MARKET RISK REPORT 2016: What a year

December 2016

Volatilities rose during November and were typically medium relative to their 12-month averages.

Realised volatility (of Eurostoxx equities over 30 days) rose from 11.4% to 12.6% (low).

Equity market price moves were moderate and mixed during the month. Volatility trends were all upwards. Sector volatilities rose to 13-16% (but with Energy at 23%). Sector volatilities were all medium or high relative to the last 12 months.

Sovereign bond price moves were downwards. Bond volatility changes were all upwards, ending at 4-5% (and 2.1% in Japan). The US was low, others high.

FX price moves were once again large. Volatility trends were mixed: e.g. €/£ down to 9.5%. Volatilities were medium for all major currencies relative to the euro, except €/Yen which stayed low.

Option volatility will likely have risen, driven by rising volatility of volatility and with some large moves in underlying prices during the month. Volatility of volatility for the US ended at 126% (medium).

Commodities’ price moves were large, with Oil rising +4.5% but Gold -8.0%. Volatility moves were upwards e.g. Oil sharply up to 48% (high).

Real Estate (equity) price moves were again downwards outside Japan. Volatility changes were mixed and finished at 19.7% in the US (high) and 15.3% in Europe (low). PE Funds prices rose again, with volatility trends in PE and hedge funds mixed.

Niall O’Connor

Executive summary

Table of contents

1. Summary volatility matrix p. 4

2. Key News p. 5

3. Kurtosis & correlation in the equity markets p. 6-7

4. Equities p. 8-9

5. Equity Implied Volatility p. 10

6. Fixed Income p. 11

7. Foreign Exchange p. 12

8. (Equity) Options p. 13

9. Commodities p. 14

10. Real Estate (Real Estate Share Prices) & Alternatives p. 15-16

Note: Throughout the text we refer to volatilities as being "low", "medium" or "High". We define this by defining three equal "sized" regimes over the last 12 months. i.e. “High” volatility implies that volatility is in the upper third of its statistical range over the last 12 months. The table shows the "z-score" of the volatility of each market, i.e. how many standard deviations above (or below) the mean over the last 12 months each market's volatility is.

ASSET CLASS AREA LATEST

VOLATILITY LATEST

Z-SCORE REGIME

EQUITIES

North America 10.2% -0.6 low

Asia ex-Japan 13.8% 0.3 medium

Europe 11.4% -0.9 low

Japan (Nikkei) 32.1% 0.8 HIGH

Energy 23.3% 0.0 medium

Consumer Staples 13.8% 0.9 HIGH

Financials 15.9% -0.1 medium

IT 13.5% -0.2 medium

VOLATILITY OF VOLATILITY

Volatility of VIX 126% -0.0 medium

Volatility of VSTOXX 92% -0.2 medium

GOVERNMENT BONDS

Germany 5.1% 0.5 HIGH

US 3.8% -0.6 low

Japan 2.1% 0.7 HIGH

Italy 6.5% 1.6 HIGH

FX VS $

€/$ 7.5% -0.3 medium

€/Yen 7.6% -0.7 low

€/CHF 3.4% -0.9 low

€/£ 9.5% -0.3 medium

COMMODITIES

Oil (Brent) 47.7% 0.4 HIGH

Gold 17.3% 0.4 HIGH

Copper 26.9% 2.0 HIGH

PROPERTY

US 19.7% 0.9 HIGH

Europe 15.3% -0.5 low

Japan 18.9% -0.2 medium

ALTERNATIVES HFRX Global HF 3.1% -0.4 medium

Avg PE Fund 5.4% -0.7 low

KURTOSIS ZCF 1% left (vs -2.33 for normal curve) -1.95 0.9 low

CORRELATION Average market correlation with euro equities

5% -0.9 low

Summary volatility matrix

Volatilities rose back in almost all assets in

November; mostly driven by big moves in

underlying prices post the US presidential

election.

Slowly we are beginning to tick off the

long list of tail risks we have been

identifyied during the year. Both the US

Presidential election and the Italian

referendum yielded outcomes that

analysts had postulated as negative for

equity markets, and yet they rose on both

occasions. There is still a long list to get

through, including French and German

national elections, against a backdrop of a

possible post-Brexit breakup of the UK

and/or EU, the Fed’s starting to taper, the

Chinese debt bubble, another tech

bubble, rising inflation in the UK and US,

and further fallout from the lower oil

price in oil producing countries as deficits

remain high. Central banks remain all-

powerful, but it is only a matter of time

before the magic doesn’t work any more.

But it could be months or it could be

years.

2016 has been an unpredictable and

tumultuous year, with sub-$30 oil, Brexit

and Trump to name but a few. We think

everyone deserves a break; wishing you

all a very merry Christmas and a

prosperous new year.

4

GDP ESTIMATES FOR 2016, DEVELOPED COUNTRIES

GDP ESTIMATES FOR 2016, DEVELOPING COUNTRIES

The US presidential election hogged the limelight, and newsflow outside it was surprisingly light.

Donald Trump surprised pundits by winning the US presidential elections. Republicans also held onto both chambers of Congress. Markets also confounding pundits; equities and bond yields rose on a reflationary and anti-regulations theme, and Gold fell. US equities hit new record highs

The Egyptian Pound fell further after its floatation

India surprised the entire population by making 500 and 1,000 rupee notes, which make up over 80% of all currency in circulation, no longer legal tender

Valeant shares fell again after a profits warning

Samsung bought Harman for $8bn. Sunoco Logistics and Energy Transfer Partners agreed a $21bn merger.

US house prices rose to a new all time nominal high

The UK economy also continued its strength; unemployment hit a new 11 year low of 4.8% and inflation fell to just 0.9% despite the weakness of Sterling

Japan saw quarterly GDP grow by 2.2% annualised

OPEC finally managed to get an agreement on oil production cuts; prices rose.

2016 GDP estimates for developed countries were revised up for the UK and Spain.

Key News Major Volatility-Driving Events

5

2016 GDP growth forecasts for developing countries were marginally revised up for China, but marginally down for Russia, India, Brazil and Turkey.

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

Mar-15 Jun-15 Sep-15 Dec-15 Mar-16 Jun-16 Sep-16 Dec-16US UK Spain Germany Euro Area Japan France Italy

-4%

-3%

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

Mar-15 Jun-15 Sep-15 Dec-15 Mar-16 Jun-16 Sep-16 Dec-16

China India Turkey Russia Brazil

Kurtosis in the equity markets

Methodology

To capture a measure of both Skewness and Kurtosis we look at the Cornish-Fischer expansion, which gives a good measure of the tails of the equity market. (We use a 60-calendar day rolling basis). The underlying market we plot is the Eurostoxx 50, but other equity markets normally show very similar results.

We plot on the chart the expected Z-scores for 1% left tail (i.e. a 99% VaR) and a 1% right tail assuming a normal distribution: +/-2.33.

We also show the Cornish-Fischer expansion result for the same market. This indicates how far from a normal distribution each tail was.

On a long term basis on average the tails are slightly fatter than the normal distribution would suggest, which should not come as a surprise. What is perhaps more surprising is how much variation in fat-tailedness there has been: a daily 99% VaR has varied between -1 and -4.5 standard deviations over time. The biggest variations from +/-2.33 came in 2008 and 2010.

CORNISH-FISCHER EXPANSION OF EURO STOXX 50

The left tail of the eurozone equity market distribution continued to drift inside its normal level during the month, to -1.95 vs a theoretical normal -2.33. The right tail also was well behaved.

6

The left tail of the eurozone equity market distribution continued to drift inside its normal level during the month, to -1.95 vs a theoretical normal -2.33.

“

” -4

-3

-2

-1

0

1

2

3

4

ZCF 1% left Z 1% left ZCF 1% right Z 1% right

Average correlations remained low during the month.

Average correlation fell from 12% to 5% (low).

Note: The chart shows 30-day correlation over time between different markets and the pan-Euro equity market. Higher levels of correlation will in general lead to less ability to diversify risks, and higher portfolio volatility for given position holding volatility.

INTER-MARKET CORRELATIONS

MULTI-ASSET PORTFOLIO

We also look at a hypothetical multi-asset portfolio consisting of equities, bonds, gold, oil and hedge funds.

Average asset volatilities rose from 9.1% to 16.3% during the month, while the benefit of (multi-asset) diversification increased to -8.3%. In combination portfolio volatility rose from 4.7% to 8.0%.

Inter-market correlations with EU equities

↘ 7% AVERAGE CORRELATION

↗ 3.3% PORTFOLIO VOLATILITY

↘ 8.3% AVERAGE VOLATILITIES

7

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

North America Japan Bunds (negative) €/$ Average

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

Average asset Multi-asset portfolio Diversification impact

STOCK PRICE PERFORMANCE: REGIONS (LOG SCALES)

STOCK PRICE PERFORMANCE: SECTORS (LOG SCALES)

Equities Stock price

Sector price moves were unusually large.

Energy was +5.1% on the OPEC deal, Financials +7.5% on Trump’s anti-regulation drive, while IT fell -0.7% and Consumer Staples fell -5.3%.

Equity index price moves were mixed during the month.

North America rose +3.3% on the Trump presidency, Asia ex-Japan fell -1.7% and Europe ended the month down slightly at -0.8%. The Nikkei rose +5.1%; its second 5%+ month in a row.

8

↘ 0.8 % Europe

↗ 7.5% FINANCIALS

↗ 5.1% ENERGY

↘ 0.7% IT

↘ 5.3% CONSUMER

STAPLES

10,000

20,000

1000

2000

North America Europe Asia ex-Japan Japan (rh axis)

80

90

100

110

120

130

140

150

160

120

140

160

180

200

220

240

Energy Consumer Staples IT Financials, rh axis

EQUITY VOLATILITY: REGIONS

EQUITY VOLATILITY: SECTORS

Regional volatilities were all up on the month.. North America ended up to 10.2% (low), Asia ex-Japan up to 13.8% (low up to medium), Europe up to 11.4% (low) and Japan rose to 32.1% (low to high) although this was almost entirely driven by a big drop immediately after the US election followed by a similarly big rise the next day.

Sector volatility moves were likewise all upwards.

They ended at 13-16%, with Energy at 23%. All sectors ended with medium volatility, except Consumer Staples at high.

Equities Volatility

9

between 13-16%

All sector volatilities

32.1% NIKKEI

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

North America Europe Asia ex-Japan Japan (Nikkei)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Energy Consumer Staples IT Financials

Equity Implied Volatility Market-Implied Near Term Outlook

Note: Note: the implied/realised volatility ratio gives an indication as to whether the market sees an event in the next 30 days (the implied volatility period) which will increase realised volatility (implied/realised >100%, e.g. within 30 days prior to the Greek elections during the Greek crisis) or a period of relative calm after high realised volatility (implied/realised <100%, e.g. immediately after Draghi’s calming “whatever it takes” comments).

Implied Volatility

Implied volatilities dropped on the month as the US election passed. The VIX fell from 17.1 to 13.3 while European implied volatility (VSTOXX) was relatively unchanged at 21.4.

Implied vs. Realised Volatility

((European equity) implied volatility was flat on the month while realised volatility rose. So the ratio of implied/realised fell back slightly from 189% to 170%.

Interestingly despite the US election passing, this ratio is still well above a neutral level, suggesting that the market expected there would continue to be volatility-inducing news over the next 30 days compared to the last 30 days; the Italian referendum being one possibility.

IMPLIED VOLATILITY

IMPLIED VS. REALISED VOLATILITY

13.3 VIX

↘19%

21.4 VSTOXX

IMPLIED/REALISED

VOLATILITY

10

0

5

10

15

20

25

30

35

40

45

VSTOXX VIX

-

50%

100%

150%

200%

250%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Implied Realised Implied / Realised (rh axis)

Trump victory(Nov)

Fed raises,ECB

disappoints (Dec)

BoJ goes negativeOil price trough(Jan)

Fed hints at June rate rise (May)

Brexit (Jun)

Fed hints at rate rise

(Sep)

Prices

Government bond prices were down on the month on higher expected inflation in the US as a result of a Trump presidency.

US bonds dropped -3.4%, while German bonds fell -0.7%, and Japan lost -0.8%.

Volatility

Volatility moves were all upwards during the month.

German bond volatility rose to 5.1% (medium up to high) while Japanese bonds rose to 2.1% (low up to high) and the US also rose to 3.8% (low compared to the last 12 months).

PRICES OF 10Y BOND FUTURES

SPANISH 10Y BOND YIELD

VOLATILITY OF 10Y BOND FUTURES

Fixed Income 10-Year Government Bond Futures

11

Spanish bond yields also rose sharply during the month to 1.6%.

125

130

135

140

145

150

155

160

165

170

Germany US Japan Italy

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Spain Yield

0%

1%

2%

3%

4%

5%

6%

7%

8%

Germany US Japan Italy

Note: The charts show currencies vs. the €. Axes on the first chart are inverted to show conventional currency quotations, but with higher on the chart representing a stronger currency vs. the euro.

Prices

FX moves were again large during the month.

The Dollar rose +3.3% against the euro on higher rate expectations, while Sterling bounced back +5.4%, and the Yen again fell -5.1%.

Volatility

FX volatility moves were again mixed. €/$ rose to 7.5% (low up to medium), but €/£ fell to 9.5% (medium), while €/Yen fell to 7.6% (low relative to 12 month averages.)

FX RATES VS. €

VOLATILITY OF FX RATES VS. €

Foreign Exchange

12

↗ 7.5% € vs. $

↘ 9.5% € vs. £

↘ 7.6% € vs. ¥

↘ 5.4% € vs. £

↘ 5.1% € vs. ¥

↗ 3.3% € vs. $

0.65

0.70

0.75

0.80

0.85

0.90

1.00

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1.40

1.45

1.50€/$ €/JPY /100 €/£ (rh axis)

0%

5%

10%

15%

20%

25%

30%

€/£ €/Yen €/$

(Equity) Options Option volatility is mainly driven by the volatility of volatility and moves in prices of the underlying instruments affecting options’ deltas.

Volatility of Implied Volatility

Volatility of implied volatility rose, with the US ending at 126% (low up to medium) and Europe at 92% (also low up to medium relative to the last 12 months.) Volatility of volatility could quite probably have been a driver of option volatility during the month.

Major (Regional Equity) price moves

(Equity) prices saw big swings during the month.

Underlying price moves are also likely to have been a big driver of option volatility.

VOLATILITY OF VOLATILITY

CHANGE IN PRICES OF EQUITY INDICES, 30 DAYS

126% US

92% EUROPE

Note on Treatment: Options show more complex behaviour than the other instruments we look at in this report, so we make some simplifying assumptions. As Calls and Puts are in effect polar opposites and in and out of the money options behave very differently, it is hard to generalise all options’ behaviour. However, we look at the two key drivers: volatility of implied volatility and major price movements of the underlying security.

Implied volatility (via an option's Vega) drives option prices, so a big indicator of option price volatility is the “volatility of implied volatility”.

But usually the biggest driver of individual option prices is the movement of the underlying (via the option Delta): a move in either direction will cause the option to go more in or out of the money (and a corresponding change in the option’s Delta and price volatility). As a proxy for this, we look at the 30-day price swing of equity market indices; options on bonds or FX could of course behave differently. The 30-day period is relatively close to the time to maturity of many options. Calls and Puts will respond in opposite fashions: calls becoming more volatile (relative to the size of the underlying notional) as prices rise.

Note on Convertibles: Convertibles are in effect a combination of a bond and a call option, with the bond portion usually making little contribution to the instrument volatility unless the option is significantly out of the money. As such, convertible portfolios’ volatilities will tend to behave similarly to call option portfolios, and this commentary can be applied to convertibles as well as options. 13

0%

50%

100%

150%

200%

250%

Volatility of VIX Volatility of VSTOXX

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

North America EU Asia ex-Japan Japan

Commodities

Note: all prices refer to near futures rather than spot with the exception of iron ore which is a spot price.

Prices

Commodity price moves were large during the month.

Oil rose +4.5% on the month on the OPEC agreement. Gold fell -8.0% on rising US bond yields while Copper was +18.9%, partly on rising growth estimates and Trump’s election, but also partly attributed to speculative trading.

Volatility

Volatility changes were up for all assets; Oil finished significantly up at 48% (low up to high) while Gold rose slightly to 17% (low up to high) and Copper rose to 27% (also low to high).

COMMODITIES PRICES

COMMODITIES VOLATILITY

↘ 8.0% GOLD

OIL

14

↗ 18.9% COPPER

↗ 4.5%

600

700

800

900

1,000

1,100

1,200

1,300

1,400

30

40

50

60

70

80

90

100

Oil (Brent) Copper (indexed) Iron Ore Gold (rh axis)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Oil (Brent) Copper Gold

Real Estate (Real Estate Share Prices)

Note: Note that for property we look at indices of the share prices of REITs, and not the underlying property directly, for which little real-time data is available. This is usually consistent with funds which tend to invest in property indirectly, e.g. via REITs or property companies.

As REITs are usually focused on commercial property, residential property may also follow a slightly different pattern to that discussed in this article.

Real estate equities price moves were again downwards outside Japan on the prospect of higher interest rates.

Europe was down -1.0%, the US down -2.1% while Japan was again up at +5.2%.

Volatility moves were mixed.

Europe fell back to 15.3% (medium down to low) while the US rose to 19.7% (medium up to high). Japan was sharply up at 18.9% (low up to medium).

REAL ESTATE (REIT) PRICES

REAL ESTATE (REIT) VOLATILITY

↘ 1.0 %EUROPE

↘ 2.1% US

↗ 5.2% JAPAN

15

2,400

2,600

2,800

3,000

3,200

3,400

3,600

1,800

1,900

2,000

2,100

2,200

2,300

2,400

Europe Japan (rh axis) US (rh axis)

0%

10%

20%

30%

40%

50%

60%

Europe Japan US

PE funds had a seventh consecutive positive month, at +0.3%. The average hedge fund rose fractionally.

The global hedge fund index volatility rose to 3.1% (low up to medium) while the volatility of an average of PE fund fell slightly again to 5.4% (medium down to low by the standards of the last 12 months).

ALTERNATIVES PRICES

AI VOLATILITY

Alternatives

5.4% AVERAGE PE FUND

3.1% HFRX volatility

16

900

950

1,000

1,050

1,100

1,150

1,200

1,250

Global Hedge Funds (EUR) Avg PE Fund (indexed)

0%

2%

4%

6%

8%

10%

12%

14%

Global Hedge Funds (EUR) Avg PE Fund

Definitions

To avoid repetitions, the term volatility refers to annualised, 30-day average realised volatility in local currency unless otherwise specified. As such, it may be lower than, and lag, shorter-term market volatility in times of high market volatility.

Charts show data up until 30th November 2016, and the commentary was written on or before 12th December 2016.

Disclaimer

The commentary does not constitute, and is not intended to constitute, investment advice.

Any views expressed in this report are based on historical market data and as such cannot be interpreted as being forward-looking, or to constitute forecasts. Past movements are not necessarily indicative of future movements.

Employees of IRML/ARKUS FS may hold positions in securities mentioned.

All expressions of opinion reflect the judgment of IRML/ARKUS FS at this date and are subject to change. Information has been obtained from sources considered reliable, but we do not guarantee that the report is accurate or complete.

This document is not for US clients or distribution to the US.

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