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Q3 2016

Hermes Investment Office Market Risk Insights

A bend in the road is not the end of the road… unless you fail to make the turn. Helen Keller – author and political activist

In our third Market Risk Insights of 2016, we try to add some colour to the current market risk environment as we move into an uncertain second half of the year. As predicted, the markets were prone to bouts of in the second quarter, the biggest of which came when the UK voted to leave the European Union. On the back of such instability, navigating the markets is always going to require more than a simple understanding of the investment fundamentals.

The Brexit vote is not a crisis on the scale of Lehman Brothers’ collapse We group our thinking into five key aspects of market risk: and the subsequent global financial crisis – the latter was a financial crisis with -lasting geo-political consequences, whereas Brexit is 1. Volatility a geopolitical event that may well have deep financial repercussions. 2. Correlation risk However, we should not downplay the potential dangers for 3. Stretch risk in the post-Brexit environment. The risk of contagion remains real, even as equity markets are showing signs of recovery. The Italian banking 4. Liquidity risk system is one pressure point. Unconventional monetary policy and its 5. Event risk knock-on effects (particularly on banks and investors) also remains an acute cause for concern. While investors must also consider the full gamut of risks, beyond pure risks, we will leave our analysis of the wider context for This makes it even more challenging for investors and fund another day. managers to navigate the markets. We cannot underestimate the risks posed by real-world scenarios. But, as investors, we must bear some risk in order to generate returns and must broaden our Summary understanding of risk beyond traditional measures to attempt to Key risks highlighted in this report: capture the full picture. „„Volatility will spike again this quarter Risk is best considered a multi-headed hydra, one that changes shape dramatically through time depending on market conditions. As such, „„Correlation risk is heightened understanding the impact of market risks requires close analysis of the „„Liquidity risk could easily progress from being a concern to risks at hand. a problem

The Hermes Investment Office Totally independent of the investment teams, the Hermes Investment Office continuously monitors risk across client portfolio and ensures that teams are performing in the best interest of investors. It provides rigorous analyses and attributions of performance and risk, demonstrating our commitment to being a transparent and responsible asset manager.

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Expectations of future volatility can be seen in the VVIX, a risk-neutral Volatility forecast of large-cap US equity index volatility. Looking solely at volatility has its pitfalls, but it remains a reasonable starting point for all risk analysis. The key is to consider forward-looking Figure 2: The volatility of volatility volatility through several different lenses, across multiple asset classes and various geographies. 14

We use a broad collection of volatility measures. Figure 2 shows the 12 52-week moving average of the VIX, the Merrill Option Volatility Expectations (MOVE) Index, the Deutsche Bank FX Volatility (Currency 10 VIX) Index and the expected volatility of the Bloomberg Commodity 8 Index (Commodity VIX). These measure the implied volatility of equity markets, markets, currency markets and commodity Index 6 markets respectively, and have been standardised to make them directly comparable. They each represent the market’s expectation of future 4 volatility and are often viewed as a benchmark of risk appetite. 2

Figure 1: Moving averages of selected volatility measures 0 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 VVIX 1 year MA 4

Source: Hermes, Bloomberg, CBOE as at 30 June 2016. 3

2 Forward-looking volatility predictions rose through the quarter and spiked as the UK’s referendum approached. At the end of the quarter 1 VVIX remained elevated. The one-year moving average ground steadily higher, a direction we expect it to continue following. We also

Normalised Index 0 anticipate further spikes as the rest of 2016 unfolds, a reflection of continued uncertainty. -1 The term structure of volatility can help predict the state of the market -2 and aid the construction of profitable investment strategies. With 2008 2009 2010 2011 2012 2013 2014 2015 2016 respect to the VIX, the term structure is captured by comparing the VIX MOVE Currency VIX Commodity VIX price levels of different futures expirations. Since volatility is a measure of systematic risk, the VIX term structure suggests the trend of future Source: Hermes, Bloomberg, CBOE, Deutsche Bank, Bank of America Merrill Lynch as at 30 June 2016. market risk. If the VIX is upward-sloping, it implies that investors expect the volatility of the market to rise in the future. If the VIX is downward sloping, it indicates that investors expect the volatility of the market to Equity volatility waxed and waned as the second quarter unfolded, fall in the future. peaking with the UK’s decision to leave the European Union. Although it remains substantially elevated over the 2015 average, it dropped as the quarter progressed with a strong upturn at the very end. Bond volatility Figure 3: Term structure of volatility fell steadily over the quarter and remains well below its 2015 average. 28 Currency volatility continued its steady rise as sentiment in the currency markets changed rapidly, with volatility in both the commodity and 26 currency markets elevated to levels last seen in 2012-13. A number of factors have led to an increase in market speed, crowding, herding and 24 -term liquidity evaporation, and we would anticipate that these 22 will continue to lead to sudden drops (and spikes) in the markets during the second quarter. Index 20 18

16

14 22 May 29 May 05 June 12 June 19 June 26 June 03 July 16 16 16 16 16 16 16 VIX July 16 VIX Jan 17

Source: Hermes. Bloomberg, CBOE as at 5 July 2016.

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We have compared the current July contract to the first contract When pessimism is highest, opportunities for buying risky assets available in 2017, where there is enough open interest to make it are likely to exist. The predictive power of this measure tends to be meaningful. Aside from the immediate EU referendum period, the latter strongest at extreme points. Unsurprisingly, at the end of the quarter contract has been stubbornly higher, marginally above the VIX’s long- VRP spiked, reflecting the swing in on the back of term average of about 20. This shows the market anticipates higher the referendum result. volatility over the next 6 months. We anticipated that 2016 could be a bumpy year and there has been no We also like to look at cross-sectional dispersion as a volatility metric. let-up as we progressed from the first to the second quarter. We expect It is a measure of the various opportunities available for pickers in the macro environment to remain fluid and volatile. It will be essential equity markets, reflecting the best- to-worst range at particular points for investors to stay nimble and able to take advantage of opportunities in time. as they arise. We anticipate that periods of calm will become shorter, with spikes in volatility becoming sharper and longer as uncertainty Figure 4: Cross-sectional dispersion of stock returns remains at the fore.

20 Correlation risk Looking at volatility in isolation runs the risk of being both meaningless 16 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, 12 much like volatility, it is highly time variant.

Percent

As investors, we must be careful about our use of the term correlation. 8 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 4 long-term trend should be taken into consideration when assessing 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 diversification. Given that correlation is typically measured with respect Cross sectional volatility 12 Month Moving Average to mean values, we should also account for sample error. Source: Hermes, Bloomberg, FTSE as at 30 June 2016. Figure 6: Correlation heat maps

The recent bout of volatility was distinguished by rapid increases in Correlations: March 2016 Global HY dispersion around the globe. The rise in dispersion in UK equities far US NonFin HY Constrained MSCI EM EU N-FinaFixed&Float HYC outpaced the jump in volatility. For European equities, dispersion is MSCI EUROPE MSCI NORTH AMERICA BBG Industrial Metals currently in its highest decile since early 2007. Above median dispersion Australia Govt Bonds Generic BBG Industrial Metals BBG Energy levels have become the norm in most non-US markets, while in the US BBG Agriculture BBG Livestock MSCI JAPAN dispersion is slightly lower. Cross-asset dispersion also continued its Australia Govt Bonds Generic Euro Generic Govt Bond 10Y upward trend, suggesting an improving asset picking environment all round. Germany Generic Govt 10Y BALTIC DRY INDEX Japan 10 YEAR JGB FLOAT BBG Precious Metals The variance risk premium (VRP) measures the difference between Global Broad Market market implied volatility and realized risk and is essentially a contrarian MSCI.EM Global.HY BBG.Energy MSCI.JAPAN BBG.Livestock indicator in that when it is high and positive it suggests that market MSCI.EUROPE BBG.Agriculture BALTIC.DRY.INDEX BBG.Precious.Metals participants are overly pessimistic about market risk and vice versa. Global.Broad.Market BBG.Industrial.Metals MSCI.NORTH.AMERICA Eu.N.FinaFixedFloat.HYC US.NonFin.HY.Constrained Australia.Govt.Bonds.Generic.Y Germany.Generic.Govt.10Y.Yield Japan.10.YEAR.JGB.FLOATING.RA

Figure 5: Variance risk premium, US equities Euro.Generic..Govt.Bond.10Y.Yield

300 Correlations: June 2016 Global HY US NonFin HY Constrained 200 EU N-FinaFixed&Float HYC MSCI EM MSCI EUROPE MSCI NORTH AMERICA 100 BBG Industrial Metals BBG Energy BBG Agriculture MSCI JAPAN Australia Govt Bonds Generic 0 Euro Generic Govt Bond 10Y Germany Generic Govt 10Y BBG Livestock BALTIC DRY INDEX -100 Japan 10 YEAR JGB FLOAT BBG Precious Metals

Risk difference Global Broad Market -200 MSCI.EM Global.HY BBG.Energy MSCI.JAPAN BBG.Livestock -300 MSCI.EUROPE BBG.Agriculture BALTIC.DRY.INDEX BBG.Precious.Metals Global.Broad.Market BBG.Industrial.Metals MSCI.NORTH.AMERICA -400 Eu.N.FinaFixedFloat.HYC US.NonFin.HY.Constrained Japan 10 Year JGB Floating RA Year Japan 10 Australia.Govt.Bonds.Generic.Y 2008 2009 2010 2011 2012 2013 2014 2015 2016 Euro.Generic.Govt.Bond.10.Year Germany.Generic.Govt.10Y.Yield Variance Risk Premium Z-score

Source: Hermes, Deutsche Bank. as at 7 July 2016. Source: Hermes, Bloomberg as at 30 June 2016.

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From a correlation perspective, the markets appeared little changed by time-dependency in the volatility of the correlation coefficient. At at the end of the quarter. However, the journey to that point from times, correlations appear to fluctuate within a tight range, at others, the beginning of the quarter was far from straightforward. Developed we see fluctuations in the sign of correlations in very short time periods. equities and credit markets in particular have seemed fragile from a correlation perspective. Figure 9: Correlation v correlation signal

Analysing correlation surprise allows us to capture the degree of 1.0 statistical unusualness in current correlation levels relative to history. As with any statistical measure, we must be cautious when interpreting this 0.8 data. In general though, we can see that spikes in correlation surprise are often followed by disappointing returns. 0.6

0.4 Figure 7: Correlation surprise and returns, 31 December 1998 – 17 April 2015

Correlation 0.2 0.00

-0.0 -0.05

-0.10 -0.2

-0.15 -0.4 2004 2006 2008 2010 2012 2014 2016 -0.20 80 -0.25 70 Subsequent one-month annualised return -0.30 Russell MSCI MSCI MSCI MSCI 60 3000 Emerging Emerging Europe China Markets Asia 50

Average return after correlation surprise 40 30

Source: Hermes, Bloomberg as at 31 March 2016. Correlation signal 20

Figure 8: Correlation surprise in the global equity universe 10

400,000 0 -10 350,000 2004 2006 2008 2010 2012 2014 2016 300,000 Source: Hermes, Bloomberg as at 30 June 2016. 250,000

200,000 To overcome these issues, we can think of a correlation signal metric as the average correlation divided by the standard deviation of the 150,000 coefficient. This can serve as a guide to the stability of the correlation

Correlation surprise index 100,000 and whether it is viable as a basis for inference. For example, the correlation between global equities and high-yield bonds remained high 50,000 over the quarter, with a sizeable jump towards the end. The bottom

0 chart in figure 9 shows considerable instability in the correlation 1999 2001 2003 2005 2007 2009 2011 2013 2015 2016 between different risky assets even before the vote.

Source: Hermes, Bloomberg as at 30 June 2016. The correlation heat map suggests an unchanged, relatively calm level of correlation risk, whereas the correlation surprise and correlation This index soared at the time of the referendum, with one of the stability metrics suggest that the relationship between risky assets is largest peaks seen since 2011. The uncertainty surrounding the vote both unusual and unstable. As a result, we suspect that markets are to leave and what it will mean for financial markets has clearly more fragile than the correlation heat map indicates. exacerbated the statistical unusualness of asset behaviour, and that is captured in this chart. We expect this to continue as events unfold in the coming months.

Variation in correlation levels is a key challenge in investment management 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

4 Hermes Investment Office

Valuations can become very stretched without the appearance of Stretch risk increased volatility. Assets or markets can become extremely cheap or Stretch risk allows us to identify assets that trend in one direction for a expensive through continual small price movements. However, such considerable period of time, suppressing headline volatility, and giving valuations rarely persist and a snap back or reversal in value is likely to the impression that an asset is less risky than is actually the case. occur, with the relevant asset or market returning to fair(er) value.

Figure 10: Stretch risk – IG/HY ratio Figure 12: Stretch risk – valuation 1.4 0.30 1.2

1.0

0.25 0.8

Ratio 0.6

Ratio 0.4 0.20 0.2

0.0 2011 2012 2015 2013 2016 2014 2001 2010 2007 2002 2005 2003 2009 2006 2004 2008 0.15 2010 2011 2012 2013 2014 2015 2016 Ratio of MSCI Emerging Markets Index P/B to MSCI World Index P/B SPCDZR50 Index/SPCDYR50 Index

Source: Hermes, Bloomberg, MSCI as at 1 July 2016. Source: Hermes, Bloomberg, S&P as at 5 July 2016.

Here, we compare the Price-to-Book value in developed equity markets In the past, we have illustrated this with reference to specific credit to that in emerging markets. The modest reversion that we noted in markets, and in this edition we look at the ratio of investment grade to the first quarter, reflecting a narrowing of the differences in valuation high-yield credit. We compare two indices of credit default swaps on terms between developed and emerging markets, has persisted. This is a investment grade and high yield corporate entities in the US. After four significant reversal, as over the preceding 68 months developing markets years of spread narrowing between the two sections of the liquid credit continuously cheapened relative to their developed counterparts. market, spreads have recommenced their widening which has continued in the second quarter after the brief blip of the first quarter 2016. Over the past few years, corporate buybacks have provided significant support for equity markets, in the US in particular. Buyback A second example of stretch risk that we believe is still firmly in play is announcements are now slowing at a dramatic pace, falling by around in the commodity markets. 40% on a trailing 12-month view.

Figure 11: Stretch risk – commodity Figure 13: Stretch risk – buybacks 250

800 2,200

200 700 2,000

600 1,800 S&P 500 Index 500 S&P 150 500 1,600

BCOM Index 400 1,400

100 Buybacks 300 1,200

200 1,000 50 100 800 1992 2012 1996 2016 1994 2014 1998 2010 2002 2006 2004 2008 2000 0 600 Bloomberg Commodity Index 2004 2006 2008 2010 2012 2014 2016 Buybacks # Companies Buybacks USD billion S&P 500 Index Source: Hermes, Bloomberg as at 5 July 2016.

Source: Hermes, Bloomberg, MSCI as at 30 June 2016. Having seen commodities head continually lower over the last five years towards levels not seen since the late ‘90s, the risk of reversion emerged This activity has also been highly supportive of equity markets as a in the first half of the year. The steady slide in commodity prices whole in recent years. The index of the 100 firms with the largest appears to have been stopped, as nearly all commodities have risen with buybacks shown above has, until recently, comfortably outperformed oil. It is not yet clear whether they can break out of the range in which the US equity market. This source of demand has helped to stabilise they appear bound. equity markets, particularly during the selloffs in the last 12 months. The slowdown in buybacks indicates higher perceived risk in equity markets and potentially greater difficulty in shrugging off future volatility.

www.hermes-investment.com | 5 Q3 2016

Riskier assets were pulled lower in mid-February, and we have witnessed considerable since that point. Their stretched valuations Figure 15: Fund managers answer the question: where do you think the most appear to have turned and there was a shift in momentum for specific crowded trades currently are? assets. It is unclear whether that will spread through asset classes and markets over the course of the year. Other Long Gold Liquidity risk Long S&P500 Investigating the relationship between market risk, funding and Short UK Equities monetary liquidity is essential in today’s markets. Funding refers to the ease of borrowing, whereas monetary liquidity reflects the ease of Long Cash monetary conditions. They influence market liquidity, through market- Long Quality making activity and bank funding respectively. Short Treasuries The two most closely followed metrics for funding and liquidity risk Short EM are the TED spread and the Credit spread. The former focuses on the difference between the interest rates available in the interbank market Long Eurostoxx 50 and those on short-term US government debt (T-Bills), typically at a Long USD one- or three-month view. The latter generally focuses on the spread between corporate bonds and government bonds, again at a short 0% 5% 10% 15% 20% 25% 30% maturity. The credit spread is thus an indicator of perceived credit risk, Jun-16 May-16 Apr-16 linked closely to the potential for default in the corporate bond market. Source: Hermes, Bloomberg as at. 30 June 2016. Figure 14: Funding and credit risk A number of popular trades fell away during the quarter, such as long dollar and short emerging markets. Long quality equities remains 8 popular in the most recent survey and has been joined by long cash and short UK equities. 6 Concerns over liquidity risk in the corporate debt market remain highly 4 relevant, and we continue to closely monitor this liquidity alongside our credit portfolio managers. We analysed the Hui and Heubel ratio

Percent for both Bund futures in last quarter’s Market Risk Insights – the ratio 2 measures intra-day price movement relative to the ratio of traded volume to either market capitalisation or open interest. 0

Figure 16: The Hui and Heubel ratio for Bund futures -2 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 0.10 TED Spread Credit Spread 0.09 0.08 Source: Hermes, Bloomberg as at 30 June 2016. 0.07 0.06

Both measures continue to remain subdued at pre-crash levels. This HHL ratio 0.05 indicates that liquidity is at a reasonable level in the money markets, 0.04 and that liquidity concerns have not engulfed the credit markets yet. 0.03 However, we know anecdotally from dealing with the credit markets 0.02 that pockets of illiquidity abound, and that can be 0.01 particularly fleeting. 0.00 Jul 11 Jul 12 Jul 15 Jul 13 Jul 16 Jul 14 Jul 10 Jan 11 Jan 12 Jan 15 Jan 13 Jan 16 Jan 14 Dislocations can occur in markets for even highly liquid assets as Jan 10 liquidity can come and go. The liquidity of an asset also often depends Euro Bund 20 per. Mov. Avg. (Euro Bund) 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, Source: Hermes, Bloomberg as at 6 July 2016. and we introduce another variable that influences liquidity.

By identifying crowded trades, we are better able to identify potential The quarter began with a low HH ratio for bund futures suggesting trigger sources of liquidity risk. The monthly survey conducted by Bank plenty of depth, but it spiked rapidly twice towards the end of the of America Merrill Lynch of global fund managers provides some clues. period, in the run-up to the UK referendum and then immediately following it. We anticipate further spikes throughout 2016, signifying a reduction in market liquidity, and we don’t believe that demonstrations of liquidity risk will be limited to as large a market as Bund futures without some contagion to other less liquid markets.

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We can also measure the prevailing liquidity conditions in the US Treasury market. The index below displays the average yield error across Figure 18: Turbulence index – future returns the universe of US Treasury notes and bonds with remaining maturity 0.8 1-year or greater, based off the intra-day Bloomberg relative value curve 0.6 fitter. When liquidity conditions are favourable, the average yield errors 0.4 are small, as dislocations from fair value are normalized within a short 0.2 time frame. Under stressed liquidity conditions, dislocations from fair 0.0 value are persistent resulting in large average yield errors. -0.2 -0.4 Figure 17: US Bond liquidity Turbulence index -0.6 -0.8 -1.0 4 Russell MSCI MSCI MSCI MSCI 3000 Emerging Emerging Europe China Markets Asia 3.5 Full sample annualised return Annualised return following most turbulent period 3 Annualised return following most non-turbulent period

2.5 Source: Hermes, Bloomberg as at 31 March 2016. 2 Index Here, we analyse market turbulence by identifying the statistical 1.5 unusualness of the current risk environment, in terms of both volatility and correlation. This demonstrates that most turbulent periods precede 1 significant drawdowns across a number of asset classes and markets.

0.5 Figure 19: Turbulence index – global equities 0 30 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 US Govt Securities Liquidity Index 25

Source: Hermes, Bloomberg as at 5 July 2016. 20

We can see that liquidity conditions in the US government securities 15 have been steadily tightening over several years. There was a brief dip Index in late 2015 and early 2016, but the trend has been restored, with the 10 Brexit decision having a particularly sharp influence. 5 Concerns about liquidity in the bond markets remain entirely valid 0 in our view, with the distinct possibility for contagion to other asset 2011 2012 2015 2013 2016 2014 2010 2001 2007 2002 2005 2003 2009 2006 2004 2008 classes should there be further shocks that lead to capital flight. 2000 Global Equity Turbulence 30-day moving average

Event risk Source: Hermes, Bloomberg, MSCI as at 30 June 2016. No discussion of risk would be complete without consideration of the events which determine the degree of uncertainty that is Global equity turbulence remained at subdued levels for much of the prevalent at any one time. We recommend the use of non-standard second quarter of 2016, with a spike at the end of the period associated, models when attempting to quantify risk, and feel strongly that a as with several other metrics, with the Brexit vote. This implies that better understanding of possible outcomes stems from stress-testing markets behaved normally relative to their own histories, despite the portfolios and detailed scenario analysis. plunge in the later part of the quarter.

During the financial crisis, unusually high market volatility and financial The next tool that allows us to estimate market fragility is the turbulence affected the entire economy. If we can successfully identify absorption ratio, which captures the market’s ability to absorb shocks. periods in which asset prices will behave uncharacteristically, then we It is best thought of as a measure of systemic risk. We use principal may be able to minimise portfolio drawdowns by adjusting portfolios components analysis (PCA) to determine the extent to which the appropriately in advance. 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.

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During the most recent quarter, we have seen a significant increase Figure 20: Absorption ratio – global equities in early activity relative to institutional activity later in the day. This suggests that the recent swings in markets were fairly indiscriminate, 1.00 with investors little concerned about the semantics of stock selection amid the uncertainty of the macroeconomic environment. 0.98

0.96 Figure 22: Political risk

0.94 3.0 2.5 0.92 Absorption Ratio 2.0 0.90 1.5 1.0 0.88 0.5 Index 2011 2012 2015 2013 2016 2014 2001 2010 2007 2002 2005 2003 2009 2006 2004 2008 2000 0.0 Absorption Ratio -0.5

Source: Hermes, Bloomberg, MSCI as at 30 June 2016. -1.0 -1.5 -2.0 The absorption ratio for global equities has remained elevated, but 2011 2012 2013 2014 2015 2016 was not as aggravated by Brexit as other risk metrics. Nonetheless, its BNP Political Risk Index elevation suggests continued fragility that the other event risk indicators we consider have not identified. Source: BNP Paribas, Bloomberg, Hermes IM as at 27 June 2016. Another indicator of event risk is the smart-. It is calculated by comparing trading activity in a US equity index across two Tensions from Britain’s vote to leave the European Union are spreading time periods, the first and last half hours of the trading day. Activity beyond its borders, driving an index of political risk in the Euro region to during the opening spell tends to be dominated by retail investors, its highest level since at least 2011. With the vote boosting contagion buying on emotion and overnight news, while the ‘smart money’ waits concerns and the outside possibility of the breakdown of the entire until the end of the day when a significantly greater quantity of assets EU project, alongside the looming elections in the U.S. and elsewhere, is traded. there’s potential for political upheaval to spill over into markets. Investors are increasingly having to evaluate the political context.

Figure 21: Smart money 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 20,000 ratio, remained subdued in the second quarter, although other metrics 19,500 are giving strong warning signals. Collectively all of our metrics suggest 19,000 that, while assets are behaving relatively normally, the possibility of 18,500 market shocks during the rest of 2016 remains. 18,000 17,500 Index 17,000 16500 16,000 15,500 15,000 2011 2012 2013 2014 2015 2016 Smart Money Flow Index

Source: Hermes, Bloomberg as at 1 July 2016.

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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.

Overall, our forecast for risk during the third quarter is:

Volatility will remain highly changeable and markets are signalling a rise in market instability. The likelihood of further and more frequent spikes in 2016 is significant.

Correlation risk rose during the second quarter and will remain at a heightened level.

Stretch risk concerns have subsided, as long-established trends have broken.

Liquidity risk remains a significant issue for the credit markets in particular, although liquidity concerns abound more generally too. This exacerbates the potential for market risk contagion in the event of a local shock.

Event risk has dipped to green on the traffic light scale, as markets have steeled themselves for further uncertainty.

Several concerns that have overshadowed the markets are still with us. China’s bumpy landing, increasing political uncertainty in Europe and the US, and significant pockets of corporate leverage are all key risks. We remain in a fragile risk environment, where markets are capable of providing severe dislocations, even if short-lived, due to generally poor liquidity and central bank market activity.

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

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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.

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