Global Credit Investing at Loomis Sayles Credit... · Tactical allocation to off-benchmark sectors enhances risk-adjusted returns. Top-down and bottom-up sector teams comprehensively

1MAY 2019 For Institutional and Investment Professional Use Only. Not For Further Distribution.

MANAGER INSIGHT

By the Loomis Sayles Global Fixed IncomeTeam

Global Credit Investing at Loomis Sayles

Philosophy

Our investment philosophy is based on the principle that dynamic active management can exploit inefficiencies in global credit markets. Within our approach, two elements are integral to alpha generation: 1) tactical sector and industry allocation via effective beta management and 2) a concentrated focus on identifying risk-adjusted security-level relative value.

While we recognize that market prices reflect fundamentals over time, they can diverge periodically for a variety of technical factors, such as:

• investor reactions to short-term performance,

• anchoring bias,

• herding behavior,

• the growth of passive ETFs/funds,

• market liquidity,

• changing market participants

• and cross-currency forces.

Over time, these pricing discrepancies typically revert toward fundamental value, therefore making an investment view over a full credit cycle imperative.

Investor tendency to anchor to historical prices and spread ranges, as well as to extrapolate the most recent information or market conditions into the future, can create opportunity for long-term, value investors like us. Additionally, the growing presence of price-insensitive participants, such as yield-seeking foreign buyers, passive players, and central banks can create significant relative value opportunities.

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MAY 2019 2For Institutional and Investment Professional Use Only. Not For Further Distribution.

Risk PremiumWe believe Loomis Sayles’ proprietary risk premium model succinctly highlights the pricing dislocations that frequently occur in markets. The Investment Grade Risk Premium (IGRP), or the credit risk premium available to be captured after accounting for expected losses from credit migration and defaults, has experienced significant volatility over time (see following chart). Prices deviate significantly from underlying fundamental fair value frequently, often exacerbated by an inflated liquidity risk premium, as in 2009 and 2011.

We believe a consistent focus on fundamental value over a credit cycle in conjunction with dynamic active management can enable the exploitation of pricing anomalies and capture this premium. Our bottom-up research effort is critical to our absolute and relative beta positioning, since limiting undesired credit tail risks and seeking the necessary conviction to increase exposure to bonds with above-average spreads and return potential is essential for alpha generation.

INVESTMENT GRADE RISK PREMIUMSeparation of Downgrade Loss and Premium Components

Loomis Sayles analysis, as of 4/30/2019. Drawdown: a drop in the net asset value of an asset class from the peak. IGRP: investment grade risk premium. OAS: option-adjusted spread. Regime periods (credit repair, recovery, expansion/late cycle) are determined by the investment team based on subjective and objective factors, including past economic and asset performance metrics. Views and opinions expressed reflect the current opinions of the investment team, and views are subject to change at any time without notice. Other industry analysts and investment personnel may have different views and opinions.

Expansion / Late Cycle

Recovery

Credit Repair

Downturn

IGRP

Expected Downturn Loss

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700

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1997

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974/

1998

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2001

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/200

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/200

56/

2006

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/200

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2011

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/201

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AS

(bps

)


Alpha ThesisOur guiding principles, or core tenets, drive our repeatable investment process and form the foundation of our alpha thesis. Our singular objective is generating alpha potential over a credit cycle via a benchmark-aware, value style in an information-ratio-efficient manner.

LOOMIS SAYLES GLOBAL CREDIT ALPHA THESIS

TENET PROCESS PROOF POINTS

Overall portfolio credit beta management via targeted industry allocation leads to alpha generation. Incorporating a view over a full credit cycle is imperative.

Rigorous, repeatable sector and product team process of focusing on fundamentals, valuations and technicals identifies the best opportunities. Risk targets are set by the product team and measured relative to the benchmark based on contribution to beta.

We have dynamically shifted portfolio and industry beta exposures through cycles. Long-term historical excess returns have been generated through both the identification of the best risk-adjusted security selection ideas and key top-down portfolio and industry beta positioning.

Idiosyncratic security selection and disciplined position sizing lead to strong returns over market cycles. Downside protection is crucial given negative skew.

Sector/product teams and various proprietary quantitative models identify the best opportunities. Strict adherence to ticker-level contribution-to-beta targets maximize risk/reward.

Tactical allocation to off-benchmark sectors enhances risk-adjusted returns.

Top-down and bottom-up sector teams comprehensively assess risks and forecast sector returns on a quarterly basis to aid the product team in sector allocation decisions.

Strategic allocations to high yield, securitized, loans, and emerging markets have enhanced historical risk-adjusted returns.

A diversified portfolio consisting of core holdings and expected alpha generators minimizes unwanted risk exposures.

Portfolio is diversified across sectors, industries and geographical regions. Portfolio construction balances diversification vs. alpha.

Historically strong information ratio. Portfolio averages over 250 holdings.

Currency and rate exposures should be immunized in a credit portfolio, with the exception of use as a liquidity tool for portfolio risk control.

Currency and key rate duration exposures are immunized to the benchmark via bonds and/or derivatives.

Contribution to historical excess returns from active currency and rates positioning has been minimal.

Tactical sector and industry allocation via effective beta management and a concentrated focus on risk-adjusted security-level relative value are integral to alpha generation.

There is no guarantee that the investment objective will be realized or that the strategy will generate positive or excess return.


VARIABLES THAT CAN SHAPE PORTFOLIO CONSTRUCTION

MACRO SECTOR FLOWS

• Macro risk analysis - probabilities and potential spread impacts

• Commodity forecasts

• Expected default rate and credit migration losses

• Credit ratings upgrade/downgrade ratio forecast

• New issue use of proceeds

• New issue ratings distribution

• Bank lending conditions

• Covenant quality

• Proprietary credit risk premium models

• Sector horizon return and spread target scenarios

• Spread per unit of duration by region

• Spread ratios between rating cohorts

• Spread per unit of leverage

• Valuation analysis by stage of credit cycle

• Cross-currency spread valuation analysis

• Pension demand

• Foreign holdings and flows

• ETF and mutual fund flows

• M&A pipeline

• Coupons and maturities

• Bond supply/demand expectations

• Hedge costs/gains between regions

• Loan and LBO volumes

INDUSTRY INDUSTRY/SECTOR POSITIONING

• Credit and leverage cycle by industry

• Regulatory dynamics

• M&A activity

• Debt growth trends by industry

• Industry-wide anticipated direction of margins, free cash flow, and leverage

• Proprietary Unified Relative Value tool

• Historical spread changes, returns, and Z-scores

• Cross-currency spread valuation by issuer

• Spread curve analysis

• Spread relationships to sovereign

• Capital structure analysis

• Investor survey monitors

• Dealer inventories

• Systematic leverage

ISSUER DERIVATIVES MOMENTUM

• Leverage, change in leverage and components

• Revenue, profit growth, margin trends, coverage

• Free cash flow trends and uses of cash

• Capital expenditures, financing gap

• Share buybacks and dividends

• Crossover analysis - rising stars vs. fallen angels

• CDS and equity changes

• CDX and ITRX indices and basis moves

• ETF premium/discount

• Implied vols

• Trading liquidity

• New issue concessions and break performance

Portfolio Credit Beta Management via Targeted Industry Allocation

Our investment team monitors and targets portfolio credit beta at the overall level versus the benchmark, but it is primarily the aggregation of contribution to beta from industry and issuer positioning.

Our rigorous, repeatable sector and product team process of systematically focusing on the relevant fundamental, valuation, and technical indicators (see below) impacting global credit markets helps provide the basis of our portfolio construction.


Deeper Perspective Gained During CollaborationWe gain a deeper perspective through the collaboration of portfolio managers, strategists, research analysts and traders. Each sector team brings together these professionals to focus on a particular portion of the fixed income market as seen in the next exhibit. Each team integrates the macro views with team member insights to assess their respective market sector’s risk/return characteristics and seeks to uncover specific industries and credits that may offer the best return potential.

TOP-DOWN AND BOTTOM-UP FRAMEWORK

MACRO-ORIENTED TEAMS MARKET SECTOR TEAMS

• Global Asset Allocation

• US Yield Curve

• Developed Non-US Markets

• Bank Loans

• Commodities

• Convertibles

• Emerging Markets

• Equity

• Global Credit

• High Yield

• Investment Grade Corporate

• Municipals

• Mortgage & Structured Finance

• US Government

Our Global Fixed Income Team of three portfolio managers, two global credit strategists, one currency/rates strategist and two product managers review and debate recommendations from all of the various Sector Teams when constructing portfolios. The Global Fixed Income Team has ultimate decision-making authority over portfolio construction with a desire to build diversified portfolios with the most favorable risk/reward proposition.

While our research process is rigorous and repeatable, it does not provide a specific quantitative output detailing the optimal contribution to beta at the industry or overall level. Therefore to construct information-ratio-efficient portfolios, product team insights and experience, as well as strict parameters around contribution-to-beta exposures are instrumental.

At the portfolio level, relative overall credit beta positioning ranges from 0.8 times benchmark credit risk when we determine adequate spread premium is unavailable, to upwards of two times benchmark credit risk when product/sector teams indicate valuations are significantly overcompensating for underlying fundamental risk. From an industry perspective, our maximum relative contribution to beta is 15%. This calculation is essentially a “modified duration multiplied by spread (DTS)” methodology, which allows us to size positions on a risk-adjusted basis that reflects our conviction level.

RESEARCH ANALYSTS TRADERS

PORTFOLIO MANAGERS & STRATEGISTS

SECTOR TEAMS


Source: Bloomberg Barclays, Loomis Sayles analysis, as of 10/31/2017.

Performance is shown for a representative account as supplemental information.

Due to system limitations, it is difficult to analyze this data on a composite basis. This representative account was selected because it closely reflects the Loomis Sayles Global Credit investment strategy. Due to guideline restrictions and other factors, there is some dispersion between the returns of this account and other accounts managed in the Global Credit investment style.

RELATIVE CONTRIBUTION TO BETA BY INDUSTRYRepresentative Global Credit Account

Portfolio Construction and LimitsWe adhere to strict, self-imposed limits with regard to our overall industry and issuer contribution-to-beta positioning versus the benchmark. These guidelines are in place as a risk-management tool to ensure an adequately diversified portfolio, as well as to provide a concise assessment of the potential basis point impact to the portfolio’s excess return from any given position. These positions are monitored in real time via proprietary software and account-specific Risk Awareness Packages (RAPs).

9.09%

-7.72%

5.08% 4.94% 4.67%4.11%

-4.01%

3.84%2.77% 2.55% 2.44% 2.25% 2.23%

-2.19%

1.98%

-10.00%

-8.00%

-6.00%

-4.00%

-2.00%

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%-0

.76%

Ban

king

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8% S

over

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fe

1.90

% M

edia

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ent

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% Ca

ble

Sate

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depe

nden

t

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pay

Gua

rant

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% M

idst

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1.11

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0.72

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1.40

% Tr

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tion

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vice

s

0.12

% O

il Fi

eld

Serv

ices

1.29

% Re

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ocal

Aut

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0.55

% H

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Relative Market Weight

Rela

tive

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Bet

a

Decision Making and Shifting Portfolio ExposuresWe dynamically shift industry beta exposures over time. In our experience, certain industries matter more at different times and attempting to capture excess risk premium from critical industries is crucial to alpha generation. Consider technology and telecom in the late 1990s to early 2000s, banking in 2008 to 2009 and during the past couple of years, as well as the commodity sectors during 2015 to 2017. We believe positioning in these sectors during these periods was essential for outperformance, and heavily dependent upon our top-down and bottom-up macro and credit research.


The graph below highlights our beta management from October 2006 to October 2017 (the benchmark beta of 1.0 is the 0 line). Key points include:

1. Overall contribution to beta fluctuated from 1.9 times the credit risk of the benchmark in 2009 to 0.8 times in 2014,

2. The banking and insurance exposure pre-GFC was quite low, but has been elevated from 2015 onward, and,

3. Energy exposure ramped up during 2015, declined during 2016, and then increased again in 2017.

Source: Bloomberg Barclays and Loomis Sayles analysis, as of 10/31/2017. Performance is shown for a representative account as supplemental information. Due to system limitations, it is difficult to analyze this data on a composite basis. This representative account was selected because it closely reflects the Loomis Sayles Global Credit investment strategy. Due to guideline restrictions and other factors, there is some dispersion between the returns of this account and other accounts managed in the Global Credit investment style.

RELATIVE CONTRIBUTION TO BETA BY INDUSTRYRepresentative Account

Communications

Energy

Insurance

Banking

Technology

Consumer Cyclical

Capital Goods

Total Relative Credit Beta

Bloomberg Barclays Global Agg Corp. OAS

0

100

200

300

400

500

600

-0.40

-0.20

0.00

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0.60

0.80

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1/20

062/

28/2

007

6/30

/200

710

/31/

2007

2/29

/200

86/

30/2

008

10/3

1/20

082/

28/2

009

6/30

/200

910

/31/

2009

2/28

/201

06/

30/2

010

10/3

1/20

102/

28/2

011

6/30

/201

110

/31/

2011

2/29

/201

26/

30/2

012

10/3

1/20

122/

28/2

013

6/30

/201

310

/31/

2013

2/28

/201

46/

30/2

014

10/3

1/20

142/

28/2

015

6/30

/201

510

/31/

2015

2/29

/201

66/

30/2

016

10/3

1/20

162/

28/2

017

6/30

/201

710

/31/

2017

Bloomberg Barclays G

lobal Agg Corp OAS

Rela

tive

Bet

a

Fluctuations in relative exposure at the industry, and therefore overall level, have been quite dramatic and significant drivers of performance in our view. For example, positioning in financials, led by banking and insurance has been quite additive over the past five years. Our favorable view of the banking and insurance companies was more of a top-down industry decision. We believed spreads were overcompensating for underlying credit rating migration and default risk—most likely owing to investor perceptions following the financial crisis. Of course our comfort with the sector, as well as our issue selection within each industry, resulted from the bottom-up credit analysis by our centralized research analysts, sector teams, and global credit strategists. In contrast, the contribution to return from communications was largely from bottom-up security selection opportunities versus an industry choice.

Accordingly, our historical excess returns have been generated through both top-down portfolio and industry beta positioning and the identification of the best risk-adjusted security selection ideas. While this decomposition varies over time depending upon the opportunity set and market volatility, it has been our experience that unstable, down markets highlight our security selection, while low-volatility, highly correlated markets inherently reward overall and industry beta positioning more heavily.


Idiosyncratic Security Selection and Disciplined Position SizingA concentrated focus on relative value at the issuer and issue level in partnership with Loomis Sayles’ fundamental and quantitative research groups is also a key element of our alpha thesis. The Global Fixed Income Team leverages the full array of research insights originating from these sources and the sector teams to help identify undervalued securities. Our process includes both qualitative and quantitative elements in an effort to accurately assess an issuer’s fundamental fair value. In addition to our deep fundamental credit research effort and our sector team process, our risk premium and Unified Relative Value (URV) quantitative tools and Global Fixed Income Team focus on relative value are instrumental.

We populate portfolios with what we believe are our best ideas and size each based on our level of conviction on a contribution-to-beta basis within strict limits (4% contribution-to-beta maximum). We strive to purchase securities offering the greatest excess return potential over a cycle. Security-specific return is generated from both excess yield, which in our view overcompensates for potential risk, as well as performance in excess of the market and its industry. Corporate bonds, especially investment grade, suffer from a highly asymmetric risk profile. A plethora of academic research based upon Merton’s original work highlights that while higher volatility/spread bonds have resulted in better returns over time, their probability of returns is more negatively skewed (see “The Real World is Not Normal” by Cindy Sin-Yi Tsai, Morningstar Alternative Investment Observer, 3Q11; also “Do the Distributional Characteristics of Corporate Bonds Predict Their Future Returns” by Jennie Bai, Turan Bali, and Quan Wen, Georgetown University, March 2016). As a result, deep fundamental research is required for both downside protection and identifying the potential for spread tightening versus comparable securities.

TIME/YEARS

POSITIVE SKEWESS NEGATIVE SKEWESS

NO SKEWESSCORPORATE BONDS CAN DEMONSTRATE A HIGHLY ASYMMETRIC RISK PROFILE

Source: Assetinsights.net. The chart to the right is shown for illustrative purposes only. Some or all of the information on this chart may be dated, and, therefore, should not be the basis to purchase or sell any securities. The information is not intended to represent any actual portfolio.

Quantitative ToolsAs a firm and product team we have continued to refine and enhance the quantitative tools that support our security selection. Loomis Sayles’ proprietary URV application is a core aspect of our process. It formalizes and standardizes the fundamental and relative value views of our centralized credit research analysts. By plotting the expected credit quality of a company against its interpolated five- and 10-year bond spreads, one can easily visualize opportunities within and across the broader set of industries. A powerful feature of the tool is that it computes an estimate of fair value for each bond in the universe, not just a hypothetical 10-year on-the-run bond. Therefore, the tool is able to offer trade recommendations that can quickly capture dispersions between an analyst’s fundamental credit view or rating and the market’s pricing of that risk, in addition to opportunities along a given issuer’s yield curve.


Truly GlobalAt the heart of our investment process is seeking securities that are theoretically cheap given their underlying credit quality or rating. Other sources of alpha opportunities across the global credit landscape can be uncovered primarily in cross-currency, crossover, and high yield. As a truly global credit manager, we seek to capitalize on cross-currency pricing discrepancies at the issuer and even regional level. Integrated into our sector team process are Loomis Sayles’ trading and research desks in Boston, London and Singapore.

While the major developed credit markets of the US, Europe and the UK are highly correlated over the long run, divergences occur over certain periods for a variety of factors, such as differences in relative growth rates, rate expectations or particular events (2017 French presidential election, ECB corporate sector purchase plan, Brexit, etc.). More importantly, at the issuer level we have found that bond supply and demand dynamics, differences in the buyer base and investor risk tolerance result in recurring cross-currency opportunities. While our regional allocation shifts could at times be a top-down decision, they are more often a function of our issuer cross-currency analysis and the resulting aggregation of our contribution-to-beta positioning in a given market. Of course, we closely monitor deviations from the benchmark at the regional level as this allocation can shift over time depending on the issuer opportunities that arise.

CONTRIBUTION TO BETA BY CURRENCYRepresentative Account

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

Oct

-200

6Fe

b-20

07Ju

n-20

07O

ct-2

007

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2008

Jun-

2008

Oct

-200

8Fe

b-20

09Ju

n-20

09O

ct-2

009

Feb-

2010

Jun-

2010

Oct

-201

0Fe

b-20

11Ju

n-20

11O

ct-2

011

Feb-

2012

Jun-

2012

Oct

-201

2Fe

b-20

13Ju

n-20

13O

ct-2

013

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Jun-

2014

Oct

-201

4Fe

b-20

15Ju

n-20

15O

ct-2

015

Feb-

2016

Jun-

2016

Oct

-201

6Fe

b-20

17Ju

n-20

17O

ct-2

017

Rela

tive

Bet

aEuro

British Pound Sterling

US Dollar

Other Currencies

Source: Bloomberg Barclays, Loomis Sayles analysis, as of 10/31/2017. Performance is shown for a representative account as supplemental information. Due to system limitations, it is difficult to analyze this data on a composite basis. This representative account was selected because it closely reflects the Loomis Sayles Global Credit investment strategy. Due to guideline restrictions and other factors, there is some dispersion between the returns of this account and other accounts managed in the Global Credit investment style.

Tactical Allocation to Off-Benchmark Sectors Can Enhance Risk-Adjusted ReturnsTactical allocation to off-benchmark sectors is a core part of our strategy. This approach has led to enhanced risk-adjusted returns over time. Our top-down and bottom-up sector teams comprehensively assess risks and forecast sector returns on a quarterly basis to aid sector allocation decisions. Our Global Asset Allocation Sector Team (GAAT) chairs meetings quarterly to review sectors with each sector team followed by a meeting with senior decision


HISTORICAL INDEX RETURNS AND INFORMATION RATIOS 12/31/2008 - 3/31/2019

BLOOMBERG BARCLAYS GLOBAL

AGG CREDIT EXCESS RETURN

BLOOMBERG BARCLAYS GLOBAL AGG CORPORATE EXCESS RETURN

BLOOMBERG BARCLAYS GLOBAL AGG SECURITIZED EXCESS RETURN

BLOOMBERG BARCLAYS GLOBAL HIGH YIELD EXCESS

RETURN

BLOOMBERG BARCLAYS EM HARD

CCY AGG EXCESS RETURN

S&P/LSTA LEVERAGED LOAN

INDEX TOTAL RETURN

AVERAGE EXCESS RETURN* (ANNUALIZED) 2.64% 3.03% 1.11% 9.28% 5.73% 8.57%

VOLATILITY (ANNUALIZED) 3.21% 3.70% 1.14% 8.49% 6.77% 5.41%

INFORMATION RATIO 0.82 0.82 0.97 1.09 0.85 1.59

BEST ROLLING 12-MONTH EXCESS RETURN 17.44% 20.73% 5.89% 59.31% 37.59% 51.62%

MAX 12-MONTH DRAWDOWN -3.44% -3.95% -1.28% -6.72% -5.64% -3.54%

CORRELATION TO GLOBAL CORP. INDEX 1.00 -- 0.68 0.90 0.84 0.79

Q1 2019 2.09% 2.38% 0.37% 5.03% 3.11% 4.00%

2018 -2.36% -2.75% -0.57% -4.50% -3.51% 0.44%

2017 3.19% 3.38% 0.76% 6.91% 6.11% 4.12%

2016 3.36% 4.00% 0.02% 13.68% 8.02% 10.16%

2015 -1.04% -1.14% -0.06% -1.96% -0.07% -0.69%

2014 0.46% 0.50% 0.70% -1.11% -1.16% 1.60%

2013 2.65% 3.29% 1.65% 8.38% 0.33% 5.29%

2012 7.07% 7.66% 2.24% 16.24% 14.09% 9.67%

2011 -3.41% -3.83% -1.17% -4.20% -5.14% 1.51%

2010 1.24% 1.48% 1.69% 9.49% 4.38% 10.13%

2009 14.72% 17.30% 5.89% 59.31% 37.59% 51.62%

makers to discuss and debate the results before they are published. Utilizing these views as an input, the Global Fixed Income Team develops sector weightings across the fixed income universe and populates portfolios with high yield, crossover, bank loan, and securitized ideas.

We have dynamically shifted our allocations to high yield, bank loans, and securitized assets over time in order to seek risk premium from these segments, as well as to access attractive security-specific ideas. Further, the crossover space has historically presented opportunities for us given the favorable risk/reward proposition afforded. Academic research supports the theory that the tactical usage of such sectors improves the efficiency of a portfolio in terms of a stronger information ratio. In an October 2015 white paper entitled “Alternative Credit; Credit for the Modern Investor”, Towers Watson argues that the use of such sectors dramatically improves the Sharpe ratio of an investment grade corporate portfolio.

Below, we have compiled data including historical excess return, volatility, information ratio, and drawdown by sector to illuminate further that these off-benchmark sectors have the potential to improve risk-adjusted returns.

*Excess return is a metric used to quantify the duration-neutral return of a security by comparing the total return of a spread security to that of a “risk-free” Treasury asset, represented by a Treasury bond(s).

Source: Bloomberg, Barclays Live, as of 3/31/2019. See disclosure for index definitions.


In the previous table, notable points include the stronger information ratios that securitized, high yield, and bank loans possess over the given time frame, as well as the higher maximum drawdown of high yield. We believe tactical allocation to these sectors in a timely fashion is therefore paramount, as is the downside protection provided by deep fundamental credit research. Our usage of these off-benchmark sectors has fluctuated over time (see next two charts) and historically has resulted in better return per unit of risk than the benchmark, as the second chart attests.

0%

2%

4%

6%

8%

10%

12%

Jan-

2010

Apr-

2010

Jul-

2010

Oct

-201

0

Jan-

2011

Apr-

2011

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2011

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-201

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Apr-

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Jul-

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7

Secu

riti

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Mar

ket

Wei

ght

%

SECURITIZED ALLOCATION: JAN 2010 – OCT 2017Representative Account

CMBS (Agency & Non-Agency)

Covered

ABS Other

Car Loan

Credit Card

Home Equity

Whole Business

Agency MBS Pass-Through

Source: Loomis Sayles analysis, as of 10/31/2017. Performance is shown for a representative account as supplemental information. Due to system limitations, it is difficult to analyze this data on a composite basis. This representative account was selected because it closely reflects the Loomis Sayles Global Credit investment strategy. Due to guideline restrictions and other factors, there is some dispersion between the returns of this account and other accounts managed in the Global Credit investment style.

CONTRIBUTION TO BETA BY HIGH YIELD AND IG SECURITIESRepresentative Account

HY ContributionIG ContributionTotal Beta - Credit ER to BGA Credit ER

-0.60

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

Oct

-200

6

Feb-

2007

Jun-

2007

Oct

-200

7

Feb-

2008

Jun-

2008

Oct

-200

8

Feb-

2009

Jun-

2009

Oct

-200

9

Feb-

2010

Jun-

2010

Oct

-201

0

Feb-

2011

Jun-

2011

Oct

-201

1

Feb-

2012

Jun-

2012

Oct

-201

2

Feb-

2013

Jun-

2013

Oct

-201

3

Feb-

2014

Jun-

2014

Oct

-201

4

Feb-

2015

Jun-

2015

Oct

-201

5

Feb-

2016

Jun-

2016

Oct

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6

Feb-

2017

Jun-

2017

Oct

-201

7

Cred

it E

R to

BG

A Cr

edit

ER

-H

isto

rica

l

Source: Loomis Sayles analysis, as of 10/31/2017. ER is shorthand for excess return. Performance is shown for a representative account as supplemental information. Due to system limitations, it is difficult to analyze this data on a composite basis. This representative account was selected because it closely reflects the Loomis Sayles Global Credit investment strategy. Due to guideline restrictions and other factors, there is some dispersion between the returns of this account and other accounts managed in the Global Credit investment style.


Unwanted Risk Exposures Should Be Immunized in a Credit PortfolioThe core of our investment philosophy is predicated on the belief that tactical sector and industry allocation via effective beta management and a concentrated focus on risk-adjusted security-level relative value are integral to alpha generation. As a result, we seek to immunize unwanted risk exposures versus the benchmark. In addition to the aforementioned industry and security-level concentration risks that we address through diversification and strict contribution-to-beta parameters, we believe the chief risks that need to be immunized to the benchmark in a global credit/corporate portfolio are currency and key rate duration exposures. We seek to accomplish this by matching these benchmark exposures via bonds and/or derivatives. We have learned over the years that currency and rate positioning that do not have favorable outcomes can quickly wipe away a year or more of hard work on the allocation and security selection side. Further, both risk factors are less efficient from an information ratio perspective given the inherent volatility of each. Consequently, within our global credit/corporate portfolios, we seek to minimize these risks and aim to generate alpha solely via sector/industry allocation and security selection.

ConclusionIn our view, a rigorous, repeatable process is central to identifying pricing dislocations that often occur in markets. Prices can deviate significantly from underlying fundamental fair value frequently, often exacerbated by an inflated liquidity risk premium. Tactical sector and industry allocation via effective beta management, a consistent evaluation of fundamental value over a credit cycle, and a concentrated focus on risk-adjusted security relative value are integral to capturing this risk premium and potentially generating alpha.

Source: Loomis Sayles analysis, as of 3/31/2019. Benchmark is Bloomberg Barclays Global Aggregate Credit Index.

Performance is shown for a representative account as supplemental information. Due to system limitations, it is difficult to analyze this data on a composite basis. This representative account was selected because it closely reflects the Loomis Sayles Global Credit investment strategy. Due to guideline restrictions and other factors, there is some dispersion between the returns of this account and other accounts managed in the Global Credit investment style.

GLOBAL CREDIT REPRESENTATIVE ACCOUNT AS OF 3/31/2019

PORTFOLIO

RETURN

BENCHMARK

RETURN

EXCESS

RETURN

TRACKING

ERROR

INFORMATION

RATIO

PORTFOLIO

STANDARD

DEVIATION

BENCHMARK

STANDARD

DEVIATION

ONE-YEAR 3.58% 3.29% 0.29% 0.97% 0.30 3.40% 3.03%

THREE-YEAR 3.90% 2.62% 1.28% 0.95% 1.35 3.29% 2.95%

FIVE-YEAR 3.91% 3.29% 0.62% 1.09% 0.57 3.39% 3.00%

TEN-YEAR 7.32% 5.61% 1.71% 1.54% 1.11 4.38% 3.47%


One Financial Center Boston, MA 02111 www.loomissayles.com

Disclosures Diversification does not ensure a profit or guarantee against a loss.

Indices are unmanaged and do not incur fees. It is not possible to invest directly in an index.

Although the investment manager actively seeks to manage risk for a targeted level, there is no guarantee that the portfolio will be able to maintain its targeted risk level.

Performance and characteristics are shown for a representative account as supplemental information. Due to system limitations, it is difficult to analyze this data on a composite basis. This representative account was selected because it closely reflects the Loomis Sayles Global Credit investment strategy. Due to guideline restrictions and other factors, there is some dispersion between the returns of this account and other accounts managed in the Global Credit investment style.

Commodity interest and derivative trading involves substantial risk of loss. This is not an offer of, or a solicitation of an offer for, any investment strategy or product. Any investment that has the possibility for profits also has the possibility of losses.

This article is provided for informational purposes only and should not be construed as investment advice. Any opinions or forecasts contained herein reflect the subjective judgments and assumptions of the authors only and do not necessarily reflect the views of Loomis, Sayles & Company, L.P. Other industry analysts and investment personnel, including those within Loomis Sayles, may have different views and assumptions. Investment recommendations may be inconsistent with these opinions. There can be no assurance that developments will transpire as forecasted and actual results will be different. Data and analysis do not represent the actual or expected future performance of any investment product. We believe the information, including that obtained from outside sources, to be correct, but we cannot guarantee its accuracy. This information is subject to change at any time without notice.

Past performance is no guarantee of future results.

Bloomberg Barclays Global Aggregate Index is an unmanaged index that measures fixed income performance of regions around the world.

Bloomberg Barclays Global Aggregate Credit Index represents the union of the Global Aggregate Index and the Global High-Yield Index and captures investment grade and high yield securities in all eligible currencies and is hedged back to the US dollar.

Bloomberg Barclays Global Aggregate Corporate Index represents the corporates portion of the Bloomberg Barclays Barclays Global Aggregate Index.

Bloomberg Barclays Global Aggregate Securitized Index is the securitized securities portion of the Bloomberg Barclays Barclays Global Aggregate Index

Bloomberg Barclays Global High Yield Index is an unmanaged index that provides a broad-based measure of the global high-yield fixed income markets. It represents that union of the US High-Yield, Pan-European High-Yield, US Emerging Markets High-Yield Indices.

Bloomberg Barclays Global Aggregate Emerging Market Index includes USD, EUR, and GBP denominated debt from sovereign, quasi-sovereign, and corporate EM issuers.

S&P 500/LSTA Leveraged Loan Index is a capitalization-weighted US syndicated loan index.

LS Loomis | Sayles is a trademark of Loomis, Sayles & Company, L.P. registered in the US Patent and Trademark Office.

MALR023300

AUTHORS

SCOTT SERVICE, CFAVP, Portfolio Manager

LYNDA SCHWEITZER, CFAVP, Portfolio Manager

DAVID ROLLEY, CFAVP, Portfolio Manager

Documents

Global Credit Investing at Loomis Sayles Credit... · Tactical allocation to off-benchmark sectors enhances risk-adjusted returns. Top-down and bottom-up sector teams comprehensively