Investcorp Hedge Fund Strategy Environment Report · INVESTCORP Investcorp Hedge Fund Strategy...

INVESTCORP Investcorp Hedge Fund Strategy Environment Report | 1st Quarter 2014INVESTCORPBahrainLondonNew YorkAbu DhabiRiyadh

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Investcorp Hedge Fund Strategy Environment Report

1st Quarter 2014

HEDGE FUNDS

INVESTCORP Investcorp Hedge Fund Strategy Environment Report | 1st Quarter 2014

Page

Section 1: Hedge Fund Strategy Outlook 1

Section 2: Macro 15

Section 3: Hedge Equities 39

Section 4: Credit 47

Section 5: Event Driven 65

Section 6: Convertible Arbitrage 69

Section 7: Fixed Income Relative Value 75

Section 8: White Paper: Credit Investingin a Rising Rate Environment 83

Table of Contents


Macroeconomic Outlook

As we enter 2014 the global economy appears to be on much stronger footing than we have seen in recent years

While we are not yet at pre-crisis levels of GDP, growth expectations are expected to be on a stable, if somewhat modest, path higher across most regions

Consensus expectations for world 2014 GDP are expected to be 3.1%

Asia remains the engine of global growth, particularly North East Asia, driven by China which is expected to grow at 7.5%

While significant risks are still present, Europe is expected to move into positive growth territory in 2014

There is certainly now a realization that policy makers are very serious to take action if required and this in itself has diminished the tail risks we have lived with in Europe for the past three years

STRICTLY CONFIDENTIAL | 1


Hedge Fund Strategy Outlook

Investcorp’s investment strategy is driven by our in-house proprietary hedge fund research effort. The research studies thedrivers of individual hedge fund strategies and measures their attractiveness through a variety of indicators, which are highlightedin the following pages.

Strategy Attractiveness Score(Scale 1 t0 10)

Trend(Recent trend in

change to scores)

Special Situations / Event 9(Q4 2013: 8) Positive

Hedge Equities 8(Q4 2013: 7) Positive

Macro 7(Q4 2013: 6) Modestly Positive

Structured Credit 6(Q4 2013: 7) Modestly Positive

Equity Market Neutral 6(Q4 2013: 5) Neutral

Fixed Income Relative Value

5(Q4 2013: 5) Neutral

Convertible Arbitrage 4(Q4 2013: 5) Modestly Negative

CTA 4(Q4 2013: 5) Modestly Negative

Corporate Credit 4(Q4 2013: 4) Modestly Negative

Corporate Distressed 4(Q4 2013: 4) Modestly Negative

Attractiveness increased

from previous quarter

Attractiveness decreased

from previous quarter

Attractiveness did not change



Hedge Fund Strategy Outlook

We have a “Positive” rating on Special Situations / Event Driven strategies predicated on strong corporate balance sheets inthe US that are flush with cash in excess of $ 1.9 Trillion with corporate profits nearing 11% of GDP, but have limited paths togrowth in a world of slowing revenue (8.3% in 2011 to 2.9% in 2013) and an environment of peak margins where EBITDA marginshave fallen to 18.8% from their 19.4% peak in 2010. We believe that increased shareholder pressure (or activism) will lead to anincrease in event-driven activites. 2013 was a very strong year for investor activism with 279 instances up from 230 in 2012, M&Awhere there were 1426 small and midcap deals in up from 1201 in 2012, special dividends, and corporate buybacks and weexpect this trend to persist into 2014.

We have a “Positive” rating to Hedge Equities and see an expansion in the opportunity space for long-short equity managers.After the strong performance by developed equity markets in 2013 especially the US and Japan, we see greater opportunities inEurope and Asia in 2014. We see increased dispersion in valuation metrics across equity markets with MSCI World trading at18.83, China H shares at 7.5 and the US at 11.98. There has also been significant variation in equity return drivers, with multipleexpansion driving most of the 2013 equity returns in the U.S and Europe (76% and 87% respectively) and multiples contractingand earnings growth driving stock returns in Japan and Asia (110% and 425% respectively). We believe this trend will continueand lead to a greater dispersion of global equity returns in 2014. Correlations across major equity markets that hovered around70% to 90% have subsided to around 50% and we now see opportunity for variable bias, global managers to profit from alteringmarket exposures, geographical allocation and stock selection.



Hedge Fund Strategy Outlook (Contd.)

We’re “Modestly Positive” on Macro. While Macro has disappointed over the last 12-18 months given the coordinated monetarypolicy accommodation across the world, we see 2014 providing a greater opportunity set for managers as national policiesdiverge, and lower cross-market correlations set in. Furthermore, withdrawal of quantitative easing by the Federal Reserve isexpected to have a disproportionate impact on emerging markets, which could also benefit macro managers with EM expertise.

We continue to have a “Modestly Positive” rating on Structured Credit as a strategy, but have downgraded our outlook. Weexpect residential mortgages to underperform their more recent past as well as other parts of the structured credit markets. Wecontinue to favor CMBS over RMBS, specifically mezzanine paper. Specialized ABS markets also continue to be attractive,especially TRUP CDOs, but these opportunity sets admittedly remain small. Our view on structured credit is also tempered byrisks of a rate rise in the US. We are positive on the European CMBS markets based in UK and Germany as the European creditmarkets heal over the near future.

We remain “Neutral” on EMN as we continue to see commoditized factor models delivering sub-optimal alphas in the developedmarkets. However, returns to non-market factors are attractive in other parts of the world, especially the Asia-Pacific. We alsocontinue to favor managers who are globally diversified and can time their factor exposures. We continue to have a wait andwatch approach to statistical arbitrage managers.

Our “Neutral” rating on Fixed Income Relative Value is unchanged. We continue to structurally like Relative Value strategiesas capital shrinkage relative to the opportunity set makes many strategies interesting, but a lack of realized volatility has madeit challenging in the recent past to benefit from this. The current three-track world of economic growth (US vs. EM vs. Europe)should result in divergent monetary policies and create an environment conducive to the re-shaping of yield curves globally,thus providing a rich opportunity set for FIRV managers.



Hedge Fund Strategy Outlook (Contd.)

The “Neutral” rating to Convertible Arbitrage is also unchanged. Our outlook for convertible bonds as an asset is modestlypositive because of our view on global equities, but we’re neutral on the arbitrage. For arbitrage portfolios, credit spreads remaintight and close to historical average discounts-to-theoretical are unattractive, and volatility – both realized and implied – remainsat cyclical lows. We do, however, see some improvements in the issuance calendar which could provide some extra returnopportunities.

We maintain a “Neutral” ranking on CTAs. Recent structural suppression of volatility, particularly in fixed income markets due toquantitative easing, combined with potential long-term reversals of fixed income markets have hampered quantitative trend-following models. With this being said, we continue to prize CTAs’ ability to diversify risks and provide downside protection if themarkets were to face any turbulence.

We are “Modestly Negative” on both Corporate Credit and Distressed, as valuations fully reflect the low default-rateenvironment and strong corporate balance sheets in the US. A low distressed ratio of just 5.2% currently provides very littleopportunity to earn systematic risk premium from this strategy. We do have a more favorable view on European distressed versusUS distressed. Higher expected default rates and the fragmented jurisdictional presence across the continent create an addedlevel of complexity, but also a more robust opportunity set.



Special Situations / Event Driven

We are positive on Special Situations / Event Driven equity strategies and have upgraded our ratings for the quarter. This is predicated on strong corporate balance sheets, a low interest rate environment, increased corporate risk appetite and increased activism. We believe these factors will lead to improved deal flow and corporate balance sheet restructuring activities that could provide a conducive environment for event managers

Driver of Strategy Returns Comments

Attractiveness Score

(Scale 1 to 10)

Valuations

Valuations for Event Driven and catalyst-oriented equities remain compelling. Merger Arbitrage spreads have been intermittently attractive, but not on a standalone basis.

8

Supply

Improved capital market environment is resulting in companies taking measures to unlock value, creating a significant supply of opportunities. Volume of M&A deal flow has been improving and could pick up further with increased risk appetite by companies.

9

CapitalRisk capital is available as many Event Funds have liquidity and are investing in their respective strategies

9

Liquidity

Strategy does not provide liquidity to the market. As market liquidity is healthy, the environment for the strategy should get better.

8

Financing Not an issue. This strategy typically does not use significant leverage.

1. Median returns of Investcorp’s strategy peer group. Strategy peer groups are created by Investcorp and are comprised of funds that Investcorp has judged to be relevant for each strategy.Source: Investcorp, US Federal Reserve

249387 430 433 498

513

696 733 768

930

0

200

400

600

800

1,000

1,200

1,400

2009 2010 2011 2012 2013

$200M – $5B Transactions (count) Small-Cap ($200M-$1B)Mid-Cap ($1B-$5B)

‐20%‐15%‐10%‐5%0%5%

10%15%20%25%30%

Jan‐01

Jul‐0

1Jan‐02

Jul‐0

2Jan‐03

Jul‐0

3Jan‐04

Jul‐0

4Jan‐05

Jul‐0

5Jan‐06

Jul‐0

6Jan‐07

Jul‐0

7Jan‐08

Jul‐0

8Jan‐09

Jul‐0

9Jan‐10

Jul‐1

0Jan‐11

Jul‐1

1Jan‐12

Jul‐1

2Jan‐13

Jul‐1

3

Median 12‐Month Rolling

Returns 1Event Driven Strategy



Hedge Equities

We are positive on Hedge Equities for both fundamental and flow-related reasons. Valuations richened in the US, Japan and Europe through 2013, but are not overly challenged, relative to their historical averages. We see great divergence in returns across markets and believe this is a good environment for global players who can either allocate across markets or excel at security selection. The trend of rising correlations, which was a negative for the strategy in recent years, has turned both across and within markets. This should make security selection also more profitable.



(Scale 1 to 10)

ValuationsThe rally this year has richened equity valuations, but they are reasonable relative to longer-term periods.

8

Earnings

While earnings are healthy, momentum is declining. Furthermore, margins are at cyclical peaks and could decline going forward in the US. At this stage of the economic cycle we expect significant upside in Europe, Japan and in relative value plays in emerging markets.

8

Momentum / Sentiment

Short-term momentum has been positive, and sentiment has become quite bullish. While this can be seen as a contrarian indicator we see good reason for the optimism and fund flow dynamics continue to favor equities.

9

Macro Backdrop

The World GDP forecasts have been raised by most forecasters with high income economies expected to grow. Tails risks remain in Europe and emerging markets.

7

Liquidity and

Financing

Not an issue. Most managers use little leverage, well within prescribed limits. Liquidity is also not a significant issue in this strategy.

9

1. Median returns of Investcorp’s strategy peer group. Strategy peer groups are created by Investcorp and are comprised of funds that Investcorp has judged to be relevant for each strategy.Source: Investcorp, Bloomberg

(24)

(18)

(12)

(6)

0

6

12

18

24

‐4%

‐3%

‐2%

‐1%

0%

1%

2%

3%

4%

2000

: Q1

2000

: Q3

2001

: Q1

2001

: Q3

2002

: Q1

2002

: Q3

2003

: Q1

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: Q3

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: Q1

201 0

: Q3

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: Q1

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: Q3

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: Q1

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: Q3

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: Q1

2013

: Q3

Average Qua

rterly Equ

ity Dispe

rsion

Average Med

ian Qua

rterly Returns

US Hedge Equities Strategy

ReturnsDispersion



Global Macro

Our outlook for Global Macro is modestly positive. We have seen early signs that macro managers are now willing to take on more risk as policy uncertainty and the “risk on / risk off” environment abates. Managers able to play equities aggressively in 2013 fared well; however, increased fixed income volatility and yield curves normalizing may presage further opportunities in fixed income trading. Policy dispersion between the US, Europe, Japan and emerging makerts should also offer opportunities in both FX and fixed income trading.



(Scale 1 to 10)

Fundamentals

We are increasingly seeing that fundamentals and not just aggressive central bank intervention driving behavior of risk assets. In addtion, we see macro managers taking on more risk looking to profit from these opportunities.

7

Trends

After being choppy over the last several years, markets in recent quarters have begun to exhibit some trend. Gradual tightening of monetary policy by the Fed should provide a fertile environment for global macro players to trade around inflection points and profit from them.

6

LiquidityNot an issue. Most managers trade exchange traded instruments which have very high liquidity.

9

FinancingNot an issue. Most managers trade exchange traded instruments which have no financing risk.

9


‐5%

0%

5%

10%

15%

20%

25%

30%

Jan‐01

Jul‐0

1Jan‐02

Jul‐0

2Jan‐03

Jul‐0

3Jan‐04

Jul‐0

4Jan‐05

Jul‐0

5Jan‐06

Jul‐0

6Jan‐07

Jul‐0

7Jan‐08

Jul‐0

8Jan‐09

Jul‐0

9Jan‐10

Jul‐1

0Jan‐11

Jul‐1

1Jan‐12

Jul‐1

2Jan‐13

Jul‐1

3


Returns 1Global Macro Strategy

RecessionRecovery & Growth Recession Recovery

Slowdown/Recession Recovery



Structured Credit

We remain modestly positive on Structured Credit, but have downgraded our score. We believe the strategy provides adequate opportunities across both legacy residential and commercial-based assets, but we are cautious because prices have increased off depressed levels and certain securities have longer duration given slower pay-downs. Furthermore, legacy CLO and other select ABS opportunities provide an additional tailwind.



(Scale 1 to 10)

Valuations

Legacy credit still trades at a relatively large discount to par which should partially normalize as these instruments move closer to maturity.

6

Supply

Legacy supply is still dominant in the market. However there are also some new issues that have come to market. This is expected to increase in the coming years.

6

Capital

Risk capital is available as a number of new hedge fund players have entered the market and raised capital in recent years.

6

Liquidity

Current liquidity is good relative to recent history. This is a less liquid asset class, especially when dealing with mezzanine securities.

6

Financing

Historically, some participants have used leverage in this strategy (and have sustained heavy losses). We evaluate this opportunity only on a unleveraged basis, therefore, financing should not be an issue.


(2,500)

(2,000)

(1,500)

(1,000)

(500)

0

500

1,000

1,500

2,000

2,500

‐2%

‐2%

‐1%

‐1%

0%

1%

1%

2%

2%

3%

2003

: Q1

2003

: Q3

2004

: Q1

2004

: Q3

2005

: Q1

2005

: Q3

2006

: Q1

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2013

: Q1

2013 : Q3

Average Qua

rterly High Yield Sp

rea d

Average Med

ian Qua

rterly Returns

Structured Credit Strategy

Returns

HY Spread



Equity Market Neutral

Our outlook for the EMN strategy remains neutral. Valuation spreads are slightly above their historical averages; return dispersions are rising and correlations are declining. These trends suggest normal returns for the strategy going forward. We see strong opportunities outside the core of US, Europe and Japan – i.e. Asia and developing Europe. In addition, we see liquidity and flows improving in Europe that benefit both momentum and relative value strategies.



(Scale 1 to 10)

Dispersion

Average correlations between stocks, which have been high, are now coming off high levels recently. This implies that investors are beginning to discriminate between stocks on a fundamental basis and not macro and liquidity considerations.

6

Capital

Capital in the strategy has reduced considerably. Many Hedge Funds and Bank Proprietary trading desks have exited the business. Furthermore, liquidations have occurred in long-only strategies

5

LiquidityNot an issue. Most managers trade exchange traded instruments which have very high liquidity.

Financing Leverage levels in the strategy have normalized. 5


‐4%

0%

4%

8%

12%

16%

Jan‐01

Jul‐0

1Jan‐02

Jul‐0

2Jan‐03

Jul‐0

3Jan‐04

Jul‐0

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Jul‐0

5Jan‐06

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Jul‐1

0Jan‐11

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1Jan‐12

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3


Returns 1Equity Market Neutral Strategy




We are neutral on the core FIRV strategy. There has been an increase in both realized volatility and implied volatility – both in treasury bonds and in swaps – and FIRV strategies that are positioned to trade the convexity of the curve and volatility surfaces should continue to do well in the coming months. There is adequate liquidity and money market rates reflect improvement in financial conditions. We expect more dispersion in returns earned by arbitrage managers because of the increased volatility.



(Scale 1 to 10)

ValuationsSpread relationships have not yet normalized and there are few opportunities to trade the basis across markets.

5

Supply

Record new issuance of sovereign debt and Quantitative Easing programs have had a Net zero impact on the opportunity set. The new supply has been easily absorbed and the Federal Reserve purchases of debt reduced the volatility and arbitrage opportunities in the market.

5

Capital

Limited capital chasing the opportunities. Many Hedge Funds and Bank Proprietary trading desks have exited the business.The average spreads to various relative value strategy have improved, but so has the costs of putting on these trades

7

Liquidity

Strategy does not take liquidity risk except when trades are put on using exotic derivatives. The downside risk on cash market instruments is the changes being wrought on the Repo markets.

6

Financing

Overall leverage levels are significantly less than pre-crisis levels. This is a function of prime brokers necessitating high minimums for fixed income accounts.

6


(120)

(60)

0

60

120

180

240

‐1.0%

‐0.5%

0.0%

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1.0%

1.5%

2.0%

2000

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: Q1

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Average Qua

rterly M

errill R

ate Im

plied Vo

l Ind

ex

Average Med

ian Qua

rterly Returns

Fixed Income Relative Value Strategy

Returns

MOVE Index



Convertible Arbitrage

We are neutral on the strategy as valuations have richened and credit spreads have tightened to mean levels. However, managers are seeingidiosyncratic opportunities in certain attractively-priced new issues and, given the favorable environment for recapitalization and M&A activity, therehas been an uptick in new issuance that will provide some pick up to what would be normal returns for the strategy. Convertible bonds as an assetclass will continue to do well on the back of improving equity markets, but we remain concerned about the meager returns to assuming credit risk.



(Scale 1 to 10)

Valuations

Discounts have narrowed significantly and most convertible issues are fairly valued. Valuations are now higher than the long-term average.

4

Supply

New issuance has begun to pick up as a spate of attractively-priced new issues came to the market and were well received. New issues are still lower than long-term historical averages, and the size of the market after shrinking for a number of quarters grew in size in Q4.

5

Capital

Convertibles are not a crowded space. Only 3% of total hedge fund assets are invested in Convertibles. Additionally, long-only buyers have stepped in and are now an important part of the market.

7

Liquidity

Liquidity provision is an important feature of the strategy. Prime broker financingthat drives financing liquidity has been good.

6

Financing

Overall leverage levels have risen somewhat recently for the strategy, however, they are lower than pre-crisis levels and do not presentimminent risk of financing led deleveraging.

5


(2,500)

(2,000)

(1,500)

(1,000)

(500)

0

500

1,000

1,500

2,000

2,500

‐5%

‐4%

‐3%

‐2%

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0%

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5%

2003

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Average Qua

rterly High Yield Sp

read

Avera ge Med

ian Qua

rterly Returns

Convertible Arbitrage Strategy

Returns

HY Spread



Corporate Credit

Our outlook on Corporate Credit is modestly negative. Compensation for credit risk is close to average, but the rising rates outlook is a major risk for this asset class in the US. Emerging market credit is overly exposed to what happens to US interest rates, and Europe spreads have ground lower but do provide some opportunity for attractive risk-adjusted return.



(Scale 1 to 10)

Valuations

Corporate Yield to worst are at close to the lowest levels they have been in the last twenty years. We see spreads contracting a little because of improved economic conditions; but that will be accompanied by rising rates which will more than compensate.

3

Supply

There has been an unprecedented amount of issue of high yield credit over the past two years and a general deterioration in covenants attached. Supply of bonds in Europe should be healthy.

5

Capital Capital is plentiful relative to the opportunity set. 5

Liquidity Strategy does provide liquidity to the market. The liquidity market is normal. 6

Financing Not an issue. This strategy typically does not use leverage.


250

450

650

850

1050

1250

1450

1650

1850

2050

2250

0%

10%

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30%

40%

50%

60%

70%

80%

90%

100%

Jan‐03

Jan‐04

Jan‐05

Jan‐06

Jan‐07

Jan‐08

Jan‐09

Jan‐10

Jan‐11

Jan‐12

Jan‐13

High

Yield Bon

d Yield (b

ps)

Distressed

Ratio

Bond Yield & Distressed Ratio

Distressed Ratio Bond Yield



Corporate Distressed

Our outlook on Distressed Credit is modestly negative. U.S. default rates are low, suggesting a meager opportunity set for managers. A higher portion of the return is expected to be delivered from legacy bankruptcy resolutions and late-stage corporate and asset liquidations.



(Scale 1 to 10)

Valuations

Valuations have risen recently. While companies have restructured and generally have less leverage, a weaker economic environment could negatively impact valuations.

4

Supply(Defaults and Restructuring Opportunities)

The supply of new defaulted debt has fallen sharply. The default rate remains below 2%.

3

Capital Capital is plentiful relative to the opportunity set. 2

Liquidity Strategy does provide liquidity to the market. The liquidity market is normal. 6

Financing Not an issue. This strategy typically does not use leverage.


(0.8)

(0.6)

(0.4)

(0.2)

0.0

0.2

0.4

0.6

0.8

‐4%

‐3%

‐2%

‐1%

0%

1%

2%

3%

4%

2000

: Q1

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: Q3

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201 0

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Average Qua

rterly Distressed Ra

tio

Average Med

ian Qua

rterly Returns

Distressed Strategy

ReturnsDistressed Ratio



Macro


Macro Environment Report July 2013 INVESTCORP Macro Environment Report | 1st Quarter 2014

Global Economic Review and Outlook

Global Economic Summary As we enter 2014 the global economy appears to be on a much stronger footing than we have seen in recent years. Whilst we are not yet

at pre-crisis levels of GDP, growth expectations are expected to be on stable path higher across most regions. Whilst significant risks are still present, Europe is expected to move into positive growth territory in 2014. It is interesting that in 2013 we witnessed a strong rally in peripheral European soveriegn bonds which has continued into 2014 indicating that investors are willing to overlook several key events that could have set markets on a very different trajectory. These included issues of establishing a coalition government in Italy; haircuts imposed on bank depositors in Cyprus and a rejection of austerity measures in Portugal, all of which proved to be non-events. In the US, the year started off with fears over automatic spending cuts dominating sentiment; however a combination of accomodative monetary policy, healthy corporate balance sheets and an improving economy acting bolstered equity market performance in 2013.

The 4th quarter ended on a strong note despite being marked by the US Federal Reserve deciding to commence the tapering of its $85B asset purchase programme. This was largely priced into risk assets by the time the decision was announced and markets reacted very differently to the summer sell-off in bonds and shake-up in EM assets when Bernanke first spoke of tapering on May 22nd. The S&P ended the quarter up +10% and the year up +32% posting the strongest year since 1997. The MSCI World finished the quarter up +7.6% and the year +24%. Bond markets suffered losses in 2013 marking the largest gap in performance between equities and bonds since the financial crisis.

We are seeing a broad acceleraton of economic data across the major regions, that continues to provide a tail-wind to markets. Broadly consumer and business sectors have shown a positive trend for US, Europe, Japan and China, whilst government, fiscal and monetary sectors have been more mixed. The US labour market has been on an improving trend with the exception of the December payroll number which came in signicantly below expectations. Of slightly more concern is the longer term trend of lower labour force participation rate which the Federal Reserve is likely to watch closely as they continue with tapering. Global Purchasing Managers Indices (PMI’s) remain above the expansionary levels of 50 and are, in fact, at the highest aggregate PMI levels since June 2011. The US housing market remains robust. The Case-Shiller index rose 13.6% y-o-y to October recording the highest gain since 2006 whilst home sales and housing starts continue to improve. The US Consumer is benefitting from a wealth effect of both rising house prices and stock market gains. Household net worth increased by $1.9 trillion in the third quarter 2013 and has increased by $19 trillion since the trough four years ago. The housing market is a key conduit for consumption both through the positive wealth effect and as a source of collateral for borrowing and spending – so is clearly a cornerstone in the continued recovery of the US economy.

Chinese GDP expanded at 7.8% annual rate in Q3. This marked a strong pickup after the policy induced slowdown earlier in the year and the SHIBOR spike in June as the government orchestrated a liquidity squeeze on banks to slow lending to the shadow banking sector. China concluded its Third Plenum setting out an aggressive agenda of reforms to rebalance the economy. The economy weathered expectations of a policy induced slowdown exceptionally well during 2013 but the latest data out on China has shown some softness although not indicative of a sharp slowdown in activity.



Next to the US recovery and Chinese growth, “Abenomics” continues to be a major driver of markets and was responsible for some of the large asset price shifts that we witnessed in 2013. The Japanese economy continues to show evidence of strengthening but at a slower pace than anticipated. 2014 will be an important year for Abe and the Bank of Japan to navigate with a further sales tax hike planned for April and rolling off of some of the powerful fiscal stimulus enacted in 2013. There are varying estimates of how much of a drag this could be on growth with the IMF and OECD forecasts being as high as -2.5% but several bank research houses are predicting a smaller headwind for 2014.

Our outlook is that we remain in a modest global growth environment of around 3% with Central Banks still accomodative and prepared to backstop any signficant downside risks to the global economy. At the same time there are several tail winds supporting the current growth such as lower oil prices, lower fiscal drag in the US and Europe and potential higher corporate activity and business investments. Our current key concerns are:

(1) Risk of failure to Abenomics – Japan appears to have turned a corner in reversing decades of deflation but is entering a phase where we would need to see real wage growth to sustain the momentum in CPI. Corporates need to play a much larger role in boosting exports. Thus far, export volumes have been weaker than expected (considering the weaker JPY) and SME’s which account for over 70% of employment have not benefited in the same manner from a weaker JPY as larger firms have instead having to absorb cost inflation.

(2) Emerging Markets – The growth acceleration in China could result in tighening which has already begun for credit in the economy. Additionally, countries such as India, Turkey and Russia have have had to tighten monetary policy to defend currencies despite weaker growth which would normally require more expansionary policy. We remain alert for any hit to confidence at a delicate stage in the global economic recovery. The partial carry trade unwind seen in May/June provided a signal of how much capital has flowed into emerging markets that could reverse.

(3) European Tail Risks – Europe looks to have stablized at a low level of activity and is looking more positive on several growth fronts.

Even Greece managed to positively surpise with authorities meeting fiscal targets with a reasonable margin and coalition government survivng a number of challenges in 2013. Nevertherless we cannot ignore disparate conditions between Germany and the periphery, unemployment over 25% in certain areas, interlink between indebted soverign balance sheets and banking sector, weak inflation and an ECB that is not in a hurry to ease without a crisis and lagged effect of a strong EURO on the region’s competiveness.

(4) US Equity Valuations – US equities are no longer cheap by historical standards after the market rally in 2013. The gap between the

S&P earnings yield and investment grade credit and US treasuries have narrowed significantly from a year ago. Corporate balance sheets are healthy and corporate activity is picking up but multiple expansion is conditional on profit margins and earnings growth being able to keep pace. We remain watchful for signs that the corporate capex cycle will pick-up to fill in a much needed part of the business investment led component to economic growth story.



(5) Tapering “Glide Path” – Interest rates yields look set on a path higher withtthe FED beginning QE. Whilst we view a sharp rise in yields as a potential risk we believe the FED will move forward cautiously and pay very close attention to the economic data and remain ready to slow down the speed of tapering should it be necessary.

Consensus GDP Forecasts: World real GDP forecasts for 2013 / 2014 have remained at comparable levels from 3 months ago with expectations of 2% growth

in 2013 and 2.8% in 2014. The US, Eurozone and China have been revised up for 2013. While Asia remains an engine of growth, its pace has slowed. China is expected to grow at 7.7% in 2013 and 7.5% in 2014

The Eurozone is expected to record a positive growth rate of +1% in 2014 compared to contracting by -0.4% in 2013.

IMF forecasts (latest October 2013) is for World GDP to grow by 3.6% in 2014 up from 2.9% in 2013 and for the US to grow by 2.6% up from 1.6% in 2013. Europe is expected to grow by 1% following a contraction of -0.4% in 2013.

*Latest data points- IMF forecasts are as of latest outlook published in October

2007 2008 2009 2010 2011 2012 2013 E Change 3M 2014 F Change 3MWorld 3.9 1.6 ‐2.4 4.0 3.0 2.2 2.0 0.0 2.8 0.0US 1.8 ‐0.3 ‐2.8 2.5 1.8 2.8 1.7 0.1 2.6 0.0Eurozone 2.9 0.4 ‐4.4 2.0 1.6 ‐0.7 ‐0.4 0.0 1.0 0.0Japan 2.2 ‐1.0 ‐5.5 4.7 ‐0.5 1.5 1.7 ‐0.2 1.6 0.1Asia 10.3 7.1 6.0 9.4 7.6 6.2 6.5 0.1 6.3 0.0LatAm 5.7 4.2 ‐1.7 6.4 4.2 2.9 2.4 ‐0.2 2.9 ‐0.4BRIC's 10.7 7.7 4.7 8.8 7.1 5.6 5.7 0.0 5.7 ‐0.1China 14.2 9.6 9.2 10.4 9.3 7.7 7.7 0.1 7.5 0.1

Bloomberg Aggregation of Economic Forecasts

2007 2008 2009 2010 2011 2012 2013 E 2014World 5.20 2.80 -0.60 5.00 4.00 3.20 2.90 3.60US 2.10 0.00 -2.60 2.80 1.50 2.20 1.60 2.60Europe 2.70 0.50 -4.10 1.80 1.60 -0.60 -0.40 1.00Japan 2.30 -1.20 -6.30 4.30 -0.50 2.00 2.00 1.20Emerging Markets 8.30 6.00 2.60 7.10 6.40 5.10 4.50 5.10Developing Asia 10.60 7.70 7.00 9.30 8.20 6.60 6.30 6.50China 13.00 9.60 9.20 10.30 9.50 7.80 7.60 7.30

IMF World Economic Outlook



Economic Highlights

US Europe Japan China

Consumer (+) Q3 GDP accelerated to annualised 4.1% despite concerns over impact of government shutdown and debt ceiling. Non-farm payrolls were revised up for November to 241k but came in surprisingly low at 74k in December whilst the unemployment rate fell to 6.7%. This was largely due to a drop in the labour force participation rate. Retail sales and particularly vehicle sales have held strong with retail sales +4.1% YoY in December and vehicle sales +15.3%. Consumer confidence in December (Confererence board index) beat forecasts to record strongest levels since 2007. Housing strength continued with Case Shiller recording highest gain since 2006 rising 13.6% YoY in October after 13.3% in September.

(+) Eurozone Real GDP contracted at a slower pace of -0.4%YoY in 3Q and has recorded 7 consecutive quarters of contraction. Unemployment has held at 12.1% after rising in April. Unemployment remains at dangerously elevated levels above 25% in Spain and Greece with youth unemployment higher despite headline numbers having recorded a slight improvement recently. German unemployment has remained stable at 6.9% since September. Consumer confidence improved slightly but remains depressed although retail sales notably picked up rising 1.6% YoY in November to surpass expectations.

(+) Real GDP growth picked up to a pace of +2.1%YoY in 3Q but a slower pace of increase comparing QoQ. Retail sales bounced +4% YoY November. Department store sales have climbed at an impressive double digit pace in the last 4 months to December recording 18.7% YoY at year end. Unemployment held at 4% in November and real wage earnings inde recorded a slight increase in October and November compared to 3Q.

(+) Real GDP grew at 7.8%YoY annualised in 3Q2013 higher than the 7.5% in 2Q. Retail sales increased 13.7%YOY in November although consumer confidence dipped slightly in November v October. Unememployment fell to 4% in 3Q 2013.

Business (+) Industrial production increased

3.2% YoY and capacitiy utilisation rose in November. Durable goods orders recorded a 9.9% YoY jump on par with increases last seen in early 2012. ISM manufacturing recorded 57 and ISM Non- Manufacturing 53 in December slightly below November readings.

(+) Eurozone industrial production recovered sligthly from contracting earlier to post a weak +0.2% YoY growth in September and October. Capacity utilisation recorded a marginal uptick in 4Q and Euro area business climate index and industrial confidence surveys were marginally better. The ZEW Economic expectations survey marked a significant improvement from 60 to 68 November to December.

(+) Industrial production reversed a previous long negative trend with positive YoY growth from September to November marking 5% YoY growth in November. Machine orders jumped 17.8% in October. Tanken business conditions survey continued to record a broad improvement across large and medium businesses in manufacturing and non-manufacturing sectors.

(-) Manufacturing PMI declined to 51 in Decemberer and new orders PMI recorded lower at 52. Industrial production increased at a 10% in in November slightly slower pace compared to the 3 months prior gains. Urban Cummulative Fixed Asset Investment climbed 19.9% YoY in November recoridng the slowest pace for the year thus far.



US Europe Japan China External Sector & Government Sector

(=) Trade deficit narrowed with exports rising 5.2% and imports -1.1% in November. Government budget deficit widened in October and November.

(+) Current account for the Eurozone as a whole continued the positive and improving trend since January. Both exports and imports increased. Government sectors remain stuck in auesterity mode for most periphery countries .

(+) Headline export volumes increased 6.2% in November recording a positive but slower pace of export growth to US, Europe and Asia compared to October. Total import volumes were up +5%YoY in November. Foreigners bought more Japanese stocks whilst selling bonds in November. Japanese investors bought more foreign bonds and sold foreign stocks.

(-) Exports declined -0.3% YoY in September after showing signs of picking up over June and July but imports continued to rise at 7.4%. The trade balance recorded a slightly smaller surplus in September compared to 2Q and July and August. Foreign Direct Investments suddenly decelerated to +0.6%YoY in August after having recorded 20% plus increments in June and July.

Inflation (-) Low Inflation with CPI recording

1.2% YoY in Nov and CPI Ex food and energy 1.7%. PPI Finished goods slowed down to a pace of 0.7%YoY and PPI Ex Food and Energy to 1.3% in November.

(-) CPI increased at a 0.8%YoY in December weaker than the recorded growth rate in 3Q. Ex food and energy recorded 0.7% showing a similar pattern. PPI Finished goods managed a marginal +0.2% increase in October reversing a falling trend for the first time since 2011. PPI manufacturing contracted in November the 4th month in a row.

(+) CPI has been responding slowly to the BOJ explicitly targeting a 2% inflaton rate. The National CPI rose +0.9% YoY and Ex Food and Energy +0.3% in December.

(-) CPI declined from November to December recording 2.5% in December. Retail prices rose at a slower pace of 1.2% YoY. PPI finished goods and raw material prices continued to record declines over the 4th quarter with both measures falling trend since 2011.

Monetary (-) The FED tapered asset purchases

by $10bn a month in December to a pace of $75bn with the intention to end asset purchases in 2014. Any tapering is expected to be countered with forward guidance to keep interest rates low until both unemployment falls to below 6.5% and inflation shows signs up picking up closer to FED target.

(=) ECB cut the main refinancing rate by 0.25% to 0.25% in November and latest ECB meeting in January left the subject of QE open as “non taboo” The monetary base has however been contracting with return of LTRO capital from banks.

(+) BOJ monetary base has expanded 46% YoY in December. The Abe administation’s and BOJ Governor Haruhiko Kuroda both remain commited to increasing the pace of JGB purchases and to target longer maturities from 3 years to 7 years in duration.

(-) Interbank interest rates have spliked again slightly in December past 7% although much less than the 20% handle in June. The Government is accutely aware of the creit led growth in the economy and pursuing ways to curtail shadow market lending activities. With economic activity strong further monetary tightening could be on the cards for 2014.



US Europe Japan China Fiscal (+) The fiscal drag is expected to be

lower in 2014 compared to 2013. The actual budget deficit has been declining and recorded -4% of GDP in September which was less than half the peak annual deficit during 2009.

(=) Fiscal deficits have been slow to come down and faced several challenges such as the constitutional vote against Austerity in Portugal. On the otherhand Greece managed to meet fiscal targets in 2013.

(-) The consumption tax hike from 5% to 8% in April 2014 and expected drop in stimulus implemented in 2013 (2013 Stimulus nearly 10 Trn JPY and 2% of GDP) is likely to make fiscal policy tigher in 2014. A smaller stimulus of around 5.5 trn JPY is expeted to be passed in February which could offset some of the drag.

(+) Following the earlier policy induced slowdown and squeeze of bank lending to shadow financial sector, Chinese authorities have demonstrated ability to step up expenditures to offset the slowdown.

Noteworthy Changes

FED began tapering in December 2013 and is broadly expected to fully taper QE in 2014 although combining tapering with forward guidance to keep rates on hold until unemployment falls to at least 6.5% and inflation registers closer to FED target.

Marked reduction in European banking stress and Sovereign spreads with only marginally improved economic data. ECB cut interest rates in November and has not fully ruled out QE. With the German elections behind us it awaits to be seen if we can navigate 2014 without any peripheral sovereign debt rollover issues or if the banking sector can decouple from link to weak sovereign balance sheets.

The new administration led by Abe appear to have reversed the deflationary trend for the time being but economic data suggests they need to increase the pace of policy stimulus to achieve the intended results within the targeted time frame.

China clearly navigated fears of a growth slowdown much better than expected in 2013 but there is still a delicate balancing act to get right to rebalance economy away from credit fueled growth and government spending. The 3rd Plenum set out an abitious agenda and risk remain on implementatino.



Data Review – Leading Indicators Leading indicators still pointing upwards after a declining trend from 2010

Source: Bloomberg

‐8‐6‐4‐202468

US OECD Leading Indicator YoY %

US OECD Leading Indicator YoY%

‐5‐4‐3‐2‐101234

Japan OECD Leading Indicator YoY %

Japan OECD Leading Indicator YoY%

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Japan OECD Leading Indicator YoY %

Japan OECD Leading Indicator YoY%

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China OECD Leading Indicator YoY%



Data Review – Citi Economic Data Surprise Indices

Upside economic surprises across the regions

Source: Bloomberg

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100

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CIti Economic Surprise Index ‐ US

Citi Group Economic Surprise Index ‐ US

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50100150200

Citi Economic Surprise Index ‐ Eurozone

Citigroup Economic Surprise Index ‐ Eurozone

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20406080

100120

Citi Economic Surprise Index ‐ Japan

Citigroup Economic Surprise Index ‐ Japan

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Citi Economic Surprise Index ‐ China

Citigroup Economic Surprise Index ‐ China



Data Review – Labour Markets

Long-term trend lower in US unemployment. Average earnings increasing at a slow pace

Source: Bloomberg

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0200400600

US Non Farm Payroll Monthly Chg '000's

Initial Jobless Claims (Left axis)

01000200030004000500060007000

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Data Review – Labour Markets

Unemployment continues to be a major problem outside of Germany with Spanish and Greece unemployment over 25% and even France over 10%

Source: Bloomberg

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France Unemployment Spain Unemployment Italy Unemployment

Greece Unemployment Portugal Unemployment



Data Review – US Housing

US housing recovery still on track with lower mortgage delinquencies, rising housing starts and home sales

Source: Bloomberg

90

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US Housing Starts

US Housing Starts US Private Housing Building Permits

70270470670870107012701470

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US Mortgage Delinquencies % of total loans



Data Review – US Housing

US housing recovery evident across several data points despite a recovery from a very low base

Source: Bloomberg

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US Case Shiller Home 20 City Home Price Index

US Case Shiller Home Price Index

01020304050607080

US NAHB Index

US NAHB Index



Data Review – US Consumer/Retail Sector

Consumer confidence picked up in December. US retail and vehicle sales have been strong

Source: Bloomberg

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100120

US Consumer Confidence

Conference Board Consumer Confidence

U of Michigan Consumer Confidence

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02468

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Proxies for Business Conditions / Economic Activity

PMI’s picked up and stronger Industrial Production. Europe showing early signs of a recovery from low base

Source: Bloomberg

253035404550556065

US ISM Manufacturing & Non Manufacturing PMI

US ISM Manufacturing PMI US ISM Non Manufacturing PMI

0102030405060708090

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US Industrial Production (YoY%)

US Industrial Production (YoY%)

US Capacity Utilization % of Total Capacity (Right axis)

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US Durable Goods New Orders (YoY%)

US Durrable Goods New Orders Total (YoY%)

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Eurozone Industrial Production YoY%



Proxies for Business Conditions / Economic Activity

Chinese activity data stabilised. Abe’s reflationary policies are slow to reflect in Japanese business activity data

Source: Bloomberg

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100150200250300

Japan Machine Tool Orders (YoY%)

Japan Machine Tool Orders YoY%

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Japan Industrial Production (YoY%)

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Business / Investor Confidence

Improving business confidence across the regions with Japan & Eurozone showing a notable increase

Source: Bloomberg

‐40‐30‐20‐10010203040

US Business Conditions Surveys

Philly Fed Business Outlook Survey IndexEmpire State Manufacturing General Business Conditions

‐80‐60‐40‐200

20406080100

ZEW Eurozone Expectations of Economic Growth

ZEW Eurozone Expectation of Economic Growth

5060708090100110120

IFO Pan Germany Business Expectations

IFO Pan Germany Business Expectations

‐80‐60‐40‐200

2040

Japan Tankan Business Conditions Large Enterprises Manufacturing

Japan Tankan Business Conditions Large Enterprises Manufacturing



Consumer Inflation

Low inflation in US and weak trend in Europe. Japan showing a small response to reflationary policies

Source: Bloomberg

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US CPI Urbun Consumers (YoY%) US CPI Ex Food & Energy (YoY%)

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Eurozone CPI All Items (YoY%) Eurozone Core Ex Food & Energy (YoY%)

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China CPI YoY China RPI (YOY%)

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Producer Price Inflation

Producer price inflation has been contained/trending down which reflects positively for manufacturer margins

Source: Bloomberg

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US PPI Inflation (YoY%)

US PPI Finished Goods (YoY%) US PPI Processing/Intermediate Materials (YoY%)

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PPI Eurozone Finished Goods (YoY%) PPI Eurozone Manufacturing (YoY%)

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China PPI (YoY%) China PPI Raw Material Prices (YoY%)



Market Fear Gauge

Volatility low across equity and FX markets despite recent fears over a US debt ceiling

Source: Bloomberg

0102030405060708090

VIX Volatility Index

VIX Index

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Barclays Swaption Volatility Index

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Euro‐Dollar Volatility



Indictors of US Financial Market Stress

Improvement in US financial conditions index and low signs of stress in corporate credit and money markets

Source: Bloomberg

‐7‐6‐5‐4‐3‐2‐10123

US Financial Conditions Index

US Financials Conditions Index

0100200300400500600700

US Corporate Baa / 10 Year Spreads

US Corporate Baa/10 Year Spreads

020406080100120140160

US Commercial Paper / T‐Bill Spread

Commercial Paper / T‐Bill Spread

020406080

100120140160

US TED Spread

US TED Spread



Non-US Indictors of Financial Market Stress

Source: Bloomberg

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EU Financial Conditions Index

EU Financials Conditions Index

01234567

China 3M Shibor Rate

China 3M Shibor Rate



Central Bank Behavior – US

US quantitative easing has not increased the velocity of money in the real economy with the banking sector still building up capital buffers in favour of lending money out

Source: Bloomberg

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Hedge Equities


INVESTCORP Hedge Equities Environment Report | 1st Quarter 2014

Equities Alpha View In the traditional CAPM like framework, it is useful to think of return to equity investing as consisting of two parts – a Beta component, and a residual Alpha component. Returns to equity markets worldwide are very well covered from many different perspectives- fundamentals with its focus on macroeconomic growth flowing down to sector and stock level expected performance, recent and long term valuation metrics and funds flows. We will not add much to the discussion on Beta timing in this section, but will instead focus on what we think captures the environment that is ripe for earning equity alpha.

There are four broad sources of earning Alpha in the equity markets – taking on systematic factor exposures other than broad market exposures, stock selection alpha exploiting through skill the wide dispersion in stock returns, providing liquidity in a market where trading volumes impact specific stock prices that is mean reverting and by trading in realized volatility through a portfolio construction process. We will for ignore the last two sources of return and focus instead on the return to factors other than the market as well as on dispersion of returns that allow managers to take active bets on their performance and outperform the index.

Factor Returns Since the seminal Fama-French paper it has been the standard practice to use their three priced factors in addition to market returns to explain security returns. If any confirmation was needed on the importance of this strain of research, the Nobel committee’s decision to award Eugene Fama one-third of this year’s economics prize provided one. We will evaluate monthly returns to factors from a different source- the commercially available Barra GEM3 (Global Equity Market) long term model. Fama-French factors and their close cousins like Barra are not the only way to view the factor structure of the equity market returns and in the future we will introduce other models based on very different pricing kernels. As is always the case, a long history helps put the more recent numbers in perspective – even if it is only to describe the glory days gone by- and explains our longer term view on factor based investing; the near term returns provide a context of the magnitude of returns. We have selected a few factors for our purposes here to make our case.



Near-Term Performance of Factors It is instructive to see the factors that have done well in the current year and link that to investment themes. Some of the conclusions are consistent with more fundamental based views and others not so. The search for yield that has been the bedrock of the criticism of QE and its effect on equity markets is borne out partially; earnings yield as a factor has explained 3.13% of the return in excess of the market while its purer cousin- dividend yield has not losing -0.90% during 2013. Size has not been an advantage this year with large cap stocks underperforming small cap stocks and there have been persistent trends in outperformance- stocks that outperformed in recent periods have tended to outperform in subsequent periods with unit exposure to the factor earning an excess return of 7.58%. It has paid to be long Beta in the current rally where world equity markets have returned 25%.

Book to Price

Dividend Yield

Earnings Yield Growth Leverage Liquidity Momentum Size

Size Non‐ Linear Beta Volati l ity

Year to Date 1.12% ‐0.90% 3.13% 0.47% 0.68% ‐0.95% 7.58% ‐1.31% 0.75% 2.38% ‐2.31% 2013:Q4 0.47% ‐0.12% 1.01% 0.14% 0.25% ‐0.28% 1.91% 0.08% 0.06% 0.54% ‐0.23% 2013: Q3 0.17% ‐0.38% 0.72% 0.07% 0.08% 0.01% ‐0.04% ‐0.29% 0.12% 1.52% 1.11% 2013: Q2 0.57% ‐0.28% 0.11% 0.36% 0.15% ‐0.23% 2.73% ‐0.14% ‐0.26% 1.87% ‐2.36% 2013: Q1 ‐0.10% ‐0.13% 1.27% ‐0.10% 0.19% ‐0.45% 2.81% ‐0.96% 0.83% ‐1.53% ‐0.83%12 Month Return 1.12% ‐0.90% 3.13% 0.47% 0.68% ‐0.95% 7.58% ‐1.31% 0.75% 2.38% ‐2.31%24 month Return (Ann.) 0.98% ‐0.64% 3.34% 0.80% 0.94% ‐0.31% 5.26% ‐1.02% 0.63% 2.87% ‐3.35%36 Month Return (Ann.) ‐0.04% 0.59% 3.03% 0.61% ‐0.23% ‐1.15% 5.98% ‐0.61% 1.08% 1.47% ‐4.76%

Value Factors Size Factors Volatility

Sources: Barra, Investcorp



Longer-Term Factor Performance Trends

Value Factors There are three different metrics you can use to identify value stocks in the Barra model – Book to Value, Earnings Yield and Dividend Yield.

The classic book to price factor has been less consistent since 2007. The charts above have monthly returns to the factors as well as a six month moving average to smooth out monthly volatility. It is clear that pre 2007 there were very few 6 month periods where the cumulative returns were negative. The factor has become far more volatile since then.

In contrast a hedge fund manager focusing on high earnings yield companies (cash earnings, price to earnings as well as analyst-predicted earnings) have done very well. Hedge fund managers sticking to high earnings to price stocks have since 2008 not had many poor six month runs. The post crisis equity markets have rewarded investors looking for yields.

But stocks with high dividend yield have not been consistent and in the recent past have not added any Alpha to stock portfolios. High dividend yielding stocks did outperform in the flight to quality post 2008 and the European crisis in 2011, but since then have suffered from diminishing returns.


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Other Factors

Hedge fund managers with portfolio exposure to momentum have generally performed well over the long run barring for the periods of market corrections 2000, Q4:2008, and 2009. The factor exposure continues to earn positive Net return alpha. Stated in flow terms the marginal flow of Dollars in the equity markets is to stocks that have outperformed their peers and to repeat a cliché there is return chasing in markets and exploiting it has on average been profitable.

Large cap has continued to underperform small cap over the long run ….


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Other Factors (continued)

… and Growth names have had positive returns and seen lower month to month .

A longer term view of factor returns argues that managers who construct portfolios that are long fundamentally strong names (earnings yield) or in momentum names have done well. We continue to be wary of funds investing in stocks that are levered (operational and financial).


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GROWTH



Dispersion Trends Performance of hedged equity managers is a function of the systematic exposures (both market and other fundamental factors) and the ability to exploit the opportunity to select stocks. We believe that the best way to characterize the opportunity set for a hedged equity managers is to examine the intra-market correlations. Time series correlations estimated using a rolling window are one way to measure correlations but do not react fast enough to data as they are average measures estimated over long time windows. Dispersion among the stocks is a measure that is estimated every period and presents a faster estimate of changes in correlation. Mathematically, dispersion is inversely related to correlation.

Over the long run, the correlation amongst stocks in the broad market has been trending upwards as evidenced by this dispersion chart. The 6 month average dispersion is for most markets as low as it has ever been. In the large cap universe approximated by the Russell 1000, the dispersion levels have reached levels close to summer of 2007 when S&P and other major equity indices made their tops. A glimmer of opportunity exists in the small and midcap space where the dispersion has been at least 5 points higher than the large cap stocks and the gap has widened in the recent months. Our view is that if an investor wants to invest in managers who earn stock selection alpha, they stand a better chance of earning higher absolute return in the small and midcap space.

Among the various sectors, it is not surprising that non-cyclical sectors such as utilities and financials have shown lower cross sectional dispersion (or high correlation); and sectors such as health care (which are idiosyncratic) have shown lower correlations. The interesting observations are that telecommunications services has shown cyclicality in its cross sectional dispersion and has seen a significant uptick in the recent months and so has energy. The rest of the sectors are tracking closely the overall market dispersion trends. While healthcare is fraught with event (binary) risk, significant alpha opportunities exists in telecom, technology, energy and consumer discretionary. Investors looking for active stock selection alpha have a better chance of earning meaningful alpha by using a skilled manager in the sectors displaying larger dispersion than in others.

Source: Bloomberg



Credit


INVESTCORP Credit Environment Report | 1st Quarter 2014

Credit Strategy View Overall we are neutral on the global credit opportunity at this point in the cycle. We are neutral/negative on U.S. performing corporate credit and somewhat positive on structured credit and one-off U.S. and European corporate restructurings. U.S. corporate high yield’s (yield to worst) remain at historically low levels (due both to spread compression and declining treasury yields). Structured credit is still somewhat dislocated and presents a relatively attractive opportunity within credit. However we believe that the risk/reward is more balanced than in previous quarters. There are still infrequent opportunities within U.S. corporate credit which are confined to select mid-sized stressed corporates and special situations (i.e. liquidations). European stressed/distressed credit opportunity set is still in its nascent stages, however, could increase in the coming years.

The credit opportunity set is smaller, but returns are still achievable in certain sub-strategies. Asset backed securities and one-off corporate restructurings/special situations are relatively the most compelling. We remain focused on credit opportunities that are low duration and catalyst-oriented in nature versus credit tightening.

U.S Corporate High Yield The current price of high yield and leveraged loan debt are near historical highs. This has been aided in the past few years by a rally in treasuries, improving corporate fundamentals and a dramatically improved financing environment. The asset class can stay at or above par for a relatively long period of time. However at this point in the cycle, many securities in the space are unattractive. There are a few corporate-specific situations, but these are cases where there is some sort of idiosyncratic event and/or a liquidation of a legacy corporate structure (i.e., Ambac, Capmark). Our view is that there are potentially multiple ways to lose in fixed rate securities (i.e. via widening from historically tight credit spread levels, or from an increase in treasury rates).

For the most part (excluding minor intra year corrections) yield to worst for performing high yield is at historically low levels (near 25-year lows). Both credit spreads and 10-year treasuries are near recent historical lows indicating that there is little upside to performing high yield.



Not surprisingly, loan yields exhibited lower volatility over the past few months given their floating rate structure. High yield, (i.e., the index) continues to trade above par. This has significant implications as any new investment into the average high yield bond is betting that a) the principal will be repaid in full and b) that the company will be able to refinance its debt at an attractive rate.

While high yield spreads are near the 20-year average (440 bps current vs. 595 bps 20-year average) the yield to worst rate (i.e., the overall yield for holding the security) is near historical lows (5.8% current vs. 10.0% 20-year average) due to still abnormally low interest rates. In essence, there are multiple ways for an investor to lose money given the current high yield environment: corporate spreads increase, treasuries decrease in price, or defaults increase. Investors are compensated only 5.8% (before any losses) for taking this risk.

While high yield prices remain near historical highs, overall appetitite for high yield dipped in 2013 as it was the third largest net fund outflow on record ($4.1 billion outflow). This does not present a strong technical picture for high yield credit.

However the the bid in the market remains relatively intact at least in the near term. The last two years were the highest yearly totals for high-yield issuance. In 2013, high-yield issuance broke last year’s record via nearly $400 billion in new issuance. Another interesting dynamic is the record increase in non USD denominated high yield issuance in 2013. Most of this increase is coming from Europe where the disintermediation of bank lending will ultimately change the shape of European landscape. The increase in high yield issuance should continue within Europe which should help plant the seeds for the next stressed credit cycle in Europe. This has ramifications for investing in European credit and the overall liquidity of the market.

High Yield Net Flow

High Yield Issuance

Non-USD High Yield Issuance



Another warning sign that is not problematic (yet, but starting to look more troubling) is the sources and uses of high yield issuance activity. The vast majority of activity in recent years has gone to refinance existing debt and for general corporate purposes. Debt to support LBO and acquisition activity still remains well below 2007/2008 levels. Furthermore nearly 100% of the high yield issued over the past few years has been cash pay bonds (versus more risky PIK/Toggle notes). In summary, the high yield environment is relatively stable, albeit with an unattractive intermediate-term return profile with some technical and fundamental indicators that have started to flash warnings signs.

New Issue Activity

Source: J.P. Morgan



U.S. Corporate Loans Similar to high yield, leveraged loans have a somewhat meager total return profile at this point in the cycle. Currently, spreads within the asset class are L+419 bps which are well below historical spreads (7 year average spread of L+568 bps). This is even more pronounced in the context of a yield to maturity (5.9% currently vs. 8.0% -- 7 year average). Anectdotally LBO multiples are again increasing (some deals are clsing at 10x+) and credit standards for new loan origination is starting to decline. The recently issued warning by the Federal Reserve on underwritting standards for new loans supports this view.

Leveraged Loan Net Fund Flows

CLO Volumes

Demand for leveraged loans has remained relatively robust in recent months aided by the resurgence in CLO volumes and the presence of a floating rate structure (in loans versus a fixed rate structure in bonds). The increase in demand for CLOs shows that demand for structured loan products is coming back. In 2013, demand for loans, CLOs and floating rate products (generally) was quite robust given inevitability of the Fed and a normailizing rate environment.

Overall the demand for leveraged loans remains more robust, however the return profile is less compelling going forward. Select opportunities may present themselves as the maturity wall continues to be refinanced over time. However demand from both institutional funds and CLOs seem to have created a current healthy bid in the market. CLO volumes are nearly back to 2007/2008 levels.



U.S. Corporate Defaults

High Yield and Leverage Loan Default Volumes

Leverage Credit Default rate

Defaults for both high yield and leveraged loans remain significantly below long term averages. This is the case in both dollar and count. There are a number of drivers to the low current default rates including: significant amount of liquidity in the market (i.e. the ability to refinance), reasonable (but not burdensome) lending standards, and healthier corporate balance sheets.

Default rates are 1-2% which is well below recent historical averages (13 year average of ~3%). There could be a few large legacy capital structures (i.e. TXU) that could default in the coming months. In 2013 there have been 29 total defaults on $18.9 billion. On average this is $651 million per default. This is in line with the thesis that relatively smaller/weaker select corporates can struggle throughout a cycle.



Second Lien and Covenant-lite Loan New-issue Voume

In summary defaults have remained near cyclical lows. Defaults have mainly (ex., potentially TXU) been companies are smaller in size and are typically competitively disadvantaged. In the charts above it is evident that loan underwritting standards have clearly loosened. Both second lien and covenant lite origination have reached historical highs in 2013. Additionally, the technical picture within high yield that is starting to become more ominous. Both current high yield and leverage loan origination should provide opportunities for the next corproate distressed cycle Defaulted credit situations provide an opportunity for one-off opportunities but the flow of new/attractively priced investments within the area should remain somewhat limited over the next 12 months.



Structured Credit The return of liquidity into structured products market has led to an increase in legacy prices eliminating most of the illiquidity premium that was priced in after the financial crisis. In terms of complexity structured credit backed by residential mortgages are the simplest structures and have recovered the fastest when compared to commercial mortgage backed securities, collateralized loan obligations or other asset backed securities. The following chart compares the price action in high quality residential mortgage and commercial mortgage backed securities. We think there is some ways to go for CMBS and that is the market we would focus on.

Overall we view this asset class as a liquidating opportunity set with the ability to potentially deliver low double digit returns. The general thesis is that security prices (specifically for mezzanine securities where there is structural leverage) do not fully reflect the increasing value and the recovery value of the underlying asset classes. The duration across these securities is relatively short as many of these securities mature in the next 3-4 years and/or have a high level of amortization (specifically from residential mortgage securities).

There also remains opportunity in CLOs when compared to straight corporate credit with a yield pick-up of nearly 175 basis points. Broadly speaking there still remains a certain premium for complexity and it provides a decent yield pick-up over return to cash credit. Legacy CMBS, CLOs and select RMBS represent a good risk adjusted return over the next 12 to 18 months given decent on-going yield characteristics, improving underlying assets (i.e recovery values), and relatively low duration.

30-Dec-10 01-Jul-11 31-Dec-11 30-Jun-12 30-Dec-12 30-Jun-13

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75

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Prime Clean CMBS CMBX.AJ.4 (Px)Source: Credit Suisse Locus

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Residential Mortgage Backed Securities (RMBS)

The thesis around RMBS is rooted in the dislocation between prices of select RMBS and the improving underlying fundamentals within residential real estate. We have been tactically overweight this area for the past 24 months. While there are still areas of opportunities within RMBS, the price dislocation in the space has somewhat normalized. We have focused our remaining exposure on mezzanine RMBS or idosyncratic securities that could benefit from litigation. The main areas of the thesis (listed above) are still valid.

Loan Seasoning Pronounced effect of lower delinquencies with passage of time On-time monthly payments significantly increases over time Loan modifications act as tailwind to the seasoning effect

Declining Defaults and Severities

Subprime non-performing borrowers dropped from 50% to less than 40% in the past two years

Rate at which performing loans are turning delinquent declined by 50%+ from the crisis peak

No New Supply Non-agency issuance declined to zero versus $700 billion in 2007 Non-agency universe shrunk to ~$1 trillion from a peak of ~$2.0

trillion over the past 5 years

Forced Selling from Legacy Owners

Prior to the Crisis, banks and institutions bought these securities as they provided attractive yield and required very little regulatory capital to hold

These securities were downgraded and regulatory capital charges increased, these institutions needed to sell

High Barriers to Entry Not all non-agency RMBS will perform Understanding cash flow structure / underlying collateral are critical Experience of previous underwriting standards is vital

Attractive Product Characteristics

Low purchase prices High total yield; sizeable cash yield Short maturities



Credit burnout (or loan seasoning) is having a positive effect on borrower behavior.

Probability of first delinquency clearly declines after 24 months for both subprime and Alt-A

Months of on-time monthly payments significantly increases over time

Loan modifications act as a meaningful tailwind to the seasoning effect

Default rates for RMBS are declining.

Subprime non-performing borrowers dropped from 50% to less than 40% in the past 2 years

Rate at which performing loans are turning delinquent declined by 50%+ from the peak

Delinquency (90+) Balances and Roll Rates have peaked and are in steady decline

Liquidation rates remain high as delinquent borrowers continue to leave mortgage pools



Loss severities (or loss rates) for RMBS have stabilized.

Severity levels improved or remained consistent in the past year (ex lower loan balances)

Loss severity has decreased in California while remaining relatively high in Florida

Larger loan balance severities for subprime and Alt-A have decreased in the past year

Significant decline in REO liquidations (distressed sales) for subprime and Alt-A loans

New issuance for Non-Agency RMBS has vanished in recent years with a few new deals in 2013.

Non-Agency issuance declined to virtually zero versus $700 billion in 2007

Other credit categories have seen at least some meaningful activity post 2008

Non-Agency universe shrunk to ~$1 trillion from a peak of ~$2.5 trillion over the past 5 years



Some current investors are uneconomic sellers of RMBS.

Over $2 trillion in total bank loans (including RMBS) disposal programs

Approximately $45 billion of Non-Agency RMBS on EU bank balance sheets

Increasing regulatory hurdles are forcing banks to sell lower-rated debt

Recent improvement in housing provides a window to increased selling activity

Prepayment trends have started to improve and should provide a tailwind to RMBS.

Overall prepayments (especially for higher LTV loans) remain at low absolute levels

Subprime / Alt-A prepayments for older vintages (2004/2005) are near four year highs

More recent vintage (2006/2007) prepayments have increased in the past two years

Lower LTV loans dominate prepayments though high LTV loans increased in the past year



Commercial Mortgage Backed Securities

The thesis on CMBS is again derived from the disconnection between security prices and the significant improvement in the underlying asset class. There are several factors (listed below) that have led to this current opportunity.

Increasing Availability of Financing

Lenders have increased lending for CRE loans Lower CRE coupons should make refinancing more affordable 2005-2007 vintages with relatively moderate Loan-To-Values (LTV)

should benefit from more accommodative underwriting standards

Improving Fundamentals

Higher asking rents for most property types Occupancy rates have rebounded in the past 18 months New construction activity remains low

Declining Delinquencies and Severities

Distressed transactions down to 12% of total from 20% in 2011 Delinquencies peaked in to20 and have since declined Elevated liquidations and a slowdown in new delinquencies should

lead to a decline in CMBS delinquencies

Favorable Supply / Demand Dynamics

New issuance of only $44 billion in 2012 down from $230 billion in 2007

Total CMBS market has declined to approximately $500 billion versus approximately $750 billion in 2007

Orphaned Asset Class

Only 60% of 2003-2005 vintage CMBS remain Very little new issuance of CRE via CMBS in absolute and relative

terms (versus other sources or origination) Highly liquidating legacy (2008 vintage of earlier) asset class due to

refinancing and liquidation activity

Relatively Attractive vs. Corporate Credit

Capitalization rate to corporate yield spread is wide compared to historical values

Potential for moderate price appreciation



The availability of financing for commercial real estate loans is improving.

2005-2007 vintage LTVs should benefit from accommodative underwriting standards (75-90% LTV)

Indicative coupons dropped 200 bps in 2012

Lenders have loosened underwriting standards post 2009

Banks have an increasing appetite for commercial real estate loans since 2010

Source: Credit Suisse, Federal Reserve Credit Suisse, Federal Reserve



Fundamentals are improving for commercial real estate.

Improving CRE asking rents for almost all property types

Occupancy rates for all major property types bottomed over the past 18 months

Competition from new construction is limited

Significant loan modifications since 2009

Vacancies remain steady while NOI has stabilized and improved in recent quarters

Rents for most property types have been growing in recent quarters

Prices have improved off trough 2009 levels, but remain considerably lower than peak

Source: J.P. Morgan Source: J.P. Morgan



Distressed and delinquent commercial real estate is declining.

Flows into delinquency (60+ days) have declined in recent years

Delinquency pipeline continued to season over the past few years

Distressed CRE has declined in recent years

Proportion of distressed transactions peaked in 2010/2011 and continues to decline

CMBS loss severities have stabilized with elevated liquidations.

Severity levels have improved since 2009 and have stabilized in recent years

Severities on liquidating loans have declined in recent years

Commercial loan liquidations are at historically high levels

Delinquencies have declined over the past year for all property types

Hotel delinquencies (leading indicator) have declined the most in

recent years Source: Credit Suisse, Real Capital Analytics



New issuance of CMBS is minimal in recent years while the universe continues to shrink.

New issuance has been minimal post 2007 (less than $50 billion vs. ~$225 billion in 2007)

Pre 2008 vintage CMBS outstanding is expected to decline over the next few years

CMBS market has shrunk to ~$500 billion from ~$750 billion in 2007

CMBS remains an orphaned asset class for traditional investors.

1997-2002 vintages has largely disappeared (7% or less)

Only ~60% of the 2003-2005 vintages remain

From 2002-2007 CMBS were a large source of financing for new origination

Lack of recovery in CMBS market share post 2008



Legacy CMBS is a liquidating asset class.

By 2014 the legacy CMBS market is expected to be ~50% of its previous size in 2010

Legacy Mezzanine and Short Duration volumes are down over -25% in the past year

Nearly 25% of all CMBS retired in 2012 was from the 2007 vintage origination

2003-2007 vintage loan balances are expected to decline significantly in the next two years

Cap rates are still attractive versus corporate alternatives.

Cap rates remain attractive versus corporate alternatives

Absolute cap rates are near 35 year lows (partially driven by abnormally interest rates)

Capitalization/corporate ratio indicates that CRE is still relatively attractive

Legacy A4 bond yields are higher than 60% of comparable duration corporate bonds

In summary, CMBS remain an attractive investment given the dislocation between security prices and the improving underlying commercial real estate assets. The best risk/reward is in mezzanine securities where there is a high degree of difficulty around security selection and significant lack of buyers.



Event Driven


INVESTCORP Event Driven Environment Report | 1st Quarter 2014

Event Driven Equities Strategy View The market environment is very constructive for event driven strategies. In essence our thesis is the culmination of a confluence of factors facing U.S. and multinational corporations today. The current environment is one where companies are awash in liquidity, but have limited paths to growth in terms of profitability. Companies are under increasing shareholder pressure to maximize shareholder value, albeit with dwindling ways to do so organically (i.e., through increasing revenues and cutting costs).

The increasing pressure within the corporate boardroom combined with ample liquidity is leading to a potential explosion of event driven opportunities. This should materialize in many different forms including: operational/financial restructuring, increased buybacks, transformative M&A, and returning cash to shareholders (via special and increased recurring dividends. Merger arbitrage spreads as a standalone strategy is not attractive given the annualized return of approximately ~5%. Select deals that require significant insight, capital, and expertise are more interesting, but much less frequent in today’s environment.

Currently cash balances are near all-time highs for U.S. corporations. Given the opportunity cost of excess liquidity (cash earning nearly zero percent), companies need to efficiently and effectively deploy current cash balances and the ongoing cash flow of the business. This is evaluated in the context of a slow growth macroeconomic environment, very low corporate interest rates, and margins that may have peaked in recent years.

Sales growth and margin expansion of the S&P 500 has been decelerating in recent years. Corporate share prices have recovered and while the macroeconomic picture is not robust, there is some visibility on customer demand, especially within the U.S. Company management and board of directors are under increased scrutiny and pressure to deliver returns and they have the means (see cash balances above) to financially engineer value regardless of recent share price performance.

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Cash & assets for non-financial U.S. corps. ($T)

Source: Federal Reserve



Not surprisingly, this has led to a significant increase in shareholder pressure in the form of public activism. Shareholder activism continues to become more mainstream as companies pre-emptively use a number of “value-creation levers” to maximize shareholder value. In 2013 there has been more shareholder activism (as measured by 13D filings) than in any of the past five years. This is very significant and provides a tailwind to unlocking value in the future by applying pressure to the current corporate governance structure. Given the dynamics (i.e., slow but visible growth, peak margins significant cash and cheap financing); the event environment should be very strong for the next few years.

Since 2009 there is clear evidence of an increase in corporate events that seek to maximize shareholder value. There has been a marked increase in both corporate buybacks and special dividends over the past five years. Announced special dividends have dramtically increased over the past two years. Over the last 24 months there were over 2,500 special dividend announcements, slightly less than the previous three years (2009-2011). Nearly 1,200 special dividends were announced in 2013, the second highest total over the past five years. However it is important to remember that these are just one area of event driven strategies used to maximize shareholder value. Some other popular event types during the current event cycle include spin-off’s or break up candidates, operational/management-led restructurings, recapitalizations, tax-driven restructurings, litigation and or regulation resolutions, and privatizations.

Source: Capital IQ

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As seen in the chart to the right, an index of recent spinoffs or demergers can be very powerful in terms of increasing or maximizing shareholder returns. Since 2009 the Guggenheim Spin-Off Index has nearly tripled in value. It should not be a surprise that management motivations (i.e., transfer pricing or corporate strategy de-emphasis) can lead to an underutilized portfolio of assets. Furthermore management’s motivations with regards to keeping certain business segments can have nothing to do with maximizing shareholder value (i.e., wanting to manage a larger company).

Since 2009 there has been a clear improvement in M&A transaction volumes specifically for small and mid-sized capitalization companies. Each year post 2009 has led to increased M&A and 2013 small / mid-capitalization M&A was the highest level (count) in the past five years. The lack of growth prospects, very cheap financing, high opportunity cost of an oversized cash balance (immediate accretion in most cases), and the ability to transform a given business without committing massive capital (i.e., large capitalization M&A) are driving M&A volumes of smaller and mid-sized companies. Anecdotally the market has continued to award the accretive nature of these transactions and many times both the target and the acquirer will trade up substantially post the announcement. This has significant ramifications for increased M&A in the coming years.

In summary, there are a number of positive tailwinds within both the macroeconomic environment and corporate sector that have led to resurgence in event driven equity activity. The opportunity set within event should remain broad-based driven by both increasing shareholder activism and accretive M&A opportunities. We expect the environment to remain robust over the next year as companies look for ways to maximize shareholder value.

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Guggenheim Spin‐Off Index

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$200M – $5B Transactions (count) Small-Cap ($200M-$1B)Mid-Cap ($1B-$5B)

Source: Federal Reserve

Source: Bloomberg



Convertible Arbitrage


INVESTCORP Convertible Arbitrage Environment Report | 1st Quarter 2014

Convertible Arbitrage Strategy View It is useful to think of convertible arbitrage as a package with three return drivers- credit spread or return earned for assuming credit risk, opportunity to profit from elevated realized volatility (Gamma trading) especially compared to the implied volatility priced into purchase price of options (Theta bleed) and a liquidity discount that comes from investing in a relatively less liquid asset class. It is difficult to disentangle the exact cause of mispricing, but suffice it to say that on a like-to-like basis converts trade normally at a discount and this discount is best monetized by gamma trading the realized volatility. We distinguish opportunities in convertibles from convertible arbitrage. Long only converts do not specifically monetize the cheap option embedded in a convertible bond but do benefit from the performance of the underlying equity it is convertible into. Realization of new issue discounts is another source of returns as are returns earned from special situations or one-off events. Special situations returns are driven by both idiosyncratic events at individual companies as well as trends in markets similar to what drive event driven investing. New issue discounts are a source of profits, but not a significant driver across the strategy.

Convertible bonds had a good steady quarter and when you look at the underlying drivers it is not difficult to see why it is so. Yields after rising sharply following talk of potential taper (in June) have come in providing some returns; discounts have increased a little bit from the lows which provided little or no returns and are now not significantly different from 0. Unhedged Converts in the US as an asset class were up 24.4% in total driven by an above average performance by the equity underlying US converts.

We will use each of these drivers individually to assess – both statistically and through a series of subjective opinions – the attractiveness of the convertible arbitrage space. There will be managers whose performance we concede will differ depending on their security selection and aggregate portfolio exposures post hedges to the large drivers.

Discount to Theoretical (or liquidity premiums) It is not a mystery that an increase in the liquidity premium would lead contemporaneously to drawdowns in convertible arbitrage portfolios and vice-versa. These discounts have also been correlated in the past with an increase in credit spreads that only exacerbates the drawdowns. The correlation co-efficient is close to 0.660 between the two time series over the last 10 years. This past quarter saw discounts inch higher as spreads tightened; and given the sensitivity to basis point spreads, the bonds rallied.

It is clear that to understand the return dynamics better, it makes sense to look at both these drivers independently as well as simultaneously.

Figure 1

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HY Spreads Barc Discount

Source: Bloomberg



Discount to Theoretical (or liquidity premiums) (continued) Discount to theoretical levels at current levels continue to predict a low return environment for convertible arbitrage managers as can be seen in Figure 2, which charts the average 3 month prospective return for the HFRI Convertible arbitrage index and the level of discount or richness/cheapness of convertible bonds.

Current levels of cheapness have presaged lower than average 3 month returns. A low discount to theoretical (and increasing) has meant drawdowns for the strategy. A similar pattern in early 2007 (when discounts were below the long term mean and rising) and in 2004, 2005 and 2011 were periods of underperformance.

Expected returns based on past returns are fraught with the risk of ignoring a number of other factors that drive returns. Barring 2011, which was an unduly volatile period with worries emanating from Europe, all the other periods were periods of excessive leverage and/or shrinking supply. Both these factors are absent in the current environment with more than 55% of outstanding convertible bonds estimated to be owned by long only unlevered managers.

High Yield Spreads Since a significant proportion of the convertible universe is lower rated, you should not be surprised to find that high yield spreads capture one of the sources of expected returns in convertible bonds. The Moody’s Baa credit spreads are currently around 530 basis points. This is below the long term mean rates as well and trending upwards. Historically this behavior has been associated with average to slightly below average returns for convertible arbitrage index. The yield spread indicators also point towards sub-par returns for convertible arbitrage managers.

The current trajectory of high yield spreads- low (below long-term mean) and rising is associated with muted forward looking returns for the strategy. 0.00

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HFR 3 Mos Return high yield spreads Mean +1 SD ‐1 SD

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Source: Bloomberg



Implied vs. Realized Volatility Realized volatility is a source for any hedged long volatility strategy and convertible arbitrage is no exception. The degree of importance depends on the moneynesss of the options, with at-the-money convertibles profiting the most from any increase in realized volatility (compared to implied volatility). The following chart plots the cumulative squared returns of the S&P 500 index and you can see a uptick in the short term volatility in the index.

Figure 4 uses cumulative squared returns as the measure that reacts fastest to the change in volatility with the slope of the line used to identify volatility regimes. It is clear that periods when local volatility is high is when Convertible arbitrage managers perform very well. Since the middle of 2010, and barring for the summer of 2011, the equity market volatility has been very muted. The din of opinion on worldwide risk shows up everywhere except in the realized volatility charts in most developed equity markets. This is reflected in the low levels of VIX that at its current levels is still higher than the realized volatility it purports to forecast. Gamma trading, the bread and butter of convertible arbitrage strategy, and which relies solely on the volatility of underlying stock prices has suffered.

Issuance New issuance has always been a source of additional return for convertible arbitrage managers and 2013 was a great year for issuance especially the 4th quarter. There were a total of 140 new deals in 2013 with nearly 74 in the last quarter. Issuance of converts is a function both of investment climate and prevailing interest rates. Issuance of converts in the US in 2013 was around 48 Billion which compares well with the 21.4 Billion raised in all of 2012, 25.2 raised in 2011 and 35.9 raised in 2010. This provides some opportunity for the convertible arbitrage managers to earn new issuance discounts. While this is an encouraging sign, we continue to be cautious about the size of the convert universe, because the universe has seen redemptions of nearly 54 Bn. This diagram of the flows of issuance and redemptions of convertible securities …

Figure 2

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75

100

125

150

175

200

$(50)

$(25)

$-

$25

$50

$75

$100

$125

$150

$175

$200

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Num

ber o

f Dea

ls

$ bi

llion

Annual New Issues and Redemptions

New Issue Volume Redemptions

Source: Bloomberg

Source: Barclays Capital



…. paints this dismal picture of the stock of outstanding convertible securities.

The universe has seen a near 40% drop in the number of outstanding issues and amount outstanding at half the peak in 2007.

Conclusion We remain underweight convertible arbitrage as a strategy based on these drivers of returns. Credit spreads are a little below mean and represent fair compensation for assuming credit risk with risks on the upside if the spreads widen. The discount to theoretical is below average and rising which should lead to muted returns from this source. Volatility – realized and implied- has been at cyclical lows arguably because of the unprecedented amount of liquidity in the market and the uptick in both should wash itself out over the cycle (Gamma trading profits negated by Vega driven price increases), though the near term impact of this is expected to be negative for the strategy. The issuance calendar is robust and should provide some opportunity for managers participating in them. Convertibles being fair value means that the only logical argument for going overweight Convertibles is as a credit substitute. The equity call provides an upside for high yield credit investors and the relatively short duration protects convertible arbitrage portfolios from the risk of rising rates.

768804 785 764

806

714688

632

567520 526

0

100

200

300

400

500

600

700

800

900

0

50

100

150

200

250

300

350

400

450

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Num

ber o

f Iss

ues

Mar

ket V

alue

($ b

illio

n)

Convertible Market Snapshot

Source: Barclays Capital


INVESTCORP Fixed Income Relative Value Environment Report | 1st Quarter 2014

Fixed Income Relative Value Arbitrage Strategy View It is instructive, though by no means comprehensive, to think of traditional G3 Fixed Income Relative Value (FIRV) strategy as having four return drivers and one overriding constraint. The four return drivers are pricing of spreads across market segments, pricing of duration risk across segments of the term structure, pricing of volatility both explicitly in the derivatives market and implicitly through Convexity in the curve and the pricing of liquidity. The implementation of these trade structures involves a copious amount of financing (cash and collateral) and this forms the overriding constraint to articulating views and exploiting them. The accepted view that FIRV is akin to picking nickels in front of a steamroller is very accurate with mispricing opportunities being small (nickels) and the financing- both cash and collateral- the source of large drawdowns (steamroller). Each of these sources of returns- spreads, term premiums, volatility and liquidity also provide security/segment selection opportunities that adds to the return from exposure to risk premia.

We will start by examining publicly available indicators that capture the opportunity set based on these four sets of indicators and round it off with what we see happening in the financing markets.

Spreads We will look at three broad markets which price risks off the treasury curve- the interbank unsecured swap market, the market for municipal debt and the agency mortgage markets to get a sense of the level of attractiveness of the opportunity. Spreads are a pure measure of expected return for a arbitrage manager for assuming the risk.

USD Swap Rates Swap spreads are at all-time lows. They have ticked up since the talk of taper from Chairman Bernanke in May, but still normalized at levels close to 1 standard deviation below long term averages for both the 5 year and the 10 year point. The return to this strategy and other such spread trades are similar to carry trades- borrow in lower rate markets (treasury) and lend at higher rate markets (swap) – we continue to hold that the current returns do not justify levering up this trade and taking on the risk of an increase in spreads.

‐20

0

20

40

60

80

100

120

140

160

3‐Jan‐00 3‐Jan‐01 3‐Jan‐02 3‐Jan‐03 3‐Jan‐04 3‐Jan‐05 3‐Jan‐06 3‐Jan‐07 3‐Jan‐08 3‐Jan‐09 3‐Jan‐10 3‐Jan‐11 3‐Jan‐12 3‐Jan‐13

bps

10 year Swap Spreads

10 year Spread Mean + 1 SD ‐ 1 SD

0

20

40

60

80

100

120

140


bps

5 year Swap Spreads

5 Year Swap Rates Mean + 1 SD ‐ 1 SD

Source: Bloomberg



Source: Bloomberg

The picture from SIFMA swaps is not very encouraging either. The ratio that represents both risks of default as well as tax benefits of investing in municipal paper is unusually low. While it has improved from its historical lows, it is still well below its long term average. Managers can go short and long the spread, but the ratio is more volatile than it seems because of the low interest rate environment we are in. The absolute spreads are profitable only with very large notional exposure to these spreads with its associated drawbacks.

The municipal market rate – swap ratio is below its -1 historical Standard Deviation. At current levels of 26 it provides a cheap option to play for increase in municipal rates as a ratio of swap rates.

The rewards for taking on mortgage risks (prepayment primarily) have improved slightly over the year starting end of May, but they still remain close to – 1 standard deviation away from their long term mean. All spreads have backed up since the communication of tapering by the fed and the opportunity looks more attractive than it did at the end of the last quarter, but in absolute numbers the returns are dismal.

0

1

2

3

4

5

6

7

8


SIFMA LIBOR Ratio

SIFMA Curve LIBOR 3M

0

20

40

60

80

100

120

140


SIFMA Swap Ratio

SIFMA Swap ratio Mean + 1 SD ‐ 1 SD

‐40

‐20

0

20

40

60

80

100

120

140

160

180


bps

Mortgage 30 year Spreads (Treasury)

Fannie Mae 30 year Mean + 1 SD ‐ 1 SD



Duration Exposure In principle, term structure of default risk free interest rates can be decomposed into three components – expectations of future spot rates, the return for assuming the uncertainty of the path of future spot rates (Duration premium) and the difference between time average and average of per period average of rates (Convexity premium or drag). We will for our purposes here focus on the Duration risk as captured by the 5y-10y spread in the swap curve. The spread between the two rates is stripped off the market expectations of spot rates in the near term (who has point estimates of expected spot rates 5 years ahead)- and represents the (unscaled) market price of risk.

The term premiums in the swap markets are as high as they have ever been and its volatility as is evident from the chart provides skilled managers with the ability to trade this term premium profitably. Typically, FIRV managers are

partial to positive carry trades and so prefer steepeners to flatteners; the current steepness does not bode well for this trade.

Convexity risk We measure the degree of convexity or curvature by looking at 3 relatively liquid parts of the swap curve- the 5, 10 and 20 year points. The spread fell sharply in June 2013 (or 10 year rates sold off more than 5 or 20 year rates). The current levels of spreads make it reasonably attractive to trade butterflies.

The trading of convexity (like Gamma trading in options markets) requires an increase in market volatility levels. The realized volatility has increased largely on the speculation about the timing of the tapering of Federal Reserve’s QE program and anecdotally because of deleveraging in some parts of the asset markets where the marginal investor was levered (such as mortgages). Higher levels of volatility are good for FIRV managers who are long convexity and who will trade this to eke out a return.

‐0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Jan‐00 Jan‐01 Jan‐02 Jan‐03 Jan‐04 Jan‐05 Jan‐06 Jan‐07 Jan‐08 Jan‐09 Jan‐10 Jan‐11 Jan‐12 Jan‐13

5y 10y Term Spread

Spread Mean + 1 SD ‐ 1 SD

‐0.8

‐0.7

‐0.6

‐0.5

‐0.4

‐0.3

‐0.2

‐0.1

0

0.1

0.2


5 10 20 Fly

5‐ 10‐ 20 Fly Mean + 1 SD ‐ 1 SD

Source: Bloomberg

Source: Bloomberg



Source: Bloomberg

And this increase in realized volatility is getting priced in the options market both in swaptions …

… and Treasury option markets. The uptick in realized volatility is good for FIRV managers trading convexity and the increase in implied volatility for managers who trade volatility surfaces

Liquidity A classic provision of liquidity trade in the FIRV space is trading the spread between on-the-run issues and off-the-run issues. This spread has been on a secular decline and does not provide the opportunity that it provided a decade ago. The opportunity is also skewed by the actions of the Federal Reserve that through its QE program has removed a lot of treasury security from the markets with implications for the Repo markets as well.

The widening of some of the spreads does represent an increase in liquidity premium, but the simpler FIRV trades such as selling the on-the-run treasury and buying off-the-run is no longer profitable for the amount of volatility in the spreads.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2


10 Year Swap Volatility

Volatility Average0

20

40

60

80

100

120

140

160

17‐Jun‐02 17‐Jun‐03 17‐Jun‐04 17‐Jun‐05 17‐Jun‐06 17‐Jun‐07 17‐Jun‐08 17‐Jun‐09 17‐Jun‐10 17‐Jun‐11 17‐Jun‐12 17‐Jun‐13

Barclays Swaption

0

50

100

150

200

250

300


Merrill Rate Implied Vol Index

Merrill Rate Implied Vol Index

0

1

2

3

4

5

6

7

8


US On‐the‐run/ Off‐the‐run Spread

10 Year OTR/OFR Mean + 1 SD ‐ 1 SD

Source: Bloomberg



Financing Risk There are two different time series that we will use to examine the financing conditions in addition to an index created by Citibank. The first is the conditions in the market for collateralized lending (Repos) against general fungible collateral; and this presents a picture of funding conditions in the largely non-bank financial intermediary markets and another the LIBOR OIS spread for condition in the unsecured short term interbank funding market. In both cases we will compare this to a fed fund proxy (effective Fed Funds rate in the case of Repos and OIS swap rates in the case of LIBOR).

Source: Bloomberg

The general collateral market had been under some stress with issues arising from the availability of collateral following QE3. Repo rates are close to zero in line with effective fed funds rate and now trade at a 6 bps below fed funds rates and have trended up since the beginning of the year signaling return to normalcy.

The LIBOR OIS spread is at historical low levels in large measure because of the liquidity injected by the Federal Reserve and the quelling of fears about bank failures in the US. Given the high levels of excess bank reserves and the improvement in the quality of bank balance sheets it is not surprising that this one indicator from the dog days of the 2007/08 crisis is calm.

‐0.4

‐0.3

‐0.2

‐0.1

0

0.1

0.2

0.3

3‐Nov‐09 3‐May‐10 3‐Nov‐10 3‐May‐11 3‐Nov‐11 3‐May‐12 3‐Nov‐12 3‐May‐13

Fed Funds Less Repo

Fed Funds Less GC Mean + 1 SD ‐ 1 SD 12 per. Mov. Avg. (Fed Funds Less GC)

‐

0.500

1.000

1.500

2.000

2.500

3.000

3.500

4.000

Dec‐01 Dec‐02 Dec‐03 Dec‐04 Dec‐05 Dec‐06 Dec‐07 Dec‐08 Dec‐09 Dec‐10 Dec‐11 Dec‐12

LIBOR ‐ OIS USD



Market liquidity indicators – such as the Citi Market Liquidity Index –show continued improvement in the financial liquidity conditions. The indicator ticked up (signaling poorer liquidity) on the back of some short term stress in the most liquid parts of the fixed income markets- agency, 5 year and 10 year points on the term structure. Fed’s decision to not taper in September and the very benign reaction .

Conclusion Fixed Income Relative Value is a mixed bag and almost all of it is a reflection of the money market conditions. The strategy thrives on volatility – both realized and implied in the options markets – to thrive. Lower expected volatility brings down implied volatility levels in options making selling options as a trade unprofitable; it also brings down expected term spreads and anticipation of profits both from term structure trades and trades involving convexity. The recent uptick in realized and implied volatility – though sharp and painful - bodes mildly well for the strategy if it is sustained, and represents a secular shift away from a low volatility environment to one that is more “normal”. We think managers who are positioned to profit from volatility will do well in the near term. The overriding constraint to FIRV- availability of financing especially collateralized lending- is affected by actions of central banks and the wave of new regulations including capital rules and reining in of the dealer banks through Volcker rule. The change in market structure would provide for talented to earn above average returns without juicing up their portfolio with leverage, but we are not there yet in the evolution of the markets that are dominated by Fed actions.

(1.50)

(1.00)

(0.50)

‐

0.50

1.00

1.50

2.00

2.50


Citigroup US Market Liquidity Index

Source: Bloomberg



Credit Investing in a Rising Rate Environment


Credit Portfolio Management in a Turning Rates Environment

Elena Ranguelova Investcorp

Arthur M. Berd General Quantitative

November 2013

Investcorp 280 Park Avenue, 37th Floor New York, NY 10017 +1 (917) 332 5700 www.investcorp.com

© 2013 Investcorp

The information and opinions contained herein, prepared by Investcorp Investment Advisers LLC (‘Investcorp’) using data believed to be reliable, are subject to change without notice. Neither Investcorp nor any officer or employee of the firm accept any liability whatsoever for any loss arising from any use of this publication or its contents. Any reference to past performance is not indicative of future results. This report does not constitute an offer to sell or a solicitation of an offer to purchase any security and is provided for informational purposes only.

Unless otherwise noted, ‘Investcorp’ refers to Investcorp Investment Advisers Limited, Investcorp Investment Advisers LLC, N.A. Investcorp LLC, and its affiliates.

Credit Portfolio Management in a Turning Rates Environment Elena Ranguelova1 Arthur M. Berd2

November 2013

Executive Summary This paper analyzes correlations between credit spreads and interest rates

across various sectors and credit ratings in the US. Our work was prompted by

chairman Bernanke’s announcement this summer of possible tapering of the

ongoing quantitative easing program which marked a turning point for interest

rates from their historically low levels. We analyze data from 1990 to the

present and use a statistically robust multi-factor risk model framework which

can be calibrated to draw both long-term and short-terms conclusions. Our

findings are relevant for credit portfolio managers contemplating the impact of

rising interest rates and steepening Treasury curve on corporate bond portfolios.

Consistent with our earlier studies, we find strong negative correlation

between sector spreads and rate shifts and twists. A uniform increase in rates is

associated with tighter credit spreads, while a uniform drop in rates leads to wider

spreads. In most industries, with the exception of the banking and brokerage and

the consumer sector, lower credit quality is associated with stronger

negative correlation.

We compare our current estimates with the results of a similar analysis we

conducted in 2003 and find many similarities but also some notable differences.

The long-term models estimated currently and 10 years ago show similar

patterns. However, the short-term versions are quite different. The short-term

correlation estimates in 2013 are much weaker than those from 2003 – likely a

result of the Fed’s ongoing quantitative easing program which has weakened the

normal relationships between the economic recovery (represented by spreads) and

monetary policy (represented by rates). Moreover, correlation patterns in

the banking and brokerage sector have changed prior and post the financial crisis.

These results have important implications for risk management as well

as for identifying relative value opportunities across sectors with different

rate sensitivities.

1. Head of Credit and Equity Strategies, Investcorp, 280 Park Avenue, 37Fl, New York, NY 10017. 2. Founder and CEO, General Quantitative LLC, 405 Lexington Avenue, 26Fl, New York, NY 10174.

Contents

Section 1 Introduction 1

Section 2 The Co-Movements of Credit Spreads and Interest Rates 2

Section 3 Estimates from the Multi-Factor Risk Model 5

Section 4 Duration Management of Credit Portfolios 10

Section 5 Conclusions 14

References 15

Appendix 1 16

Appendix 2 17

Credit Portfolio Management in a Turning Rates Environment 1

Section One

Introduction The gradual recovery of the U.S. economy from the consequences of the financial

crisis has brought the prospect of the Fed ending its extraordinary quantitative

easing (QE) policies. The "moderate tapering" of the rate of QE, pre-announced

in May 2013, has jolted the bond market and perhaps marked the turning point

in the interest rates from historically low levels. Although the timing might still

be uncertain, the expected eventual rise in rates has come to the forefront of

many investors’ concerns.

Over the past few years, we have witnessed an (albeit slow) economic recovery

and a concurrent emergence of a benign credit cycle associated with tight spreads

and low volatility. The management of credit portfolios in such an environment

requires a more precise positioning with respect to the movements of the

underlying interest rates, as the credit-specific spread movements become less

pronounced and the impact of systemic factors becomes relatively more important.

It is a widely held belief among credit bond portfolio managers that rates and

spreads are negatively correlated. The main fundamental reason is that both

Treasury yields and credit spreads reflect the state of the economy, and

therefore one can expect their changes to be correlated to the extent that they

are caused by the same underlying economic expectation. A worsening economy

is generally associated with falling rates, while an improving economy is

associated with rising overall level of interest rates. For spreads the direction of

the dependence is precisely the opposite — spreads rise when the economy

deteriorates and default risk rises, and they tighten as the economic conditions

improve. Accordingly, analysts find negative correlation between corporate bond

spreads and US Treasury yields (see Ng, Phelps and Lazanas (2013) for a recent

look into this issue).

The above statement on negative correlation applies only to overall changes

in Treasury rates, i.e., to “parallel shifts” of the Treasury curve. However, the

shape of the yield curve can change in a much more complex way, including

twists and butterflies. The dependence of spreads on such changes in the

underlying yield curve is much less documented. In terms of economic as well as

statistical significance, the parallel shifts and (flattening or steepening) twists

are the primary modes of change of the Treasury curve, explaining more than

80% of its variability. Therefore, we focus on these factors and their impact on

credit spreads.

In this paper we revisit the analysis of the co-movement between the interest

rates and spreads originally published in 2003-2004 (see Berd and Ranguelova

(2003) and Berd and Silva (2004)). We analyze the relationship between US

interest rates and credit spreads using the statistically robust framework of the

Barclays POINT® Global Risk Model (see Lazanas et al. (2011)).

2 Credit Portfolio Management in a Turning Rates Environment

We confirm the strong evidence that rates and spreads are negatively

correlated: higher rates are associated with tighter spreads and steeper credit

curves while lower rates are associated with wider spreads and flatter credit

curves across all industries. The change in the slope of the treasury yield curve

has a different effect on credit OAS: yield curve flattening typically coincides

with narrowing and steepening of credit spread curves, with yield curve

steepening having the opposite effect. Furthermore, we observe characteristic

differences in the impact of rates on various sectors and on spread curve shapes

and OAS dispersion.

Our results are qualitatively robust to different periods of analysis and

different data calibration methodologies. However, our findings are conditional

on the historical relationship between interest rates and spreads. Managers

forecasting a reversal on this stable historical pattern (e.g., due to QE policies

and intervention or increased sovereign risk) will find this analysis less useful3.

Our findings have significant implications for credit portfolio managers. The

negative correlation of spreads with rates affects the duration management of

credit portfolios, particularly when there is a significant under- or overweight

position with respect to a benchmark containing Treasury bonds. The

differential effect across industries and ratings gives rise to potential curve-

driven cross-sector relative value opportunities.

Section Two

The Co-Movements of Credit Spreads and Interest Rates Before presenting the model results, let us define the relevant components of the

interest rate curve and illustrate the historical co-movement of credit spreads

and interest rates.

2.1 Defining the Treasury curve shifts and twists We define the Treasury shift factor as a uniform increase in the five key-rate

factors included in the Barclays POINT® Global Risk Model4, corresponding to

the 2, 5, 10, 20 and 30-year key rates. The Treasury twist factor is defined as a

series of changes in the same key-rate factors that correspond to a steepening

rotation around the 10-year maturity. Table 1 uses a 10 bp scale for shifts and

twists as an illustration.

3. In this regard Eisenthal-Berkovitz et al. (2013) document positive correlation between treasury

and credit bonds for some European distressed countries. 4. We exclude the 0.5 year key rate factor in order to avoid picking up dependencies on peculiar

movements of the short end of the Treasury curve.


These definitions differ slightly from the statistically more precise approach

known as principal component analysis. However, they get us pretty close to

the true principal components of rates changes and are easier to visualize

and discuss.

Table 1: Treasury Curve Primary Factors

Key Rate Maturity (years) 2 5 10 20 30

Treasury Curve Shift (bps) 10 10 10 10 10

Treasury Curve Twist (bps) -10 -5 0 5 10

To explain in practical terms, assume that the yield curve has undergone an

arbitrary change in each of its key rate points, denoted as iy , where the index i

corresponds to maturities 2, 5, 10, 20, and 30 years. We can now define the

approximation to the yield curve change in terms of the shift and twist factors as a

linear combination of a unit parallel shift and a unit steepening twist with yet

undetermined coefficients and the residual term containing the portion of the yield

curve change that is not captured by shift and twist:

30

20

10

5

2

30

20

10

5

2

21012

11111

twistshift

y

y

y

y

y

If we assume that, by construction, the residual term does not contain either

a parallel shift of a steepening/flattening component, we can easily find the

factor loadings shift and twist of the two primary yield curve components

as follows:

3020105251

yyyyyshift

302052 22101

yyyytwist

These formulas justify the representation of the shift and twist factors

in Figure 1.

2.2 Historical co-movement of credit spreads and interest rates The past two decades were characterized by large shifts and twists of the

Treasury yield curve, with the current levels of interest rates just off the

historical lows and stands almost 600 bps lower than in 1990, while the curve

steepness being close to its historical highs. At the same time, the Barclays

Credit Index OAS has experienced wide swings from the tightest levels of


around 50 bps in early 1997 to the widest of over 535 bps in November 2008,

returning to moderate levels of 140 bps more recently. The corresponding time

series are shown in Figure 1, where we show the cumulative time series of the

shift and twist factors, normalized to start from zero in December 1989, and

the OAS.

We can identify several periods in the past fourteen years when rate changes

have visibly correlated with credit spreads.

First, the first Gulf War in 1991 resulted in a quick drop in Treasury rates by

over 80 bps and a moderate 5 bp steepening of the curve. At the same time, the

credit OAS widened by almost 60 bps.

The dramatic rates swings in 1994, ignited by the Mexican peso crisis and

followed by MBS market problems in the US, saw the Treasury rates shift up by

about 250 bps, with a simultaneous flattening of the curve by 45 bps. The OAS

over the same period remained range bound, eventually widening by 10 bps,

almost all of it during the last four months of the year, when most of the

Treasury curve flattening also took place.

Then, in August-October 1998 the Treasury curve shifted 100 bps in a

negative direction and twist moved 10 bps in a positive direction after the

Russian default and LTCM crisis prompted the Fed to cut the short rates.

Spreads moved sharply wider by 40 bps, but then reversed just as the yield curve

twist subsided and the rates themselves moved higher in the beginning of 1999.

Next, the interest rate curve inverted (twist became negative) in the latter

part of 1999 and beginning of 2000 as the FOMC raised the Fed Funds rate up

to 6.50%, pushing the 2 year yield to 6.70% while the Treasury buybacks, budget

surpluses and dampened inflation expectations helped to keep the long yields

subdued at 6.00%. The credit spreads widened through this period by over 60

bps, apparently anticipating the coming risks in the equity markets which were

nearing the end of the Nasdaq bubble.

Figure 1: Treasury Shift and Twist vs. Credit Index OAS, 1990 – 2013

Source: Bloomberg

-800

-600

-400

-200

0

200

400

600

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Spread Cum Shift Cum Twist


Then the rates curve steadily shifted down (200 bps) and significantly

steepened (80 bps) from 2000 till 2003 as the Fed cut rates 12 times, from 6.50% to

1.25%. Spreads swung widely for most of this period, from lows close to 100 bps to

highs above 220 bps. The correlation of spreads with the twists becomes

significantly positive — in contrast to the negative correlation with the level of

rates. Spreads seemed more sensitive to expectations for the near-term economic

outlook, related to the short end of the yield curve, than to long-run growth and

inflation, which are related to the long end of the curve.

The economic recovery, accompanied by the rebound in rates (shift higher) and

gradual reduction of the steepness of the Treasury curve from 2002 through the

beginning of 2006, also saw the credit spreads tightening from over 200 bps to the

lowest of 78 bps at the end of this period. Yet again, we see the negative

co-movement of spreads and Treasury shifts and positive co-movement of spreads

and twists.

And of course the most dramatic demonstration of this relationship came in

2007 and 2008 when the unfolding financial crisis pushed the credit spreads to

historic wides, while the interest rates were brought further down by both the

actions of the Fed and the effects of the economic recession. Between July 2007

and the end of 2008 the curve shifted down by another 300 bps across the board,

while steepening by 50 bps.

The emergence from the crisis in 2009 brought a small rebound of the rates up

(driven by the long end) but the still ongoing Fed quantitative easing program has

led to further shift down and maintenance of the historically steep shape of the

rates curve. The fastest credit spreads tightening coincided with the rates shift

rebound in 2009.

However, the co-movement of rates and spreads from 2011 onward shows some

change, with spreads widening while rates decline — as before — but with

Treasury curve steepening. We discuss this in more detail later in the report.

Of course, spreads are influenced by many other factors beside the Treasury

curve and the macro-economic outlook encoded therein. However, typically the

significant trends of the rate changes do get reflected in spread moves. While the

anecdotal evidence presented in this section helps in motivating our research

project, it is not sufficiently precise to draw conclusions for the future. To do that,

we need a robust statistical estimation of co-movements in treasury rates and

credit spreads, which we undertake in the next section.

Section Three

Estimates from the Multi-Factor Risk Model To quantify the joint behavior of interest rates and credit spreads, we turn to the

Barclays POINT® Global Risk Model (see Appendix 1 and Lazanas et al. [2011]

for a good introduction to these types of models). The current approach employs

the DTS (duration times spread) methodology to model credit risk (see Silva


[2009]). However, the model allows for different risk configurations. In

particular, for this report, we use the following decomposition: six Treasury (key-

rate) factors and 27 spread factors, from a combination of nine industries times

three rating buckets (AAA/AA, A, and BBB)5.

The model estimates the covariance matrix of all common driving factors as

well as the issuer-specific risk of bonds belonging to each industry/rating sector.

We analyze the covariance estimates as of June 2013 and discuss their

implications for the relationship between rates and spreads.

The multi-factor risk model has different calibrations available. In this paper

we use two standard ones: the first weights all past observations equally, while

the second is an exponential-weighted moving average (12month half live) that

overweights recent data relative to more distant historical one. The corresponding

versions are referred to as long-term and short-term model, respectively.

In order to take into account the issuer-specific risk and incomplete

diversification of typical investor’s portfolios, we defined a sector portfolio to

consist of 20 equally weighted bonds having on average the same maturity and

same OAS as the corresponding sector. By construction of the risk model, such

portfolio is not exposed to spread twist or OAS dispersion factors. The sector

correlations discussed in this paper are the correlations of OAS changes of these

hypothetical sector portfolios with the Treasury shift and twist factors.

The results are shown in Table 2 for the long- and short-term models

estimated as of June 2013. For comparison, and to highlight the time variability

of estimates, we also show the results estimated at the time of the most recent

turning rates environment: Table 3 shows the results for the long- and short-

term models estimated as of December 2003.

The statistical dependence patterns found in these results are discussed in

the rest of this section. Their implications for the duration management of credit

portfolios are covered in section 4.

3.1 The effect of a Treasury curve shift We start by documenting the effect of the Treasury curve shift on credit spreads.

The results (Table 2) demonstrate a strong negative correlation between these

variables for each credit sector. Uniform increase in rates is associated with

tighter credit spreads while uniform drop in interest rates leads to wider credit

spreads.

As an example, we find a –33% correlation for the A-rated Banking and

Brokerage sector in Table 2, which implies that if all rates rise by a typical

amount (an amount equal to 1 standard deviation of the shift factor), the credit

spreads in this sector will likely tighten by amount equal to 0.33 of a typical

movement (a standard deviation) of the sector's spread factor, all else equal. To

5. We use this decomposition to keep our approach consistent with previous versions of this research

and to allow the analysis to be done across different levels of spread, here proxied by different ratings. The qualitative results should be similar across approaches.


translate this statement into nominal levels, we note that the standard

deviation of the shift factor, according to the risk model, is 24 bps, and the

standard deviation of the A-rated Banking and Brokerage sector spreads is 14

bps, therefore the above prediction is that a 24 bp positive shift in rates will on

average translate into almost 5 bps of tightening of the A-rated Banking and

Brokerage spreads.

Table 2: Spread Correlations with Treasury Curve Shifts (June 2013)

Model Long-Term Model (UW) Short-Term Model (WW)

Rating AAA/AA A BBB AAA/AA A BBB

Financials Banking and Brokerage -32% -33% -31% -39% -34% -38% Financial Companies, Insurance & REITS -26% -33% -38% -21% -34% -42%

Industrials Basic Industries and Capital Goods -32% -35% -35% -25% -26% -36% Consumer Cyclicals -38% -34% -30% -29% -27% -32% Consumer Non-Cyclicals -35% -32% -30% -25% -23% -26% Communication and Technology -31% -34% -36% -19% -29% -37% Energy and Transportation -37% -37% -38% -21% -31% -36%

Utilities -24% -35% -34% -34% -29% -30% Non-Corporate -32% -34% -36% -23% -36% -15%

Source: Barclays POINT®

The negative correlation between sector spreads and rates shift is, overall,

quite similar across both the long- and short-term versions of the models.

However, there are some important differences regarding the range of

correlations: they are significantly more dispersed on the short-term model,

while showing stronger convergence (about –30%) for the longer-term model.

Another interesting difference is that the correlations are stable across ratings

in the longer-term model while tending to show a negative slope for the

short-term model (e.g., correlations are typically more negative for lower

rating portfolios).

For comparison and to highlight the time variability of these estimates, Table

3 shows the results estimated at the time of the most recent (potentially similar)

turning rates environment: December 2003. We note that while the long-term

risk models estimated currently and 10 years ago show similar patterns, the

short-term versions are quite different. In particular, the short-term estimates

from 2003 showed a significantly stronger negative correlation (an average of

about -50%, against about -30% for the three other calibrations).

One could argue that these weaker correlations are due to the effects of the

Fed's quantitative easing program, which has weakened the normal

relationships between the economic recovery (represented by spreads) and

monetary policy (represented by rates). We will see an even stronger evidence of

this in the twist factor impact. If this hypothesis is correct, and if one assumes

that the QE program is about to end — taking the economy closer to its

historical norm — then the long-term model or perhaps even the models

estimated in 2003 may be more appropriate for prediction than the short-term

model of the 2013 vintage.


In the end, the particular patterns of dependence of the strength of negative

correlation on the sector or credit quality are driven by several factors, including

the underlying economics of the corresponding sectors, fiscal and monetary

policy, and the varying composition of the Credit Index, which occasionally has a

greater representation of certain types of companies in a particular rating class.

These shifts were particularly visible after the financial crisis. Many companies

were downgraded from AAA/AA to A, or even to the BBB category, thus

changing the compositions of those baskets and their dependence.

Table 3: Spread Correlations with Treasury Curve Shifts (Dec. 2003)



Financials Banking and Brokerage -31% -31% -22% -56% -52% -46% Financial Companies, Insurance & REITS -38% -31% -29% -52% -43% -45%

Industrials

Basic Industries and Capital Goods -31% -43% -36% -61% -62% -56% Consumer Cyclicals -41% -41% -22% -58% -56% -49% Consumer Non-Cyclicals -40% -35% -33% -57% -53% -55% Communication and Technology -31% -38% -31% -44% -51% -45% Energy and Transportation -41% -43% -40% -57% -60% -60%

Utilities -21% -36% -29% -56% -54% -40% Non-Corporate -31% -35% -41% -60% -53% -55%


The dependence patterns in correlations between industry sector/rating

category spreads and interest rates shift factor, which remain valid across time

and model types, include:

Cyclical industries exhibit a stronger negative correlation with the shift

factor than do non-cyclical industries. This should come as no surprise,

because by definition the dependence of cyclical industries on economic

decline or recovery, reflected by the changing levels of interest rates, is

stronger.

In most industries, with the exception of the Banking and Brokerage and

Consumer sectors, lower credit quality is associated with greater degree of

negative correlation. This is rather intuitive, because companies with

lower credit quality are typically more affected by the changes in the

economic outlook, as reflected in the general level of interest rates.

Equally telling are some of the dependence patterns in correlations which

changed substantially with time and depend strongly on model type:

In the years prior to the financial crisis, the Financials sector uniformly

exhibited a pattern of the higher credit ratings being associated with

greater degree of negative correlation (see Table 3). After the crisis, the

pattern changed — the correlations in the Banking and Brokerage sector

are now almost independent of the rating level, and those in the Financial

Companies, Insurance and REITs are actually strongly increasing with the

lower rating (see Table 2), closer to the pattern seen for other industries.


Before the crisis, the short- and long-term models showed a similar

variability of correlations across sectors and ratings. After the crisis,

markets tended to move more in tandem, and long-term variability

decreased. Only recently (short-term model) do we see an increased range

of behavior, more consistent with historical patterns.

3.2 The effect of a Treasury curve twist We now discuss the effect of the Treasury curve twist on credit spreads. One

of the biggest casualties of the financial crisis and subsequent QE-filled years

was the statistical dependence of credit sectors on the Treasury twist factor.

Credit spreads across all sectors and ratings used to have a consistently

positive correlation with the steepening yield curve (see Table 4 for 2003

estimates). That is, a steepening of the curve is associated with higher spreads.

This was consistent with what we observed during the periods at the bottom of

the economic cycle when the curve inversions and steepening were driven by the

Fed actions at the short end of the curve.

However, quantitative easing has changed this situation dramatically, with

the Fed now explicitly targeting also the longer end of the rate curve. The

moderate flattening of the curve caused by the start of the QE a few years ago

coincided with some spread widening that arose from uncertainty about the

strength of the economic recovery. Contrary to the normal pattern, this

combination resulted in negative correlations between Treasury twists and

spread. More recently, the further steepening of the curve due to concerns about

the end of QE — while the short end is still nailed down by the Fed's near-zero

interest rate policy — coincided with a modest credit pickup, again in contrast to

the long-term norm. This is most obvious if one contrasts the results from the

more recent short-term model in Table 5 with those from the short-term model

as of 2003, in Table 4. The effect is also seen in long-term calibrations, but to a

lesser extent. In this regard, changes in monetary policy can have a significant

effect on how portfolios react to changes in interest rates.


Table 4: Portfolio Spread Correlations with Treasury Curve Twists (Dec. 2003)



Financials Banking and Brokerage 17% 19% 15% 33% 31% 30% Financial Companies, Insurance & REITS 20% 18% 16% 35% 33% 23%

Industrials

Basic Industries and Capital Goods 15% 21% 20% 23% 28% 31% Consumer Cyclicals 19% 21% 15% 22% 32% 40% Consumer Non-Cyclicals 19% 17% 18% 25% 23% 25% Communication and Technology 16% 20% 18% 26% 32% 36% Energy and Transportation 18% 21% 21% 26% 29% 30%

Utilities 11% 18% 16% 27% 31% 33% Non-Corporate 15% 18% 21% 21% 26% 36%


Table 5: Spread Correlations with Treasury Curve Twists (June 2013)



Financials Banking and Brokerage 13% 13% 13% -26% -24% -26% Financial Companies, Insurance & REITS 11% 13% 12% -16% -23% -28%

Industrials

Basic Industries and Capital Goods 11% 12% 13% -18% -18% -24% Consumer Cyclicals 13% 13% 14% -20% -19% -22% Consumer Non-Cyclicals 12% 12% 12% -18% -17% -19% Communication and Technology 9% 13% 14% -14% -20% -25% Energy and Transportation 12% 13% 14% -15% -22% -25%

Utilities 10% 12% 13% -23% -20% -21% Non-Corporate 8% 13% 14% -14% -25% -12%


Section Four

Duration Management of Credit Portfolios The results of our study have important implications for risk management as

well as for identifying relative value opportunities across sectors with different

interest-rate sensitivities.

The directionality of credit spreads and interest rates poses a challenge to

credit investors who want to manage the interest rate exposure of their portfolio.

Because spreads tend to move in conjunction with underlying interest rates, a

corporate bond is not fully insulated from rate movements if hedged with the

same-duration Treasury bond. In other words, a credit bond portfolio

benchmarked against government bond index (such as the overweight credit

portion of a typical fixed income portfolio) will not be neutral to interest rate

movement if it has a matching duration with the Treasury benchmark.

Indeed, duration measures the sensitivity of bond prices with respect to the

change in yield. For a given shift in interest rates, the corresponding change in


the corporate yield is smaller because it gets partially offset by the tightening of

the spread. To account for this fact, we introduce the concept of Effective

Duration, defined as the sensitivity of corporate bond prices to changes in the

interest rate component of the yield.

The multi-factor risk model allows us to estimate the volatility F of the

shift and twist factor of the yield curve as well as the volatility S of the typical

industry/rating sector portfolio spread and its correlation treasFS, with the

rate factors. Given these values, the expected change in spread given the change

in the treasury factor (either shift or twist) is:

F

treastreas

S

FFS

S

,

Using this relationship, we can estimate the price effect of the parallel shift

on the credit bond using the chain rule:

shiftshiftshift F

S

S

P

PF

Y

Y

P

PF

P

P

111

In the first term in the left hand side, we introduced the change in the

underlying yield of the Treasury curve, which by construction is assumed to be

same as the change in the shift factor when the parallel shift is the sole

movement of the yield curve. Therefore 1 shiftFY . The fractional change in

price with respect to change in yield is, by definition, the modified duration of

the bond (with negative sign).

In the second term, we introduced the spread, whose relationship with the shift

factor we explained above. The fractional change in price with respect to change in

spread is, by definition, the spread duration of the bond (with negative sign).

Defining the fractional change in price with respect to change in shift factor

as the effective duration (with negative sign) we obtain:

spreadshift

spreadshiftmodeff DFSDD

,

Here, effD stands for the effective duration, modD is the modified duration,

spreadD is the spread duration, is the correlation between spreads and

Treasury shift, spread is the volatility of spreads, and shift is the volatility of

the Treasury shift factor (both volatilities must be measured in absolute terms

and expressed in equal units, e.g. bp/month).

Since the correlation of spreads and yields is negative and quite substantial,

the effective duration will be typically smaller than modified duration. For most

fixed coupon bonds modified duration and spread duration differ very slightly,

hence the effective duration is approximately equal to a fraction of the modified


duration. We denote this fraction as Effective Duration Multiplier effM , and rewrite

the effective duration definition as follows:

shift

spreadshifteff

effeff

FSM

DMD

,1

mod

The estimated values of the effective duration multiplier are shown in Tables

6 and 7, for each of the estimates of the risk model, respectively. To illustrate

with an example, look at Table 6 for the results from the long-term risk model

from 2013, and consider two 10-year par bonds — a Treasury and a typical

corporate bond in A-rated Consumer Cyclicals. Suppose both have modified

duration of 7.5 years, the spread duration of the corporate bond is also 7.5 years.

Table 6: Effective Duration Multipliers for Industry/Rating Sectors (June 2013)




Industrials




We observe that the correlation between the 10-year yield and the spread on

the corporate is –34%. This means that a 10 bp increase in Treasury rates will

be typically accompanied by a decrease in the spread of the corporate bond,

equal to the correlation multiplied by the ratios of the standard deviations of

spreads and rates factors. The standard deviation of the rate shifts is 24.3

bps/month (as determined from the Barclays POINT® risk model), and the

standard deviation of the spreads in A Consumer Cyclicals is 18.2 bps/month.

Therefore, the corresponding spread tightening, predicted by the risk model, is

equal to 10 bps * 34% * 18.2 / 24.3 = 2.5 bps.

The price impact of the 10 bp increase in rates is 7.5 * 0.10 = 0.75 decrease in

price per 100 initial value in both bonds. However, for the corporate bond this

price decrease will be offset by a 2.5 bp decrease in spreads, and associated price

impact of 7.5 * 0.025 = 0.1875 per 100 initial value. Thus the price of the

corporate bond will decrease only by 0.75 – 0.1875 = 0.5625. Since this price

change was effected by a 10 bp rise in rates, the effective duration is 0.5625 /

0.10 = 5.625 years. This effective duration value represents 75% of the original

modified duration of 7.5 years (as reported in the figure).


Table 7: Effective Duration Multipliers for Industry/Rating Sectors (Dec. 2003)




Industrials




Thus, a credit portfolio that is overweight in this corporate bond, while

benchmarked to a Treasury portfolio with matching modified duration will in

fact be mismatched in terms of effective duration, and consequently in terms of

expected sensitivity to interest rate moves.

Another interesting take-away from this analysis is related to the Banking

and Brokerage portfolios. The effective duration of these portfolios is

significantly lower in 2013 (compared with 2003), especially in the short-term

model. As discussed previously, this may be the consequence of the atypical

behavior this industry has registered since the financial crisis.

We emphasize that when measuring the risk of credit portfolios within the

Barclays POINT® portfolio analytics system, the effect of the correlation between

the credit spreads and Treasury rates is fully taken into account by virtue of

using the complete multi-factor risk model with full covariance matrix of

dependencies. The example above illustrates the source of the high contribution

of interest rate risks to the tracking error of many credit portfolios even when

they are apparently well balanced in terms of modified duration.

Many credit portfolio managers are not actively managing the duration or

curve position of their portfolios, but are instead following the constraints imposed

by broader multi-asset class and duration allocations within risk budgeting

frameworks of aggregate fixed income portfolios. In such cases, either the portfolio

managers responsible for asset allocation can take into account the rates-spreads

directionality in setting the goals for the credit PMs, or the credit portfolio

managers can explicitly adjust their duration targets if the implicit assumption in

the asset allocation process is that of independence of rates and spreads.


Section Five

Conclusions In this paper we used the statistically robust framework of the Barclays

POINT® Global Risk Model to analyze the co-movements of interest rates and

credit spreads. The main message is that both shifts and twists of the Treasury

yield curve are accompanied by significant changes in both the level and slope of

the credit spread curve.

We reiterate that this study concerns contemporaneous correlations and is

not, by itself, a statement of causal relationship. Rather, the existence and

robustness of correlations across a long historical period from 1990 until the

present can be taken as a evidence for the common economic driving factors

between rates and spreads.

Portfolio managers need to consider the rates-spreads directionality effects

when fine-tuning their interest-rate hedging strategies and relative value

decisions across credit sectors in the environment when credit specific news are

dominated by macro-economic news leading to significant Treasury curve moves.

The years since our original studies saw periods ranging from very low risk

(2005 and 2006) to extremely high risk (2008), as well as the subsequent

recovery accompanied by the peculiar experience of the Fed's quantitative

easing, which influenced both interest rates and credit markets. As discussed in

section 3, some of the results (such as the negative correlation of spreads and

Treasury curve shifts) remain quite robust, while others (the correlation of the

spreads with Treasury curve twists) have become dislocated or even changed

signs.

Although we do not provide specific forecasts in this paper, we caution

investors to choose their scenarios carefully and pick those they believe will be

representative of the near future, when applying this framework for credit

portfolio management. Whether the most recent estimates will continue to hold

depends on the assumption that economic conditions and the effect of the Fed's

actions on the shape of the Treasury curve will remain the same.

For investors who think that these conditions will change, it is possible that

the more representative statistics for the future may be found in the more

distant past.


References BERD, A. AND E. RANGUELOVA, 2003, “The Co-Movement of Interest Rates and

Spreads: Implications for Credit Investors,” U.S. Credit Strategies

Commentary, June 19, 2003, Lehman Brothers

BERD, A. AND A. B. SILVA, 2004, “Credit Portfolio Management in the Turning

Rates Cycle,” U.S. Credit Strategies Commentary, May 24, 2004, Lehman

Brothers

EISENTHAL-BERKOVITZ, Y., EL KHANJAR A., HYMAN, J., MAITRA, A., POLBENNIKOV,

S. AND A. B. SILVA, 2013, “Sovereign risk spill-over into Euro corporate

spreads,” Barclays Research

LAZANAS, A., SILVA, A. B., GABUDEAN, R. AND A. D. STAAL, 2011, “Multi-Factor

Fixed Income Risk Models and Their Applications,” Handbook of Fixed

Income Securities, Frank J. Fabozzi (Ed.), McGraw Hill.

NG, K., PHELPS, B. AND A. LAZANAS, 2013, “Credit Risk Premium: Measurement,

Interpretation & Portfolio Allocation,” Barclays Research

SILVA, A. B., 2009, “A Note on the New Approach to Credit in the Barclays

Capital Global Risk Model,” Barclays Research


Appendix 1 The Barclays POINT® Global Risk Model

This paper analyzes the relationship between US interest rates and credit

spreads using the statistically robust framework of the Barclays POINT® Global

Risk Model. This is a multi-currency cross-asset model that covers many

different asset classes across fixed income, equity markets, commodities, etc.,

and includes derivatives in these markets. At the heart of the model is a

covariance matrix of risk factors. The model has more than 500 factors, many

specific to a particular asset class. The asset class models are periodically

reviewed. Structure is imposed to increase the robustness of the estimation of

such large covariance matrix. The model is estimated from historical data. It is

calibrated using extensive security-level historical data and is updated on a

monthly basis.

The model offers different calibrations, namely the unconditional and the

conditional models. The unconditional or unweighted covariance matrix requires

fewer assumptions than the conditional covariance matrix and can be thought of

as the long-run level of the covariance matrix. The unweighted covariance

matrix assigns the same weight to every observation in the sample. It has

perfect "memory," i.e., it never forgets a past event, no matter how far back in

the past the event occurred. In particular, it does not distinguish between the

recent and the distant past, which, depending on the circumstances, may be a

desirable feature. The conditional covariance matrix is usually calculated using

a time-weighted estimation method: this method assigns more weight to recent

observations relative to more distant ones, with the goal of conditioning the final

estimates toward the current state of the markets. POINT® uses an exponential

weighted moving average with a half-life of 12 months: a one-year old

observation receives half the weight of the most recent observation. The

unweighted volatility is very stable over time and over the state of the economy,

whereas the weighted volatility is strongly time varying. In the situation when

the dynamics of the market change rapidly, e.g., during the recent credit crisis,

the weighted covariance matrix reflects the changed market conditions in a

timely manner as it allocates more weight to the recent past. Both the speed and

the magnitude of the changes in the weighted volatility estimate are higher than

for the unweighted volatility estimate. This is true both for periods of increasing

and decreasing volatility.


Appendix 2 Quantitative Easing in the United States

Quantitative easing (QE) is an unconventional monetary policy used by

central banks to stimulate the economy when short-term interest rates are at or

close to zero and normal monetary policy can no longer lower interest rates. QE

was first used by Japan in 2001-2006 and involves an expansion of the central

bank’s balance sheet. It is typically implemented by the central bank buying

long term financial assets from commercial banks and other private institutions,

thus increasing the monetary base and lowering the yield on those financial

assets. In the United States, QE was first introduced in November 2008 in

response to the financial crisis exacerbated by the default of Lehman Brothers.

It was followed by two other rounds of QE with the current one still ongoing. Fed

Chairman Ben Bernanke argued in 2009 that the Fed’s QE program is actually a

“Credit Easing” program as it targets to buy a particular credit mix of loans and

securities (as opposed to buying government bonds) with the goal of using that

particular composition of assets to affect credit conditions for households and

businesses.

(http://www.federalreserve.gov/newsevents/speech/bernanke20090113a.htm)

QE1: November 2008 – June 2010

In November 2008, during a period of financial panic in the aftermath of the

Lehman default, the Fed announced plans to buy $100bn of GSE debt and

$500bn of agency mortgage-backed securities over the following few quarters.

The Fed eventually accumulated a balance sheet of $2.1 by June 2010 when it

stopped the program as the economy started showing signs of improvement.

QE2: November 2010 – June 2011

In August 2010, the Fed decided that the economic growth in the US was not

as robust as expected and they resumed purchases, and resume purchasing

$30bn of 2- and 10-yr Treasuries every month to maintain the Fed balance sheet

around $2 trillion. In November 2010, the Fed announced that they will buy

additional $600bn of Treasury securities by the end of Q2’11 as a second

significant round of QE.

QE3: September 2012 – present

In September 2012 the Fed announce a third round of QE, planning to buy

$40bn of non-agency MBS per month, an amount which was raised to $85bn per

month starting Dec 2012. In June 2013, Ben Bernanke announced the possibility

of “tapering” QE3 by scaling down bond purchases from $85bn to $65bn a

month, starting in September 2013. However, on September 18, 2013, the Fed

decided to hold off on tapering the current bond buying program. Current

consensus is that tapering will not start before March 2014 but surprises are

always possible.


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