk 3. Stretch risk 4. Liquidity risk 5. Event risk While investors must also consider the full gamut of risks, beyond pure financial-market risks, in this paper we will leave our analysis of the wider context for another day. For professional investors only www.hermes-investment.com
Q2 216 Volatility Looking solely at volatility has its pitfalls, but it remains a core building block for all risk analysis. The key is to consider forward-looking volatility through several different lenses and across multiple asset classes. Figure 2 shows the 52-week moving average of the VIX, the Merrill Option Volatility Expectations (MOVE) Index, the Deutsche Bank FX Volatility (Currency VIX) Index and the expected volatility of the Bloomberg Commodity Index (Commodity VIX). These measure the implied volatility of equity markets, government bond markets, currency markets and commodity markets respectively, and have been standardised to make them directly comparable. They each represent the market s expectation of future volatility, and are often viewed as a benchmark of risk appetite. Figure 2: Moving averages of selected volatility measures 4 Figure 3: The volatility of volatility 16 14 12 VVIX index values 1 8 6 4 2 27 28 29 21 211 212 213 214 215 216 VVIX reading 1-year moving average Source: Hermes, Bloomberg, CBOE as at 31 March 216. Normalised index 3 2 1-1 -2 27 VIX 28 29 21 211 212 213 214 215 216 MOVE Currency VIX Commodity VIX Forward-looking volatility predictions rose in two distinct spikes during the quarter, the first during January and the second in late February and early March, before returning to the longer-term moving average level each time. Forward-looking volatility has not reached the heights of that first spike since 211, aside from a short peak last August. We expect further spikes at a higher frequency as 216 unfolds, a reflection of growing uncertainty. We also look at cross-sectional dispersion as a volatility measure. It can be thought of as a measure of the various opportunities available for stock pickers in equity markets, reflecting the best-to-worst range at particular points in time. Source: Hermes, Bloomberg, CBOE, Deutsche Bank, Bank of America Merrill Lynch as at 31 March 216. Equity volatility rose dramatically as the first quarter unfolded, peaking around the middle of February, before falling back to lower levels. However, our normalised measure remains substantially above the average for 215. Bond volatility barely moved over the quarter, dipping modestly in the second half, and remains well below its 215 average. Currency volatility rose steadily as sentiment on the US dollar changed rapidly, while volatility in the commodity and currency markets remained elevated at levels last seen in 213. A number of factors have led to an increase in market speed, crowding, herding and short-term liquidity evaporation, and we would anticipate that these will continue to lead to sudden drops and spikes in the markets during the second quarter. Expectations for future volatility can be seen in the VVIX, a risk-neutral forecast of large-cap US equity index volatility. Figure 4: Cross-sectional dispersion of stock returns 2 18 16 Correlation signal 14 12 1 8 6 4 2 27 28 29 21 211 212 213 214 215 216 Cross-sectional volatility 12-month moving average Source: Hermes, Bloomberg, FTSE as at 31 March 216. 2
Hermes Investment Office For European equities, dispersion rose above and then fell back to its longerterm moving average during the quarter, a move that was echoed in almost all regional equity markets. With a dampened risk environment taking hold as the quarter progressed, dispersion decreased in most markets, even though the long-term trend of increasing dispersion remains intact. Crossasset dispersion also continued its upward trend, suggesting an improving asset-picking environment all round. A new indicator for this quarter is the variance risk premium (VRP). It measures the difference between market-implied volatility and realised risk. It is essentially a contrarian indicator, in that when it is high and positive it suggests that market participants are overly pessimistic about market risk, and vice versa. Figure 5: US equity variance risk premium Risk difference 3 2 1-1 -2-3 -4 1 Feb 8 27 Jun 8 22 Dec 8 23 Jun 9 Variance risk premium 15 Dec 9 11 Jun 1 3 Dec 1 31 May 11 Z-score 21 Nov 11 Source: Hermes, Deutsche Bank as at 31 March 216. When pessimism is highest, it could be an opportunity to buy risky assets. During the quarter VRP spiked and then rapidly dropped, highlighting the swings in market sentiment. We anticipated that 216 could be a bumpy transition, but the start of the year was even rougher than we predicted. We expect the macro environment to remain fluid and volatile, so investors must stay nimble and able to take advantage of opportunities as they arise. With equity volatility falling to about 3% below its long-term average, things may appear too calm to be true. 17 May 12 12 Nov 12 9 May 13 31 Oct 13 29 Apr 14 21 Oct 14 17 Apr 15 9 Oct 15 31 Mar 16 Correlation risk Looking at volatility in isolation runs the risk of being both meaningless and misleading we must also consider correlation, which measures the relationship between assets in a portfolio. Correlation is the second building block upon which the notion of diversification is grounded and, much like volatility, it is highly time variant. As investors, we must be careful about our use of the term correlation. Two variables with the same long-term trend could have a negative, short-term correlation coefficient, over-emphasising the level of diversification available between them. Information regarding the long-term trend should be taken into consideration when assessing diversification. Given that correlation is typically measured with respect to mean values, we should also account for sample error. The markets appeared marginally more correlated at the end than at the beginning of the first quarter. However, the journey between those two points was as traumatic as the trend in volatility. Across the quarter we saw an increased correlation of all assets with oil. Figure 6: Correlation of oil with US equities Correlation.5.4.3.2.1 -.1 -.2 -.3 31 Dec 15 7 Jan 16 14 Jan 16 21 Jan 16 28 Jan 16 4 Feb 16 Correlation (S&P5 Index,WTI Oil) 11 Feb 16 Source: Hermes, Bloomberg as at 31 March 216. Early signs for the current quarter indicate a decline in the Oil/S&P 5 correlation and a weakening of the US dollar/s&p 5 correlation too. This will help to remove some market tail risk, but there is still a chance that the higher drift in correlations could resume. 11 Feb 16 18 Feb 16 25 Feb 16 3 Mar 16 1 Mar 16 17 Mar 16 24 Mar 16 31 Mar 16 Analysing correlation surprise allows us to capture the degree of statistical unusualness in current correlation levels relative to history. Figure 7 shows a correlation surprise index that the Hermes Investment Office has created to demonstrate this effect. In general we can see that spikes in correlation surprise are more often than not followed by disappointing returns. www.hermes-investment.com 3
Q2 216 Figure 7: Correlation surprise in the global equity universe 4, 35, Correlation surprise index 3, 25, 2, 15, 1, 5, 1999 21 23 25 27 29 211 213 215 216 Figure 9: Correlation signal 1.8.6 Correlation.4.2 -.2 -.4 24 26 28 21 212 214 216 Source: Hermes, Bloomberg as at 31 March 216. Figure 8: Correlation surprise and returns, 31 December 1998-17 April 215 Subsequent one-month annualised return. -.5 -.1 -.15 -.2 -.25 -.3 Russell 3 Emerging Markets Average return after correlation surprise Source: Hermes, Bloomberg as at 31 March 216. Emerging Asia Europe China This index remained subdued for much of the quarter, rising to a moderate peak mid-march, far below the levels seen in 214 and 215. The spike captured global markets acting in unison as they recovered from the mid-february lows. The longer-term moving average declined steadily over the quarter. A key challenge in investment management is the variation in correlation levels as assets or asset classes that appear to be uncorrelated often become highly correlated during periods of market stress. Conversely, those that are highly correlated may de-couple at a later time. This instability in the level of correlation is further aggravated by time-dependency in the volatility of the correlation coefficient. At times, correlations appear to fluctuate within a tight range, at others, we see fluctuations in the sign of correlation in very short time periods. Correlation signal 8 7 6 5 4 3 2 1-1 24 26 28 21 212 214 216 Source: Hermes, Bloomberg as at 31 March 216. To overcome these issues, we can think of a correlation signal metric as the average correlation divided by the standard deviation of the coefficient. This can serve as a guide to the stability of the correlation and whether it is viable as a basis for inference. For example, the correlation between global equities and high-yield bonds remained high over the quarter, with a brief burst of instability at the beginning of March as credit markets threatened to dislocate from equity markets. Until relatively recently, asset managers could always rely upon some basic tenets: markets generally respond to changes in their own fundamentals, diversification can be achieved across asset classes and different investment strategies generate independent returns. But in an environment in which assets move in tandem, those tenets do not necessarily hold. This phenomenon is commonly referred to as risk-on risk-off (RoRo) and broadly sees assets split into those that are perceived as risky and those that provide a safe haven. We can create an index, based on decomposing correlations using principal component analysis (PCA), which captures the strength of the RoRo phenomenon at any given point in time. During risk-on periods, risky assets rally in unison and safe-haven investments fall. We witness the opposite during risk-off periods, capturing the mood of the market as it oscillates between optimism and pessimism. 4
Hermes Investment Office Figure 1: Risk-on/risk-off signal.6.5.4.3.2.1 23 Sept 9 23 Mar 92 23 Sept 93 23 Mar 95 23 Sept 96 23 Mar 98 23 Sept 99 23 Mar 1 23 Sept 2 23 Mar 4 RoRo 3-year moving average Long-term average Regime average 23 Sept 5 Source: Hermes, Bloomberg, HSBC as at 31 March 216. The RoRo index ground steadily higher over the first quarter, above its longer-term average, suggesting we should be cautious about diversification assumptions. Figure 11: Correlation heat maps Correlations: March 216 23 Mar 7 Global.Broad.Market BBG.Precious.Metals Japan.1.YEAR.JGB.FLOATING.RA BALTIC.DRY.INDEX Germany.Generic.Govt.1Y.Yield Euro.Generic..Govt.Bond.1Y.Yield Australia.Govt.Bonds.Generic.Y.JAPAN BBG.Livestock BBG.Agriculture BBG.Energy BBG.Industrial.Metals.NORTH.AMERICA.EUROPE Eu.N.FinaFixedFloat.HYC.EM US.NonFin.HY.Constrained Global.HY 23 Sept 8 23 Mar 1 23 Sept 11 23 Mar 13 23 Sept 14 Global HY US NonFin HY Constrained EM EU N-FinaFixed&Float HYC EUROPE NORTH AMERICA BBG Industrial Metals Australia Govt Bonds Generic BBG Industrial Metals BBG Energy BBG Agriculture BBG Livestock JAPAN Australia Govt Bonds Generic Euro Generic Govt Bond 1Y Germany Generic Govt 1Y BALTIC DRY INDEX Japan 1 YEAR JGB FLOAT BBG Precious Metals Global Broad Market 23 Mar 16 Stretch risk Stretch risk allows us to identify assets that trend in one direction for a considerable period of time, suppressing headline volatility and giving the impression that it is less risky than is actually the case. Figure 12: Stretch risk credit momentum 8 7 6 5 4 3 2 1 Jan 1 Apr 1 Jul 1 Oct 1 Jan 11 Apr 11 Jul 11 Oct 11 Jan 12 Apr 12 Jul 12 Oct 12 Jan 13 Apr 13 Jul 13 Oct 13 Jan 14 Apr 14 Jul 14 Oct 14 Jan 15 Apr 15 Jul 15 Oct 15 Jan 16 Mar 16 S&P/ISDA CDS US High Yield Index Source: Hermes, Bloomberg, S&P as at 31 March 216. In the past, we have illustrated this with reference to the credit markets, and commented on the turning point reached in late 214. The market for credit-default swaps on US high-yield bonds, shown in figure 12, moved steadily higher thereafter until mid-february 216, when we saw a sharp reversal, the largest decline of credit spreads on record. Despite this recent move, we suspect that stretch risk remains firmly on the wane in the world of corporate bonds and that the likelihood of underestimating actual risk levels is receding over time. Figure 13: Stretch risk commodity momentum 25 2 Correlations: December 215 US NonFin HY Constrained EU N-FinaFixed&Float HYC EM Global HY EUROPE NORTH AMERICA JAPAN Australia Govt Bonds Generic BBG Industrial Metals BBG Energy BBG Agriculture BBG Livestock Japan 1 YEAR JGB FLOAT BALTIC DRY INDEX Germany Generic Govt 1Y Euro Generic Govt Bond 1Y BBG Precious Metals Global Broad Market BCOM Index 15 1 5 Jan 91 Jan 93 Jan 95 Jan 97 Jan 99 Jan 1 Jan 3 Jan 5 Jan 7 Jan 9 Jan 11 Jan 13 Jan 15 Global.Broad.Market BBG.Precious.Metals.Generic.Govt.Bond.1.Year Germany.Generic.Govt.1Y.Yield BALTIC.DRY.INDEX.YEAR.JGB.FLOATING.RA BBG.Livestock BBG.Agriculture BBG.Energy BBG.Industrial.Metals Australia.Govt.Bonds.Generic.Y.JAPAN.NORTH.AMERICA.EUROPE Global.HY.EM Eu.N.FinaFixedFloat.HYC US.NonFin.HY.Constrained Source: Hermes, Bloomberg as at 31 March 216. The correlation heat map reveals a modest uptick in the measure of correlation stability, which points to likely changes in correlation. For that reason, we suspect that markets as a whole are somewhat more fragile than correlation risk would suggest. Our correlation surprise metric remained largely subdued over the quarter. Bloomberg Commodity Index Source: Hermes, Bloomberg as at 31 March 216. Commodity market stretch risk remains firmly in place, as commodities continued to head towards lows last seen in the late 199s, and the risk of a reversion has stayed high as a result. The steady slide in commodity prices may be understating the true risks of this asset class. Valuations can also become very stretched without the appearance of increased volatility. Assets or markets become extremely cheap or expensive through continual small price movements. However, such valuations rarely persist and a snap back or reversal in value is likely to occur, with the relevant asset or market returning to fair(er) value. www.hermes-investment.com 5
Q2 216 Figure 14: Stretch risk valuations 1.4 1.2 1.8.6.4.2 Apr 1 Apr 2 Apr 3 Apr 4 Apr 5 Apr 6 Apr 7 Apr 8 Ratio of Emerging Markets Index price-to-book value to World Index price-to-book value Apr 9 Source: Hermes, Bloomberg, as at 31 March 216. Apr 1 Apr 11 Apr 12 Apr 13 Apr 14 Apr 15 YTD 16 Figure 15: Funding and credit risk 8 7 6 5 4 % 3 2 1-1 -2 27 28 29 21 211 212 213 214 215 216 TED spread Credit spread Source: Hermes, Bloomberg as at 31 March 216. In figure 14 we compare the price-to-book value in developed equity markets to that in emerging markets. The ratio has modestly reverted over the first quarter, reflecting a reduced difference in valuations between developed and emerging markets relative to their long-term history, as a result of the universal volatility. Both equities and bond markets experienced sharp declines followed by steep recoveries over the quarter. Momentum-based stretch risk also declined during this period, as markets responded to macroeconomic developments. Equally, equity markets have taken their first steps towards restoring longer-term homogeneous relationships. We remain wary of mean reversion. Liquidity risk Investigating the relationship between market risk, funding and monetary liquidity is essential in today s markets. Funding refers to the ease of borrowing, whereas monetary liquidity reflects the ease of monetary conditions. They influence market liquidity, through marketmaking activity and bank funding respectively. The two most closely followed metrics for funding and liquidity risk are the TED spread and the Credit spread. The former focuses on the difference between the interest rates available in the interbank market and those on short-term US government debt, typically at a one- or three-month view. The latter generally focuses on the spread between corporate bonds and government bonds, again at a short maturity. The credit spread is thus an indicator of perceived credit risk, linked closely to the potential for default in the corporate bond market. Both measures remain subdued at pre-crash levels. This indicates that liquidity remains at a reasonable level in the money markets, and that liquidity concerns have not fully engulfed the credit markets yet. The two measures moved in opposite directions during the quarter, but not sufficiently to assume liquidity. Low trading activity appears to be a feature across almost all markets and is clearly contributing to an increase in the number of violent dislocations in asset prices. Taking the foreign-exchange markets as an example, declining interbank volume in all but a few major currency pairs continues to result in liquidity shocks becoming more frequent and liqudity risks should stay prominent in investors minds during 216. Dislocations can occur in markets for even highly liquid assets as liquidity can come and go. Moreover, the liquidity of an asset often depends on the direction in which you wish to trade and the direction that the rest of the market wishes to take. Add to that the volume of the trade, and we introduce another variable that influences liquidity. By identifying crowded trades, we are able to identify potential triggers of liquidity risk. The monthly survey conducted by Bank of America Merrill Lynch of global fund managers provides some clues. Figure 16: Fund managers answer the question: where do you think the most crowded trades currently are? Other Long quality Short treasuries Short high-yield credit Long US FANG Short emerging markets Short oil Long Eurostoxx 5 Long EU periphery debt Long US dollar % 5% 1% 15% 2% 25% 3% 35% Apr 16 Mar 16 Feb 16 Source: Hermes, Bank of America Merrill Lynch as at 13 April 216. 6
Hermes Investment Office A number of popular trades fell away rapidly during the quarter, such as long US dollar and short oil. A new position, long quality in equities, was flagged as extremely crowded in the most recent report. This suggests that concerns over liquidity risk in the corporate debt market remain highly relevant, and we continue to closely monitor this liquidity with our credit portfolio managers. We analysed the Hui and Heubel ratio for both Bund futures in last quarter s Market Risk Insights the ratio measures intra-day price movements relative to the ratio of traded volume to either market capitalisation or open interest. Figure 17: The Hui and Heubel ratio for Bund futures Hui and Heubel ratio.1.9.8.7.6.5.4.3.2.1. Jan 1 Bund Jul 1 Jan 11 Jul 11 Jan 12 Jul 12 Jan 13 Jul 13 Bund 2-period moving average Source: Hermes, Bloomberg as at 31 March 216. Jan 14 Jul 14 Jan 15 Jul 15 Jan 16 Figure 18: Turbulence index future returns Turbulence index.8.6.4.2. -.2 -.4 -.6 -.8-1. Russell 3 Emerging Markets Emerging Asia Full sample annualised return Annualised return following most turbulent period Annualised return following most non-turbulent period Source: Hermes, Bloomberg as at 31 March 216. Europe China In Figures 18 and 19 we analyse market turbulence by identifying the statistical unusualness of the current risk environment, in terms of both volatility and correlation. This demonstrates that most turbulent periods precede significant drawdowns in multiple asset classes and markets. Figure 19: Turbulence index global equities 3 Although we witnessed one significant spike in the first quarter, the ratio was generally subdued, suggesting that on the whole liquidity remained at reasonable levels. We would anticipate further spikes throughout 216, signifying a reduction in market depth, and this demonstration of liquidity risk would be likely to spill over to other, less liquid markets. Concerns about liquidity in the bond markets remain entirely valid in our view, with the distinct possibility for contagion to other asset classes should there be further shocks that lead to capital flight. Event risk No discussion of risk would be complete without consideration of the events which determine the degree of uncertainty that is prevalent at any one time. We recommend the use of non-standard models when attempting to quantify risk, and feel strongly that a better understanding of possible outcomes stems from stress-testing portfolios and detailed scenario analysis. During the financial crisis, unusually high market volatility and turbulence affected the entire global economy. If we can successfully identify periods in which asset prices behave uncharacteristically, then we may be able to minimise portfolio drawdowns by adjusting portfolios appropriately in advance. Turbulence index 25 2 15 1 5 1999 21 23 25 27 29 211 213 215 Moving average Source: Hermes, Bloomberg, as at 31 March 216. Global equity turbulence remained at subdued levels for the first quarter of 216. This implies that markets behaved normally relative to their own history, despite the plunge in the early part of the quarter and the subsequent rallies across the board. Times of financial turbulence are typically persistent and provide lower rewards for risk than normal times. As such, this measure can be used to construct portfolios that are relatively resistant to turbulence through a conditioning process. The tool that allows us to estimate market fragility is the absorption ratio, which captures the market s ability to absorb shocks. It is best thought of as a measure of systemic risk. We use PCA to determine the extent to which the largest risk factors dominate the entire risk factor set. When markets are particularly vulnerable to shocks, a handful of factors will explain the vast majority of risk, increasing the absorption ratio. www.hermes-investment.com 7
Q2 216 Figure 2: Absorption ratio global equities Absorption ratio 1..98.96.94.92.9.88 1999 21 23 25 27 29 211 213 215 Moving average Source: Hermes, Bloomberg, as at 31 March 216. The absorption ratio was already at elevated levels and moved marginally higher during the quarter. This suggests fragility that the other event risk indicators discussed have not identified. We add a new indicator this quarter, termed the smart-money flow index. It is calculated by comparing trading activity in a US equity index across two time periods, the first and last half hours of the trading day. Activity during the opening spell is dominated by retail investors, buying on emotion and overnight news, while the smart money waits until the end of the day when a significantly greater quantity of assets is traded. Figure 21: Smart-money flow index 2, 19,5 19, 18,5 18, 17,5 17, 16,5 16, 15,5 15, Mar 11 Jun 11 Sep 11 Dec 11 Mar 12 Jun 12 Smart-money flow index Sep 12 Dec 12 Mar 13 Jun 13 Source: Hermes, Bloomberg as at 31 March 216. In the most recent quarter, we saw a significant increase in early activity relative to activity later in the day. We also recently saw a day on which no stock on the New York Stock Exchange was at a new 52-week low, a Sep 13 Dec 13 Mar 14 Jun 14 Sep 14 Dec 14 Mar 15 Jun 15 Sep 15 Dec 15 Mar 16 phenomenon last seen in 1991. This suggests that the recent swings in markets were indiscriminate, with investors seemingly caring little about the semantics of stock selection, a cause for concern. Event risk is a constant feature of financial markets. Our two key metrics for capturing this type of risk, the turbulence index and the absorption ratio, are at odds with one another as we continue through 216. Although assets are behaving relatively typically, the markets will remain vulnerable to shocks in the coming months. Conclusion In financial markets, we are faced with a core dilemma: while we cannot know the probable distributions of asset returns with any certainty, we can be sure that the same outcomes present in normal market conditions are unlikely to play out during crises. To manage this conflict, we try to measure risk in our portfolios. Our assessment of risk during the current quarter suggests the following: Volatility will remain highly changeable and is unlikely to stay at its current low levels. The likelihood of further and more frequent spikes in 216 is significant. Correlation risk appears subdued on the surface, due to short-term decoupling of some asset classes, as the gloss of unconventional monetary policies starts to pale. Should conditions deteriorate, correlation risk will return to the fore. Stretch risk concerns have subsided, as long-established trends have been broken. Liquidity risk remains a significant issue, particularly in the credit markets. This exacerbates the potential for contagion across asset classes in the event of a local shock. Event risk has returned to amber, with one key metric pointing to fragility and the other to more subdued levels. We emphasise the former over the latter. The concerns that overshadowed the markets during the first quarter haven t gone away. China s slowing growth, increasingly acute political risks and uncertainty over the exact path and pace of US rate rises all remain problematic. Systematic strategies were highly supportive of the recent equity rally contributing to the suppression of realised volatility, but that may not be sustained should further market wobbles appear and risk remains skewed to the downside due to the cost of options trading. We are in a fragile risk environment, where markets are capable of providing severe dislocations, even if short-lived. The case for believing that multi-asset portfolios today are more risky than they might initially appear remains a strong one, especially if they rely on historical correlations. Although we have witnessed some divergence between equity and bond markets, we believe that the benefits of diversification in portfolios remain over-stated. The Hermes Investment Office Totally independent of the investment teams, the Hermes investment Office continuously monitors risk across client portfolios and ensures that teams are performing in the best interests of investors. It provides rigorous analyses and attributions of performance and risk, demonstrating our commitment to being a transparent and responsible asset manager 8
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Excellence. Responsibility. Innovation. Hermes Investment Management Hermes Investment Management is focused on delivering superior, sustainable, risk-adjusted returns responsibly. Hermes aims to deliver long-term outperformance through active management. Our investment professionals manage equity, fixed income, real estate and alternative portfolios on behalf of a global clientele of institutions and wholesale investors. We are also one of the market leaders in responsible investment advisory services. Our investment solutions include: Private markets International real estate, UK commercial real estate, UK private rental sector real estate, infrastructure and private equity High active share equities Asia, global emerging markets, Europe, US, global, and small and mid cap Credit Absolute return credit, global high yield bonds, multi strategy credit, real estate debt and direct lending Multi asset Multi asset inflation Responsible Investment Services Corporate engagement, intelligent voting and public policy engagement Offices London New York Singapore Contact information Hermes Investment Office Eoin Murray, Head of Hermes Investment Office +44 ()2 768 282 eoin.murray@hermes-investment.com Neil Williams, Group Chief Economist +44 ()2 768 2398 neil.williams@hermes-investment.com Business Development United Kingdom +44 ()2 768 2121 Africa +44 ()2 768 225 Asia Pacific +65 688 5858 Canada +44 ()2 768 225 Europe +44 ()2 768 2121 Middle East +44 ()2 768 225 United States +44 ()2 768 225 Enquiries marketing@hermes-investment.com Disclaimer This document is for Professional Investors only. The views and opinions contained herein are those of Eoin Murray, Head of the Investment Office, and may not necessarily represent views expressed or reflected in other Hermes communications, strategies or products. The information herein is believed to be reliable but Hermes does not warrant its completeness or accuracy. No responsibility can be accepted for errors of fact or opinion. This material is not intended to provide and should not be relied on for accounting, legal or tax advice, or investment recommendations. This document has no regard to the specific investment objectives, financial situation or particular needs of any specific recipient. This document is published solely for informational purposes and is not to be construed as a solicitation or an offer to buy or sell any securities or related financial instruments. Figures, unless otherwise indicated, are sourced from Hermes. The distribution of the information contained in this document in certain jurisdictions may be restricted and, accordingly, persons into whose possession this document comes are required to make themselves aware of and to observe such restrictions. Issued and approved by Hermes Investment Management Limited ( HIML ) which is authorised and regulated by the Financial Conduct Authority. Registered address: Lloyds Chambers, 1 Portsoken Street, London E1 8HZ. HIML is a registered investment adviser with the United States Securities and Exchange Commission ( SEC ). CM154999 T445 4/16 Certified ISO 141 Environmental Management www.hermes-investment.com