analysing active & passive fund performance _analysing active passiv… · in conclusion, 2019...

Analysing active & passive fund performance

FOR PROFESSIONAL AND QUALIFIED INVESTORS ONLYThis document is for the exclusive use of investors acting on their own account and categorised either as “Eligible Counterparties” or “Professional Clients” within the meaning of Markets in Financial Instruments Directive 2014/65/EU. This document is reserved and must be given in Switzerland exclusively to Qualified Investors as defined by the Swiss Collective Investment Scheme Act of 23 June 2006 (as amended from time to time, CISA).

LYXOR ETF Research

What 2018 results tell us about portfolio construction

Analysing active & passive fund performance

Marlene Hassine KonquiHead of ETF Research

Special acknowledgement to Kristo Durbaku, Lyxor ETF Research, and Nazar Kostyuchyk, Lyxor Quantitative Research for their helpful contributions.

Jean-Baptiste BerthonSenior Cross-Asset Strategist

CONTENT

EXECUTIVE SUMMARY 1

KEY RESULTS 3

An analysis of the performance of active and passive funds 4

Key traditional benchmark results 26

Performance/volatility 28

METHODOLOGY 31

How we compared Active Funds vs their Benchmark 32

Survivorship rate by universe 32

Breakdown of active fund universes by currency 33

APPENDIX 35

Statistical analysis 36

Universe Description 40

Glossary 41

Contributors 44

Disclaimer 45

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Executive summaryEvery year, we take a deep dive into the performance of active funds vs. their benchmarks. This year, we took our research even further by adding again more investment universes. We now cover 32 active investment universes, just under 7,000 funds and EUR1.6trn of asset under management. We cover 28 traditional and 4 alternative active investment universes. All alternative universes are UCITS-compliant long/short equity funds in the US, Europe, UK and emerging markets. Additionally, with the cycle ageing and conditions possibly turning, we’ve taken the opportunity this year to add some analysis on how active managers tend to perform during bull and bear markets.

We’ve gone further than before by showing how the performance results for both traditional and alternative active managers can help in portfolio construction. The combination between traditional, alternative active funds and passive funds is key to generating better returns.

Our research proposes what we think is the strategic neutral allocation between these investment styles. It also allows us to add ranges within which the size of each style allocation could vary - tactical allocation decisions effectively. These decisions will depend more on the expectations of the alpha generation abilities of active managers as a function of market conditions, together with the ability to select the appropriate funds among either traditional or alternative managers.

In conclusion, 2019 promises to be as difficult for active managers as 2018 was. Monetary policy is still on the dovish side, dampening volatility, while economic and political uncertainties linger. Brexit, trade war, slower growth in Europe and China and limited interest rate moves could continue to impede performance. In our view, selecting the right investment vehicle will be all the more important in addition to choosing the right asset allocation to generate returns.

Five things to know from this year’s study

Only 27% of equity managers outperformed

3One of the worst years for active managers in over a decade

1 The right blend of active and passive could have helped portfolios do better

5Fixed income managers did even worse

4Harder than ever to select an outperforming fund

2

10 key takeaways

1. 2018 was a very difficult year for active managers - one of their worst years in over a decade. Political and economic uncertainties, almost universal declines among asset classes and an uncertain trajectory for interest rates all impeded alpha generation.

2. Just 24% of active managers outperformed over the year, well below the 2017 figure of 48% and well below their yearly average over the last decade.

3. Active US growth, European and US small cap managers did best. Active emerging debt, US corporate bond, global bond and French equity managers suffered the most.

4. It was harder than in 2017 - and much harder than usual - to find an outperforming fund in 2018.

5. Only 27% of active equity managers outperformed, down sharply from 2017’s 51% and well below the one-year average of 38% over the last decade. A chaotic market, and a lack of defensive positioning was largely to blame.

6. Fixed income managers fared worse, as just 18% outperformed, down from 41% in 2017.

This was well below the yearly average over the past ten years of 33%.

7. Active funds have shown themselves more likely to outperform during bear markets but sustaining that outperformance into a subsequent bull market is more challenging.

8. Active managers’ returns seem to call the commonly held view that they are more likely to outperform in less efficient markets into question.

9. 2018 was also a weak year for UCITS-compliant long-short equity hedge funds. However, they still did better overall relative to their benchmarks than traditional active funds.

10. When it comes to generating strong, long-term returns, spending time on choosing the right investment tools is just as important as making the right asset allocation choices.

Marlene Hassine KonquiHead of ETF Research

March 2019

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Analysing active & passive fund performance2

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Key results

An analysis of the performance of active and passive funds 4

Key traditional benchmark results 26

Performance/volatility 28

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An analysis of the performance of active and passive funds1. How did active managers perform in 2018?

2018 was a very difficult year for active managers. In fact, it was one of their worst over a decade. High level of political and economic uncertainties, declines for nearly all asset classes and uncertain path for interest rates all weighed on their performances.

24% of active managers outperformed their benchmark over the year, well below the 2017 figure of 48% and below the ten-year yearly average of 36%.

AVERAGE % OF ACTIVE FUNDS OUTPERFORMING THEIR BENCHMARK

1Y10Y*1Y1Y1Y

47%

28%

48%

36%*

24%

2015 2016 2017 2018

Source: Morningstar and Bloomberg data from 31/12/2008 to 28/12/2018. *Yearly average over 10Y.

Standouts were hard to find, but active US equity growth funds was the only universe with results fairly above 50%. European and US small cap managers were the other best performing universes over the year, yet with results only above 40%.

Active emerging debt, US corporate bond, global bond and French equity managers suffered with below 15% of funds of each universe outperforming.

In terms of the dispersion of results, the top 20% of funds outperformed their benchmark by an average of 0.5%, while the bottom 20% underperformed by an average of 4.8%. Overall among all universes, the dispersion of results relative to the long-term average was even smaller than in 2017, which made it harder than usual to find an outperforming fund. With monetary policy still on the dovish side and limited economic volatility, it was difficult for active managers to generate differentiating performances.

DISPERSION OF RETURNS VS THE LONG-TERM AVERAGE AMONG ACTIVE FUND UNIVERSES

2017 avg

2018 avg

2017 avg Equity

2018 avg Equity

2018 avg FI

2017 avg FI

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

-1.5%-2.5%-3.0% -1.0%-2.0% -0.5% 0.0%

% o

f fu

nds

out

pe

rfo

rmin

g t

he b

ench

mar

k

Dispersion of performance spread vs. LT Average

++

--

+

-

Source: Lyxor ETF, Morningstar data from 31/12/2008 to 28/12/2018. Averages are calculated based on the 28 universes so it may differ from last year published data, due to perimeter changes. See page 6 how to read the graph.

2018 was a very difficult year for active managers - one of their worst in over a decade. Political and economic uncertainties, almost universal declines among asset classes and an uncertain trajectory for interest rates all impeded alpha generation.

Just 24% of active managers outperformed over the year, well below the 2017 figure of 48% and well below their yearly average over the last decade.

Active US growth, European and US small cap managers did best. Active emerging debt, US corporate bond, global bond and French equity managers suffered the most.

It was harder than in 2017 - and much harder than usual - to find an outperforming fund in 2018.

THE FIGURES RELATING TO PAST PERFORMANCES REFER TO PAST PERIODS AND ARE NOT A RELIABLE INDICATOR FOR FUTURE RESULTS. THIS ALSO APPLIES TO HISTORICAL MARKET DATA.

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2. How did active equity funds perform?

2018 was a bad year for active equity managers, with only 27% of them outperforming, sharply down from 51% in 2017. This figure is also well below the one-year average of 36% over the past ten years.

The best results were achieved by active US growth, European and US small cap equity managers.

Only US growth managers succeeded in doing significantly better than their yearly average over the past

ten years. In fact, 75% outperformed - well above the average of 41% over the past ten years.

Active European and US small cap managers did slightly better than their long-term averages, while Spanish and Japanese equity managers’ results were broadly in line. As the graph below shows, Italian and European value equity managers posted the worst results.

Overall, three quarters of the 19 equity universes we cover posted well below average results.

% OF ACTIVE FUNDS OUTPERFORMING THEIR BENCHMARK IN 2018 RELATIVE TO THE LONG-TERM AVERAGE

60%

80%

70%

50%

40%

30%

20%

10%

0%

10%0% 20% 30% 40% 50% 60%

US Equity Growth

Europe Equity GrowthItaly

Large Caps

US Large Caps

World Large CapsSwitzerland Large Caps

UK All Caps

Eurozone Large CapsEurope Large Caps

Emerging markets

Large Caps

Germany Large CapsFrance

Large Caps

Europe Equity Value

US Equity Value

JapanAll Caps

Europe Small Caps

US Small Caps

Spain Large Caps

China Large Caps

70% 80%

2018 results below LT avg

2018 results above LT avg

% o

f act

ive

fund

s ou

tper

form

ing

thei

r be

nchm

ark

on a

yea

rly

aver

age

over

10y

% of active funds outperforming their benchmark in 2018

Source: Lyxor ETF, Morningstar data from 31/12/2008 to 28/12/2018.

Only 27% of active equity managers outperformed, down sharply from 2017’s 51% and well below the one-year average of 36% over the last decade. A chaotic market, and a lack of defensive positioning was largely to blame.

3. How easy was it to pick an equity fund that outperformed?

To answer this question, we must look at the dispersion of active equity funds’ returns against their benchmark in 2018 and compare it to the long-term average for each category. This dispersion of returns gives us an indication of how outperformance is spread around the benchmark. Coupling this information with the percentage of outperformers allows us to work out the probability of picking an outperformer.

In 2017, 51% of equity funds outperformed, but the dispersion of results was lower than in previous years. Alpha generation was limited to a select few funds so

finding an outperformer was hard work. In 2018, that job became harder still, with the dispersion of results similar but the percentage of outperforming falling fairly sharply.

The dispersion in the US growth equity universe was close to average and a high percentage of active funds outperformed their benchmark. This meant the probability of selecting a fund that outperformed was high. In contrast, the dispersion in the European growth equity universe was low and a limited percentage of funds outperformed, so the probability of investing in an outperforming fund was low.


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DISPERSION OF RETURNS VS LONG TERM AVERAGE AMONG ACTIVE EQUITY FUND UNIVERSES

-3.5% -2.5% -1.0%-1.5%-2.0%-3.0% -0.5% 0.0% 0.5% 1.0% 1.5%

60%

80%

70%

50%

40%

30%

20%

10%

0%

% o

f fu

nds

out

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ing

the

ben

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Dispersion of outperformance vs LT Average

Switzerland

Eurozone

France

UK

US Large Caps

Germany

Europe Large Caps

Spain

World

China

Japan

Europe Small Caps

Emerging Markets

US Small Caps

Europe Growth

Europe Value

US Growth

Average Equity 2018

AverageEquity 2017

US Value

++

--

+

-

Source: Lyxor ETF, Morningstar data from 31/12/2008 to 28/12/2018. Averages are calculated based on the 28 universes so it may differ from last year published data, due to perimeter changes.

How to read the graph

The dispersion of the outperformance of active managers relative to their benchmark is measured as the standard deviation of outperformance minus the long-term average of the standard deviations for each universe.

Analysing the results:

A high percentage of outperformers and a low dispersion of returns means the probability of selecting an outperforming fund is high (it’s a favourable environment for active managers).

A high percentage of outperformers and a high dispersion of returns means active managers have generated some alpha but the probability of selecting an outperforming fund is lower (it’s a good, albeit slightly less favourable, environment).

A universe with a low percentage of outperformers and a high dispersion of returns means it’s been difficult to generate alpha but the probability of picking an outperformer is still significant.

A universe with a low percentage of outperformers and a low dispersion of returns means it’s been difficult to generate some alpha and that the probability of selecting an outperformer is low.

In 2018, that job became harder still, with the dispersion of results similar than in 2017 but the percentage of outperforming falling fairly sharply. So it was harder to find an outperforming active equity manager.

4. Why did active equity managers struggle in 2018?

Poor market returns

Nearly all equity regions fell over the year, with the US down 5%, Europe 11% and emerging markets 15%. After positive first three quarters, the strong trend reversal in Q4 and the instability of the correlations between markets weighed on active managers’ returns.

EQUITY MARKET RETURNS IN 2018

-16%

-14%

-12%

-10%

-8%

-6%

-4%

-4.9%

-10.6%

-8.7%

-14.6%

-12.0%

-6.7%

-2%

0%

S&P 500(in $)

MSCI Europe(in €)

MSCI World (in $)

MSCI EM (in $)

MSCI Pacific

(in $)

Hedge Fund Research

(in $)

Source: Bloomberg, Lyxor ETF data from 30/12/2017 to 28/12/2018. HFR index data.

More volatility

Greater volatility, more volatile earnings revisions and a less favourable macroeconomic backdrop made the job of active managers more difficult. Overall, G3 implied volatility increased from 15% to 25% over the year, while our Global EPS revision index hit a record high.

VOLATILITY VS. EQUITY DIRECTIONALITY

Source: Macro Bond, Lyxor AM.


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Increasing stock dispersion, unstable correlations

Overall, the dispersion of the returns of individual stocks increased throughout the year from a very low level. Meanwhile, the correlations between returns fell sharply post February, making it very difficult for active managers to find independent and diversified drivers.

DISPERSION OF STOCK RETURNS IN THE US, EUROPE AND JAPAN

SP500 (as of 1/19)SP500 (as of 1/19)

Source: Macro Bond and Lyxor AM data from 01/01/2005 to 31/01/2019.

CORRELATION OF STOCK RETURNS IN THE US, EUROPE AND JAPAN

SP500 (as of 1/19)SP500 (as of 1/19)

Source: Macro Bond and Lyxor AM data from 01/01/2005 to 31/01/2019.

An additional difficulty in 2018 for some active managers was that investors did not respond rationally to fundamentals last year. If they are to succeed, active managers need stock prices to respond to the fundamentals that they picked them for. But as the graph at the top right comparing the volatility of stocks with the volatility of macro indicators shows, the market went through periods of under-reaction and over-reaction to fundamentals last year, making it very hard for active managers to do their jobs successfully. What’s more, the proportion of returns that can be explained by company specifics after EPS announcements fell to new lows.

FUNDAMENTAL RATIONALITY

Source: Macro Bond, Lyxor AM.

SHARE OF RETURNS POST EPS ANNOUNCEMENT EXPLAINED BY: MARKET, SECTOR, COMPANY SPECIFICS

0%

20%

40%

60%

80%

100%

01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18

Market Sector Company specifics

Source: Macro Bond, Lyxor AM. Market, Sector, Company-specifics (top 100 of S&P500).


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5. What were active equity managers’ style biases over 2018?

Our risk factor analysis model helps us highlight active managers’ main style biases.

Analysis by universe

In Japan, the low beta factor was the big winner over the year, outperforming the benchmark by 7.9%. With an uncertain economic and political outlook, a cautious approach was the best option but active

managers, on average, chose to take a bit more risk. Momentum was the worst performer, 3.3% behind the benchmark. This all weighed on returns as market reversals and economic uncertainties dominated the year. Just 34% outperformed over the year, well below the 47% that did so in 2017, but in line with the yearly average over the past 10 years. Overall, active Japanese equity managers appear to have been too optimistic about the state of the country’s economy in 2018.

JAPAN ACTIVE FUNDS OVER/UNDER RISK FACTOR WEIGHTS JAPAN RISK FACTOR OUT/UNDER PERFORMANCE VS. BENCHMARK

5%5%9%

8%4%

12%

3%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40% Best vs. all funds Worst vs. all funds

-29%

-18%

Market Small Value Momentum Low Beta Quality

1%2%

8%

1%

-4%

-2%

0%

2%

4%

6%

8%

10% 2018

Small Value Momentum Low Beta Quality

-3%

Low beta, Quality + Momentum --Value -- Low beta ++

Sources: Morningstar and Bloomberg data from 30/12/2017 to 28/12/2018. Top and worst active funds of the universe weighted average results (first and last decile in terms of performance) using the following five Risk Factors from J.P. Morgan Equity Risk and MSCI: MSCI Japan SMALL CAPS INDEX, J.P. Morgan Equity Risk Premia – Japan MOMENTUM FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – Japan LOW BETA FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – Japan VALUE FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – Japan QUALITY FACTOR Long Only Index. The results of the regression gives very statistically significant results with most of the R2 being above 85%.

In Europe, low-beta and quality stocks performed best and outperformed their benchmarks by 4 and 2% respectively. On average, active managers were overweight the quality and low-beta factors, but this was not enough to offset the negative alpha that they generated – -1.5% against a long-term average of -0.5% – due to the market’s lack of rationality. Active European equity managers underperformed their benchmark by an average of 1.2% in 2018. Just 29%

of them outperformed their benchmark over the year, well below both the 49% that did so in 2017 and the ten-year yearly average of 41%. The active managers who performed best last year were overweight in low-beta stocks, while the worst were overweight value stocks. Those betting on economic recovery got it wrong. Overall, active European equity managers also seem to have been too optimistic about the state of the European economy in 2018.

EUROPE ACTIVE FUNDS OVER/UNDER RISK FACTOR WEIGHTS EUROPE RISK FACTOR OUT/UNDER PERFORMANCE VS. BENCHMARK

-15%-10%

2%

11%2%

2%

4%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20% Best vs. all funds


4%2%

-12%

-10%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

-4%

-9%

-3%


Worst vs. all funds

Low beta ++ Low beta, Quality ++

Sources: Morningstar and Bloomberg data from 30/12/2017 to 28/12/2018 Top and worst active funds of the universe weighted average results (first and last decile in terms of performance) using the following five Risk Factors from J.P. Morgan Equity Risk and MSCI: MSCI EUROPE SMALL CAPS INDEX, J.P. Morgan Equity Risk Premia – EUROPE MOMENTUM FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – EUROPE LOW BETA FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – EUROPE VALUE FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – EUROPE QUALITY FACTOR Long Only Index. The results of the regression gives very statistically significant results with most of the R2 being above 85%.


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In the US, all factors underperformed apart from low beta, which was in line with a market that was driven mainly by the tech sector. Low beta was the main style bias over the year, but overall active managers were also slightly overweight value, which underperformed by a massive 15% and weighed significantly on their performance. This may explain the low percentage of active US equity managers that outperformed over the year: just 20%,

below both the 33% who did so in 2017 and the yearly average of 25% over the past ten years. The managers who did best were those who were overweight low beta stocks and had very limited exposure to value. The worst were those who took strong bets on economic recovery by overweighting value and size. Overall, active managers’ convictions were not rewarded over the year as no one risk factor outperformed the broad market.

US ACTIVE FUNDS OVER/UNDER RISK FACTOR WEIGHTS US RISK FACTOR OUT/UNDER PERFORMANCE VS. BENCHMARK

-16%

-14%

-12%

-10%

-8%

-6%

-4%

-2%

0%

2%

-3%

-15%

-4% -4%


-68%-46%

16%6%

67% 20%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80% Best vs. all funds


Worst vs. all funds

Low beta Value, Momentum, Small, Quality --

Sources: Morningstar and Bloomberg data from 30/12/2017 to 28/12/2018. Top and worst active funds of the universe weighted average results (first and last decile in terms of performance) using the following five Risk Factors from J.P. Morgan Equity Risk and MSCI: MSCI US SMALL CAPS INDEX, J.P. Morgan Equity Risk Premia – US MOMENTUM FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – US LOW BETA FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – US VALUE FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – US QUALITY FACTOR Long Only Index. The results of the regression gives very statistically significant results with most of the R2 being above 85%.

In emerging markets, however, all factors apart from momentum outperformed the broad market. Active managers did not take any significant bet against the benchmark over the year however, and their lack of conviction was illustrated by a limited bias toward small caps, value and quality. This was not enough to compensate for their general market exposure. Just

21% of active emerging equity managers outperformed over the year, that’s half the number that did so in 2017. It is also well below the ten-year yearly average of 37%. Overall, emerging equity managers failed to protect themselves when the market was falling or to capture the trend reversal toward value that started in Q4.

EMERGING MARKETS ACTIVE FUNDS OVER/UNDER EMERGING MARKETS RISK FACTOR OUT/UNDER PERFORMANCE RISK FACTOR WEIGHTS VS. BENCHMARK

2% 2%

5%

6%

2%

2%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20% Best vs. all funds Worst vs. all funds


-15%

-6%

4%

3%

2%

1%

0%

1%

2%

3%

4%

5%

6%

7%


2018

1%

4%

-3%

6%

3%

Low beta, Quality + Value, Low beta, Quality ++ Momentum --

Sources: Morningstar and Bloomberg data from 30/12/2017 to 28/12/2018. Top and worst active funds of the universe weighted average results (first and last decile in terms of performance) using the following five Risk Factors from J.P. Morgan Equity Risk and MSCI: MSCI EM SMALL CAPS INDEX, J.P. Morgan Equity Risk Premia – EM MOMENTUM FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – EM LOW BETA FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – EM VALUE FACTOR Long Only Index, J.P. Morgan Equity Risk Premia – EM QUALITY FACTOR Long Only Index. The results of the regression gives very statistically significant results with most of the R2 being above 85%.

Factor returns were mixed across regions in 2018, reflecting the fact that different regions were at different phases of the economic cycle. However, we can see that overall, active managers suffered from their lack of defensive positioning in what was a difficult and at times chaotic environment for investing.


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6. Did active equity managers take on more risk in 2018?

By calculating the percentage of funds that outperformed their benchmarks’ Sharpe ratios, we can understand the risk or volatility taken on by active managers over the year.

The percentage of funds outperforming their benchmarks’ Sharpe ratio on an absolute basis was 2% higher than the percentage that outperformed on a risk-adjusted basis. The results suggest active equity managers took on less risk than the benchmark over the year and, perhaps unsurprisingly, obtained lower returns. The average volatility of the equity universes of active funds was 13.2% vs. an average for the benchmarks of 15.4%.

In Japan, just 19% of active managers achieved better Sharpe ratios than the market, while 34% outperformed the benchmark in absolute terms. In other words, active managers took on significantly more risk than the benchmark over the year, but this was not rewarded in terms of better risk-adjusted returns. The average volatility of active Japanese equity funds over the year was 17.1%, compared with 14.7% for the broad markets. However, these funds underperformed the index by an average of 1.6% over the year.

In the US, Europe and emerging markets, risk-adjusted results relative to the benchmark were very close to absolute returns. This shows that in these regions, active managers did not on average take on more risk than the market.

% OF ACTIVE EQUITY MANAGERS OUTPERFORMING THEIR BENCHMARK ON AN ABSOLUTE AND RISK-ADJUSTED BASIS IN 2018

0%

5%

10%

15%

20%

25%

30%

35%

40%

29%28%

34%

19%20%

Japanese active equity managers took more risk to generate performance

20%21%

22%

Europe Japan US EM

% of funds which outperformed the benchmark (Equally-Weighted)

% of funds which Sharpe outperformed the benchmark (Equally-Weighted)


On average, apart for Japan, active managers in the US, Europe and Emerging markets did not take on more risk than the market.

7. Did higher-conviction managers outperform their benchmark in 2018?

Methodology

Here, we determine the level of active risk taken by active funds relative to their benchmark, which we measure using the funds’ tracking error against their benchmark. A low tracking error generally indicates a fund is closely replicating its benchmark and is one of three signals used by the European Securities and Markets Authority (ESMA) in its study on potential closet index-tracking funds. We calculate the percentage of funds outperforming their benchmark in a universe according to which tracking error level the funds fell into in 2018.

Using TE levels of 3%, 6%, 9% and above, we classify all the funds within four equity universes: Europe, the US, emerging markets and Japan. We calculate:

1. The percentage of AUM by tracking error

2. The percentage of active funds outperforming by tracking error

3. The level of fees by tracking error.

Results

Our main finding was that 80% of the assets in our universes had a tracking error below 6% in 2018. In the US, this rose to 96%, while it was 60% in Japan. The majority of assets – 52% – had a tracking error of between 3–6%, while just 9% had a tracking error above 9%. We can conclude from these figures that, apart from in Japan, active managers had little conviction on calls in 2018.

BREAKDOWN OF ASSETS UNDER MANAGEMENT IN FOUR ACTIVE EQUITY UNIVERSES INTO FOUR TRACKING ERROR CATEGORIES

% Europe US EM Japan Average

[0;3] 25.1% 55.5% 25.8% 21.2% 31.9%

[3;6] 64.3% 40.3% 65.8% 38.9% 52.3%

[6;9] 9.5% 3.9% 6.8% 24.3% 11.1%

[9;19] 1.1% 0.3% 1.6% 15.7% 4.7%



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We can also conclude from our study that the higher the tracking error, the higher the likelihood of a fund outperforming in 2018. This holds true for all four universes.

% OF ACTIVE FUNDS OUTPERFORMING THEIR BENCHMARK


[0;3] 19.5% 9.0% 15.7% 19.4% 15.9%

[3;6] 26.6% 17.3% 27.3% 18.8% 22.5%

[6;9] 38.9% 16.7% 30.2% 22.7% 27.1%

[9;19] 42.9% 50.0% 53.8% 28.6% 43.8%


When looking at fees, it’s not always true that funds with higher tracking errors have to involve higher fees, apart from those few funds with a tracking error above 9%. For the other funds, the higher fees on average were generally to be found in the funds with a tracking error of between 3–6% in 2018.

ACTIVE FUNDS’ TOTAL EXPENSE RATIO BROKEN DOWN BY TRACKING ERROR CATEGORIES


[0;3] 0.87 0.64 0.77 0.76 0.76

[3;6] 1.05 0.77 0.93 0.97 0.93

[6;9] 0.81 0.60 0.92 0.88 0.80

[9;19] 1.14 0.76 1.52 0.82 1.06


The greater a manager’s level of conviction in 2018, the more likely it was that they would outperform. However, only a limited proportion of managers actually displayed much conviction last year, other than in Japan.

8. How did active fixed income funds perform?

2018 was also difficult for active fixed income managers, with only 18% of them outperforming their benchmark, down from 41% in 2017 and well below the yearly average over the past ten years of 33%.

Active bond managers struggled over the year in nearly all the different fixed income universes. 90% of the nine fixed income universes we cover delivered below long-term average results. Only euro high yield managers’ results were in line with the ten-year average.

% OF ACTIVE BOND FUNDS OUTPERFORMING THEIR BENCHMARK IN 2018 RELATIVE TO THE LONG-TERM AVERAGE

% of active funds outperforming their benchmark in 2018

Euro Govies

Euro Corporate

Euro High Yield

Euro Inflation Linked US Corporate

US High YieldUS Govies

Global bonds-EUR Hdg

Emerging Debt

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

0% 5% 10% 15% 20% 25% 30%% o

f ac

tive

fun

ds

out

per

form

ing

the

ir b

ench

mar

k o

n a

year

ly a

vera

ge

ove

r 10

y

2018 results below LT avg

2018 results above LT avg


Fixed income managers fared worse than their equity counterparts, as just 18% outperformed, down from 41% in 2017. This was well below the yearly average over the past ten years of 33%.


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9. How easy was it to a fixed income fund that outperformed?

Despite 41% of active fixed income funds outperforming in 2017, significantly higher than the 33% yearly average over the previous ten years, the dispersion of results was lower than in previous years and lower than for equity funds, meaning that it was even harder to select an outperforming bond fund. In 2018, despite a lower number of active funds outperforming, the dispersion of their outperformance was greater and closer to the long-term average. Even though alpha generators were limited, the probability of selecting an outperforming fund was slightly higher.

DISPERSION OF RETURNS AMONG ACTIVE BOND UNIVERSES COMPARED TO LONG-TERM AVERAGE

Euro GoviesUS HYEuro HY

Average Fixed income 2017

USGovies

EuroInflation linked

USCorporate

bonds

EuroCorporate

Bonds

Globalbonds

Emergingdebt

Average Fixed income 2018

+

-- -

++

0.0% 0.5%-4.0% -3.5% -3.0% -2.5% -2.0% -1.5% -1.0% -0.5%

30%

40%

45%

50%

55%

35%

25%

20%

15%

10%

5%

0%

% o

f fu

nds

out

per

form

ing

the

ben

hcm

ark

Dispersion of outperformance vs LT Average

Source: Lyxor ETF, Morningstar data from 31/12/2008 to 28/12/2018. Averages are calculated based on the 28 universes so it may differ from last year published data, due to perimeter changes.

10. Did active fixed income managers take on more risk last year?

19% of active fixed income managers outperformed their benchmark in risk-adjusted terms in 2018, while 18% did so in absolute terms. Active managers took on less risk than the benchmark and underperformed: the average volatility of active fixed income managers was 3.9%, compared with 4.5% for the index, while the average fund returned -1.0% over the year but the index rose by 0.2%.

A higher percentage of US government bond, euro high yield and euro corporate bond funds outperformed their

benchmark on a risk-adjusted basis than did so in absolute terms. Some funds within these universes benefited from adopting a less risky exposure than the benchmark. On the contrary, euro inflation-linked and global bond funds did not benefit from taking on additional risk on average, as the percentage of these funds outperforming on a risk-adjusted basis was lower than on an absolute basis.

% OF ACTIVE FIXED INCOME MANAGERS OUTPERFORMING THEIR BENCHMARK ON AN ABSOLUTE AND RISK-ADJUSTED BASIS IN 2018

35%

30%

25%

20%

15%

10%

5%

0%Euro

GoviesEuro

CorporateEuro High

YieldEuro Inflation

LinkedUS

CorporateUS High

YieldUS Govies Global bonds -

EUR HdgEmerging

Debt

% of funds outperforming the benchmark vs. non risk-adjusted benchmark % of funds outperforming the benchmark vs. risk-adjusted benchmark

23%25%

18%

21%23%

27%

19%

13%13%

17%

24% 24%

20%

12%

10%

7% 7%

30%

US Govies funds benefited from a less risky exposure than the benchmark


Active fixed income managers took on less risk than the benchmark and underperformed.


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11. Why did active bond managers perform so poorly in 2018?

Weak market returns

US and eurozone government bond markets both rose by 1% over 2018, but all other fixed income categories fell in value over the year. US corporate bonds lost 2.5% and euro high yield fell by 3.6%.

The reversal of the credit cycle and rangy interest rates evolution were not well anticipated by active managers and weighed on their performances.

FIXED INCOME ASSET CLASSES PERFORMANCES

-2.5%

-1.1% -1.2%

-2.1%

-3.6%

0.9%1.0%

-4%

-3%

-2%

-1%

0%

1%

2%

BB USTreasury

(in $)

BB US Corpo

Treasury (in $)

ICE BofaML

Euro Gov (in €)

ICE BofaMLEuro HY

(in €)

ICE BofaML

Euro Corpo (in €)

BB Global in

Aggregate (in $)

BB US Corpo HY

(in $)

Source: Lyxor ETF, Bloomberg data from 30/12/2017 to 28/12/2018.

Changes in spreads and rates

Having been overweight in credit following many years of outperformance, active global bond managers suffered as credit spreads widened significantly. European and US credit funds suffered for the same reason. The top right chart compares the outperformance of active global bond managers with the performance of the riskier part of the investment grade bond yield curve.

PERFORMANCE OF ACTIVE GLOBAL BOND FUNDS RELATIVE TO BBB-IG CREDIT SPREAD IN 2018

2.0%

2.5%

Dec.2017

Nov.2018

Oct.2018

Sep.2018

Aug.2018

Jul.2018

Jun.2018

May2018

Apr.2018

Mar.2018

Feb.2018

Jan.2018

1.5%

1.0%

0.5%

0.0%

-0.5%

-1.0%

0.7%

0.5%

0.3%

0.1%

-0.1%

-0.3%

-0.5%

-0.7%

-1.5%

-2.0%

-2.5%

Peer Group Global Bonds EUR hedged vs Barclays Global Aggregate Hedged EUR (LHS)

Global Corporate BBB vs Global Corporate Investment Grade Bonds (RHS)

Source: Morningstar data from 30/12/2017 to 28/12/2018. Peer Groups are built equally-weighted in terms of fund composition.

Government bond funds suffered in 2018, as most held a shorter duration than the benchmark as interest rates fell for much of the year (Q3 excluded). Less favourable economic conditions across the world prevented interest rates from rising as monetary policy became less hawkish.

PERFORMANCE OF ACTIVE EURO GOVERNMENT BOND FUNDS RELATIVE TO TEN-YEAR GERMAN YIELD

0.4%

Dec.2017

Nov.2018

Oct.2018

Sep.2018

Aug.2018

Jul.2018

Jun.2018

May2018

Apr.2018

Mar.2018

Feb.2018

Jan.2018

-0.1%

-0.6%

0.9%

0.8%

0.7%

0.6%

0.5%

0.4%

0.3%

0.2%

0.1%

0%

-1.1%

-1.6%

Peer Group vs Bench Euro Credit (LH)10Y German Yield (RH)

Source: Morningstar data from 30/12/2017 to 28/12/2018. Peer Groups are built equally-weighted in terms of fund composition.


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12. How do active fund managers perform when the cycle turns?

Over the past ten years, we’ve witnessed a very long bull market in nearly all equity markets. Fixed income markets have been rising for even longer. Now that this phase looks to be over, we consider one of the main questions investors are now asking: how will my active manager perform in a bear market?

Methodology

We define a bear market as a 20% drop in an index over a period of more than 100 days. We analyse the European and US equity markets from January 1st 2007 and identify three suitable periods. Bear market conditions are rarer within fixed income, so we only look at the euro high yield universe. We analyse the following factors:

1. The percentage of active managers outperforming during the bear market periods.

2. The percentage of funds that went on to outperform their benchmark in the bull markets which immediately followed the bear markets and did so for a time equal to that of the bear market.

3. The percentage of funds which consistently outperform in bull markets immediately following bear markets.

Results

1. Active fund returns can be better during bear markets

On average, 49% of active funds outperformed during the three bear markets in the three universes we look at. This is above the average of 33% of funds that outperformed on a yearly basis over the past 10 years in those three universes.

% OF FUNDS OUTPERFORMING THEIR BENCHMARK DURING BEAR MARKETS

90%

44%

28%

49% 50%

77%

46%

80%

70%

60%

50%

40%

30%

20%

US Equity Europe Equity

Average 49%

Euro High Yield

10%

0%

Bear market 1 Bear market 2 Bear market 3

Source: Lyxor ETF, Morningstar data from 01/01/2007 to 28/12/2018. In the US, bear markets 1 and 2 extend respectively from 15/06/2007 to 09/03/2009 and from 14/02/2011 to 19/08/2011. In Europe, bear markets 1,2 and 3 extend respectively from 16/07/2007 to 09/03/2009, from 17/02/2011 to 22/09/2011 and from 15/04/2015 to 11/02/2016. For the Euro High Yield universe, bear market 1 extends from 04/06/2007 to 15/12/2008.

2. Performance during subsequent bull markets

On average, 21% of active funds outperformed during the bull markets which immediately followed the bear markets.

% OF FUNDS OUTPERFORMING THEIR BENCHMARK DURING SUBSEQUENT BULL MARKETS

45%

18% 18%19%

41%

15%12%

40%

35%

30%

25%

20%

15%

10%

US Equity Europe Equity Euro High Yield

5%

0%

Bull Post Bear 1 Bull Post Bear 2 Bull Post Bear 3

Average 21%

Source: Lyxor ETF, Morningstar data from 01/01/2007 to 28/12/2018. In the US, bull periods following bear markets 1 and 2 extend respectively from 09/03/2009 to 02/12/2010 and from 19/08/2011 to 21/02/2012. In Europe, bull periods following bear markets 1,2 and 3 extend respectively from 09/03/2009 to 02/11/2010, from 22/09/2011 to 26/04/2012 and from 11/02/2016 to 09/12/2016. For the Euro High Yield universe, bull period following bear market 1 extends from 15/12/2008 to 28/06/2010.

3. Consistency of outperformance between bear and bull markets

We find that only 8% of the managers that outperformed during the bear market continue to outperform over the whole period.

% OF FUNDS OUTPERFORMING THEIR BENCHMARK DURING THE BULL MARKET AFTER OUTPERFORMING DURING A BEAR MARKET

35%

5%

2%

10%

23%

11%

0%

30%

25%

20%

15%

10%

5%

0%US Equity Europe Equity

Average 8%

Euro High Yield

Bear + Bull Post Bear 1 Bear + Bull Post Bear 2 Bear + Bull Post Bear 3

Source: Lyxor ETF, Morningstar data from 01/01/2007 to 28/12/2018. In the US, bear market and following bull period 1 and 2 extend respectively from 15/06/2007 to 02/12/2010 and from 14/02/2011 to 21/02/2012. In Europe, bear market and following bull period 1, 2 and 3 extend respectively from 16/07/2007 to 02/11/2010, from 17/02/2011 to 26/04/2012 and from 15/04/2015 to 09/12/2016. For the Euro High Yield universe, bear market and following bull period 1 extends from 04/06/2007 to 28/06/2010.


Active funds seem to have done better in bear markets than they have done generally over the last decade or so. There is however little consistency in their results – and therefore little guarantee that those managers who have outperformed during bear markets will continue to do so in bull markets.

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13. How did active managers perform against smart beta benchmarks?

Multifactor smart beta indices posted rather weak returns in 2018. In Europe and Japan, smart beta indices (represented in this case by the MSCI Diversified Multi Factor indices) performed nearly in line with traditional market cap indices. However, US and emerging market smart beta indices underperformed the market cap indices.

In the US, all factors underperformed the traditional benchmark, resulting in the US multifactor index underperforming it by 5.5%. Over the year, 81% of active managers succeeded in outperforming their smart beta benchmark on a risk-adjusted basis, compared with just 20% for the traditional benchmark. However, over the past 10 years, the smart beta benchmark has outperformed the traditional benchmark by 1.1% on an annualised basis. In that period, only 3% of active funds have outperformed their smart beta benchmark on a risk-adjusted basis, while 7% have outperformed on an absolute basis. So, while 2018 was a less positive year for smart beta indices, it has been much harder for active managers to outperform smart beta indices over the long term.

In Europe, the multifactor index was boosted by strong performance from the low-beta and quality factors, but the European multifactor index still underperformed the traditional benchmark by 20 basis points over the year. 21% of active managers outperformed their smart beta benchmark on a risk-adjusted basis over the year, compared with 28% for the traditional benchmark. Over the long run, the smart beta benchmark has outperformed the traditional benchmark by 3.5% on an annualised basis. Just 9% of active funds have outperformed their smart beta benchmark on a risk-adjusted basis over the last decade, compared with 37% for the traditional benchmark.

Active European equity managers continue to find it hard to outperform smart beta benchmarks.

In Japan, the multifactor index was boosted by strong performance from the low beta, quality and value factors, but it still underperformed the traditional benchmark by 30 basis points over the year. 13% of active managers outperformed their smart beta benchmark on a risk-adjusted basis over the year compared with 19% for the traditional benchmark. Over the long run, the smart beta benchmark has outperformed the traditional benchmark by 3.2% on an annualised basis. Only 10% of active funds have outperformed their smart beta benchmark on a risk-adjusted basis over the last decade, compared with 25% for the traditional benchmark. In Japan, it was difficult for active managers to outperform their smart beta benchmark over 2018 and over the ten years to the end of last year.

In emerging markets the multifactor index suffered badly in 2018, underperforming the traditional benchmark by 5%. 66% of active managers outperformed their smart beta benchmark on a risk-adjusted basis over the year, compared with 22% for the traditional benchmark. Over the long run, however, the smart beta benchmark has outperformed the traditional benchmark by 2.5% on an annualised basis. Over the past ten years, only 5% of active funds have outperformed their smart beta benchmark on a risk-adjusted basis, compared with 27% for traditional benchmarks. So, while 2018 was a bad year for smart beta in the emerging markets, long-term results show it has still been difficult for active managers to outperform their smart beta benchmark.

MSCI EUROPE MSCI EUROPE DIVERSIFIED MULTI-FACTOR

UNDERPERFORMING FUNDS OVER THE PERIOD

OUTPERFORMING FUNDS OVER THE PERIOD















21%9%

20%

19%

22%

7%

1Y10Y

1Y10Y

1Y10Y

1Y

1Y10Y

1Y10Y

81%

13%10%

28%

37%

24%

1Y10Y

1Y10Y

66%

5%

27%

10Y

3%

MSCI USA MSCI USA DIVERSIFIED MULTI-FACTOR

















21%9%

20%

19%

22%

7%

1Y10Y

1Y10Y

1Y10Y

1Y

1Y10Y

1Y10Y

81%

13%10%

28%

37%

24%

1Y10Y

1Y10Y

66%

5%

27%

10Y

3%

















21%9%

20%

19%

22%

7%

1Y10Y

1Y10Y

1Y10Y

1Y

1Y10Y

1Y10Y

81%

13%10%

28%

37%

24%

1Y10Y

1Y10Y

66%

5%

27%

10Y

3%

Source: Lyxor ETF, Bloomberg, MSCI. Data from 31/12/2008 to 28/12/2018.


PERCENTAGE OF ACTIVE FUNDS OUTPERFORMING RISK-ADJUSTED AND SMART BETA BENCHMARKS

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TOPIX J.P. MORGAN JAPAN MULTI-FACTOR

















21%9%

20%

19%

22%

7%

1Y10Y

1Y10Y

1Y10Y

1Y

1Y10Y

1Y10Y

81%

13%10%

28%

37%

24%

1Y10Y

1Y10Y

66%

5%

27%

10Y

3%

MSCI EMERGING MARKETS MSCI EMERGING MARKETS DIVERSIFIED MULTI-FACTOR

















21%9%

20%

19%

22%

7%

1Y10Y

1Y10Y

1Y10Y

1Y

1Y10Y

1Y10Y

81%

13%10%

28%

37%

24%

1Y10Y

1Y10Y

66%

5%

27%

10Y

3%

Sources: Lyxor ETF, Bloomberg, MSCI, JP Morgan. Data from 31/12/2008 to 28/12/2018.

So, while 2018 was a less positive year for smart beta indices, long-term results show that it has still been difficult for active managers to outperform their smart beta benchmark.

14. How did alternatives managers perform against their benchmark in 2018?

Methodology

We analyse the performance of 278 UCITS hedge funds which existed for at least five years, and split them into four equity universes: US, Europe, the UK and the Emerging Markets. Assets under management totaled EUR29.7bn. We used Morningstar data for UCITS long- short equity funds domiciled in Europe. The benchmarks we used are those of traditional universes (MSCI Europe, MSCI USA, MSCI EM and FTSE UK All Shares) but corrected for the hedge funds’ structural net market exposure. This net market exposure is obtained by using a simple linear regression between universe and benchmark daily returns on over a rolling 36-month period from 2010 to 2018 to approximate their structural exposure relative to the benchmark.

Results

On average, 35% of hedge funds outperformed their benchmark in 2018. These were weak results, but still well above the average of 21% for the four traditional equity equivalents in 2018. Even so, 2018 was a bad year for hedge funds, having been penalised by the surge in volatility and equity market slump of Q4 in particular.

The spike in rates caused by increased political concerns and the perceived risk of the US economy overheating also had an impact. They were forced to deleverage and missed the rotation from cyclicals into defensives.

After a year in which all equity markets ended in negative territory, how did hedge funds perform in absolute terms? On average, 22% of them posted a return above zero. 52% returned under 5% however.

PERCENTAGE OF HEDGE FUNDS AS A FUNCTION OF THEIR 2018 RETURN SPLIT

% of funds

Europe Long Short

Emerging Markets

Long

UK Long Short

US Long Short

Average

Return < -5% 61% 62% 50% 35% 52%

Return > 0% 17% 23% 17% 30% 22%

Source: Lyxor ETF, Morningstar data from 30/12/2017 to 28/12/2018 based on UCITS hedge funds domiciled in Europe.


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Over the last five years, hedge funds’ results appear significantly better, with 50% having outperformed the benchmark - although the number of funds is more limited in our sample. This 50% figure is well above the average percentage of outperformers in the equivalent traditional active equity universes. So, while 2018 and 2016 were bad years for hedge fund managers, all the other years on our study had been pretty good for long/short equity funds, as we can see in the table on the right:

PERCENTAGE OF MANAGERS OUTPERFORMING THEIR ADJUSTED BENCHMARK

Universe 2018 2017 2016 3Y 5Y

Europe Long Short 30% 46% 25% 21% 56%

Emerging Markets Long Short 38% 30% 38% 44% 67%

UK Long Short 38% 38% 13% 8% 44%

US Long Short 35% 37% 25% 37% 33%

Average 35% 38% 25% 28% 50%

Source: Lyxor ETF, Morningstar data from 01/01/2014 to 28/12/2018 based on UCITS hedge funds domiciled in Europe.

2018 was a weak year for long/short equity hedge funds. However, they still did better overall (on average) relative to their benchmarks than traditional active funds. What’s more, a much more significant number of hedge funds have outperformed their benchmark over the longer term.

15. What’s been going on with fund flows?

1. Fund flows fell significantly

Overall fund flows in Europe fell significantly in 2018, down from EUR 770bn in 2017 to EUR 156bn. This figure is well below the average flow of EUR 417bn over the past seven years.

2. Passive flows above those of active funds

In Europe, active funds gathered net inflows of EUR 72bn over the year, while passive funds collected EUR 84bn. This is the first year in Europe in which passive fund flows have surpassed those into active. The average gap over 7 years in favour of active funds has been EUR 245bn per year.

3. The gap to passive widened in Q4

When the market slumped in Q4 with the MSCI ACWI down 11%, passive funds showed more resilience, with inflows of EUR 10bn over the same period. Active funds experienced outflows of EUR 103bn over the same period. This goes against the commonly held view that passive funds will increase market trend in the event of a downturn.

ACTIVE AND PASSIVE FLOWS BY QUARTER IN EUROPE IN 2018 (EUR BILLION)

200

150 142

3625

177

22

-103

10

7284

198

-34

3

100

50

0

-50

-100

-150Q1 Q2 Q3 Q4 Q4 monthly avg9 month avg2018

Active funds Passive funds

Source: Lyxor ETF, Morningstar data in EURbn from 30/12/2017 to 31/12/2018.


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CUMULATIVE NET NEW ASSETS OF EUROPEAN-DOMICILED FUNDS SINCE 2012 (EUR BILLION)

Active Passive

3,000

2,500

2,000

1,500

1,000

500

0Jan-2012

Jan-2013

Jan-2014

Jan-2015

Jan-2016

Jan-2017

Jan-2018


Passive flows above those of active funds. In Europe, active funds gathered net inflows of EUR 72bn over the year, while passive funds collected EUR 84bn.

Equities

1. Passive outdoes active overall

Despite falling from EUR 104bn in 2017 to EUR 52bn in 2018, flows into passive equity funds in Europe were again higher than those into active. The latter collected just EUR 27bn of inflows in 2018, well below their seven-year average of EUR 52bn. It was the fifth consecutive year that flows into passive equity funds have exceeded those into active.

CUMULATIVE NET NEW ASSETS OF EUROPEAN DOMICILED EQUITY FUNDS SINCE 2012 (EUR BILLION)

400

350

300

250

200

150

100

50

0

-50

Active Passive

Jan-2012

Jan-2013

Jan-2014

Jan-2015

Jan-2016

Jan-2017

Jan-2018


2. Passive wins from Q2 to Q4

Passive equity funds gathered higher inflows than active in Q2, Q3 and Q4. The trend accelerated in Q4, when there were EUR 16bn of outflows from active equity funds and EUR 1.5bn of inflows into passive funds. Over the first nine months of the year active funds received an average of EUR 5bn of inflows per month, compared with a monthly average of outflows of EUR 7bn in Q4. Passive funds received an average of EUR 6bn per month in the first nine months of the year and average inflows of EUR 1bn per month in Q4 – a real show of resilience.

ACTIVE AND PASSIVE EQUITY FUND FLOWS BY QUARTER IN EUROPE (EUR BILLION)

0

-10

-20

10

20

30

40

50

60

Q1 Q2 Q3 Q4 Q4 monthly avg

9 monthavg

2018


45

28

-4

72

15

-16

2

27

52

5 6

-5

1


3. Passive most popular for US, European and emerging equities

Passive US equity funds collected EUR 24bn of assets in 2018, while active funds received less than EUR 1bn. Passive European equity funds received EUR 3bn of inflows, while there were outflows of EUR 28bn from active funds. Active emerging equity funds gathered inflows of EUR 6bn over the year, while passive funds collected EUR 10bn.

However, active received higher flows than passive in developed market world, global market (developed and emerging markets) and Japanese equity funds. Active developed market world equity funds received EUR 20bn of inflows, while passive funds gathered EUR 13bn.

Active global equity funds received EUR 21bn, while passive funds gathered EUR 1.1bn of inflows. In Japanese equities, EUR 1.6bn went into active funds, while there were EUR 3bn of outflows from passive funds.

It was the fifth consecutive year that flows into passive equity funds have exceeded those into active. In Q4, equity passive funds continued to see inflows whereas active equity funds saw strong outflows, a real show of resilience.


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Fixed income

1. Active suffers outflows for the first time

After record inflows in 2017, there were outflows of EUR 33bn from active fixed income funds in 2018 – the first ever year of outflows – in a challenging environment for both rates and spreads. Passive fixed income funds gathered inflows of EUR 31bn, although this was 33% lower than they collected in 2017, it is in line with the long-term average of flows collected annually.

CUMULATIVE NET NEW ASSETS OF EUROPEAN-DOMICILED FIXED INCOME FUNDS SINCE 2012 (EUR BILLION)

Active Passive

1,200

1,000

800

600

400

200

0

Jan-2012

Jan-2013

Jan-2014

Jan-2015

Jan-2016

Jan-2017

Jan-2018


2. Passive wins three out of four quarters

Active fixed income funds suffered outflows in every quarter last year. As was the case with equities, the trend accelerated in Q4, when a record EUR 50bn flowed out following some very disappointing performance. It was undoubtedly a challenging year with limited trends on the interest rate front and a reversal of the credit cycle. However, passive fixed income funds again showed their resilience, particularly in Q4, when they gathered inflows of EUR 8bn as investors took active risk off the table.

ACTIVE AND PASSIVE FIXED INCOME FUND FLOWS BY QUARTER IN 2018 (EUR BILLION)

-60

-50

-40

-20

-10

0

20

30

40

Q1 Q2 Q3 Q4 Q4 monthlyavg

9 monthavg

2018

10

-5-8

86

30


2

-17

7

-50

2 3

31

-33

10

-30


Passive developed-market government bond funds collected EUR 14bn of assets in 2018, while there were EUR 300 million of outflows from active funds. Among global aggregate bond funds, EUR 6bn went into passive, but there were outflows of EUR 6bn from active. This is particularly noteworthy as, historically, global aggregate funds have been among the most popular of active bond funds.

Passive investment-grade corporate and high yield bond funds were also more popular than their active counterparts in 2018. Both categories suffered significant outflows on the active side, with EUR 23bn flowing out of investment grade and EUR 32bn out of high yield. There were EUR 1bn of inflows into passive investment-grade corporate bond funds and EUR 600M of outflows from passive high yield funds. On the other hand, active emerging debt funds gathered more inflows (EUR 10bn) than passive funds (EUR 6bn).

There were outflows of EUR 33bn from active fixed income funds in 2018 – the first ever year of outflows – in a challenging environment for both rates and spreads. Passive fixed income funds gathered inflows of EUR 31bn. Particularly in Q4, passive fixed income funds again showed their resilience, when they gathered inflows of EUR 8bn as investors took active risk off the table with active funds seeing some huge outflows.


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16. The effect on assets under managementAssets under management in Europe including active and passive funds amounted to EUR 8trn at the end of 2018, which is 26% of overall global industry AUM. This was 4% down on 2017 after the significant market decline and much reduced flows. EUR 6.6trn of that was in active strategies and EUR 1.3trn in passive. AUM in active strategies fell by 5% over the year, while AUM in passive rose by 3%, reflecting higher inflows into passive funds.

AUM in passive funds in Europe have grown steadily over the past two decades and now account for 17% of total AUM, up from 12% in 2012. Passive equity funds account for 28% of AUM in equity funds in Europe. Passive accounts for 14% of AUM in fixed income.

SPLIT BETWEEN ACTIVE AND PASSIVE IN EUROPEAN FUNDS

PASSIVE FUNDS ACTIVE FUNDS

17%

83%EUROPE

Source: Lyxor ETF, Morningstar data as of 28/12/2018.

SPLIT BETWEEN ACTIVE AND PASSIVE EQUITY FUNDS IN EUROPE

EUROPE

EQUITY PASSIVE FUNDS ACTIVE EQUITY FUNDS

28% 72%


SPLIT BETWEEN ACTIVE AND PASSIVE FIXED INCOME FUNDS IN EUROPE

EUROPE

FIXED INCOMEPASSIVE FUNDS

ACTIVE FIXED INCOME FUNDS

14%

86%


AUM in passive funds in Europe now account for 17% of total AUM. Passive equity funds account for 28% of AUM in equity funds in Europe. Passive accounts for 14% of AUM in fixed income.

17. How have ETF costs evolved? How do they compare to those of active funds?

Low cost is one of the key advantages of investing in ETFs. The average TER of European ETFs was 0.26% in 2018, down from 0.28% in 2017. The average TER of equity ETFs

fell further in 2018 to 0.26%, its lowest level in six years. And, after reaching a high in Q3 2017, the average TER of fixed income ETFs fell to 0.25% in 2018.

AVERAGE TER OF EUROPEAN ETFS SINCE 2013 (%)

0.45%

0.40%

0.35%

0.30%

0.25%

0.20%

0.15%Jan-2013

Jun-2013

Nov-2013

Jun-2018

Nov-2018

Apr-2014

Sep-2014

Feb-2015

Jul-2015

Dec-2015

May-2016

Oct-2016

Mar-2017

Aug-2017

Jan-2018

Total Equity Fixed income

Source: Lyxor ETF, Bloomberg data from 30/12/2012 to 28/12/2018.


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We also look at the average fees of our five key active equity fund universes and continue to find a clear advantage for ETFs. The average TER of these five equity universes of 82bp was significantly higher than the average of 23bp for the equivalent ETFs.

Low cost is one of the key advantages of investing in ETFs. The average TER of European ETFs was 0.26% in 2018.

AVERAGE FEES OF EUROPEAN ACTIVE FUNDS AND ETFS (%)

% Active funds management fees ETFs TER

Europe Large Caps 0.87 0.32

Eurozone Large Caps 0.96 0.12

US Large Caps 0.56 0.09

Japan All Caps 0.87 0.31

Emerging Markets Large Caps 0.82 0.32

Average 0.82 0.23

Source: Morningstar asset-weighted data as of 28/12/2018.

18. Can asset managers perform consistently over time?

a- Percentage of funds which outperform

Over the 10 years we’ve been conducting this study, 33% of active managers have, on average. outperformed over one year. Only 15% still outperformed by the end of the year two and just 7 % by the end of year three.

Conducting this study not only over one year but over 3 years and 5 years as well gives us similar results. On average, 30% of active managers outperformed over 3 years, but only 17% continue to outperform in the following 3 years. Just 9% continued to outperform in the three years after that.

On average, 34% of active managers outperformed over 5 years, but only 13.5% continue to do so in the following 5 years. All of which goes to show how difficult it is for active managers to consistently beat their benchmark.

AVERAGE PERFORMANCE CONSISTENCY OVER 1 YEAR

1Y frequency Period 1 Period 2 Period 3

Average Equity 35.4% 16.2% 7.8%

Average Fixed Income 26.6% 11.1% 4.9%

Average 32.6% 14.6% 6.9%

Source: Lyxor ETF, Morningstar data as of 28/12/2018

AVERAGE PERFORMANCE CONSISTENCY OVER 3 YEARS

3Y frequency Period 1 Period 2 Period 3

Average Equity 32.9% 18.9% 10.4%

Average Fixed Income 24.2% 13.2% 6.6%

Average 30.1% 17.1% 9.2%


AVERAGE PERFORMANCE CONSISTENCY OVER 5 YEARS

5Y frequency Period 1 Period 2

Average Equity 36.2% 14.0%

Average Fixed Income 29.4% 12.5%

Average 34.0% 13.5%


All of our data goes to show how difficult it is for active managers to consistently beat their benchmark.


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b- Universes that tend to outperform

We look here at how many times a universe has outperformed its benchmark over the decade to end 2018 and whether there are some universes where managers consistently do so.

In 2018, all the universes we cover underperformed their benchmarks, with the exception of China. In the active China large cap equity fund universe, managers have outperformed for six of the last 10 years. Active emerging market and European equity funds have outperformed their benchmark in around half of the years between 2008 and 2018, yet they both underperformed in 2018.

Within active fixed income, Euro bond and Euro inflation-linked bond fund managers have outperformed in five or six of the intervening years but failed to do so in 2018.

Interestingly, in the Europe small caps universe, active managers outperformed in four of the ten years we’ve included in our analysis, but their large caps counterparts did so in half of the 10 years. It’s therefore difficult to conclude that in the small cap universe – a relatively inefficient market – active management generates more alpha than in a more efficient market.

This also holds true in fixed income where, for example, active European high yield fund managers only outperformed twice in the ten years of our study where as active managers of their large cap counterparts, in the euro the corporate bond universe, outperformed in 4 of the ten years.

Active managers’ returns over 10 years seem to call the commonly held view that they are more likely to outperform in less efficient markets into question.

FREQUENCY OF OUTPERFORMANCE IN EACH UNIVERSE OVER THE PAST TEN YEARS AND 2018 RELATIVE RETURNS

IN EQUITY MARKETS

Equity Universes

Outperformance frequency

by universe in the past 10Y

% of outperformers

in 2018

Germany Large Caps 60% 17%

Italy Large Caps 60% 7%

Spain Large Caps 60% 43%

EM Large Caps 60% 21%

China Large Caps 60% 38%

Europe Large Caps 50% 18%

Europe Small Caps 40% 45%

Japan All Caps 40% 34%

UK All Caps 30% 16%

Eurozone Large Caps 20% 18%

US Small Caps 20% 44%

World Large Caps 20% 19%

Switzerland Large Caps 10% 15%

US Large Caps 10% 20%

France Large Caps 0% 3%

Average 36% 27%

Source: Morningstar data from 31/12/2008 to 28/12/2018.

FREQUENCY OF OUTPERFORMANCE IN EACH UNIVERSE OVER THE PAST TEN YEARS AND 2018 RELATIVE RETURNS

IN BOND MARKETS

Fixed income Universes

Outperformance frequency

by universe in the past 10Y

% of outperformers

in 2018

Global Bonds 60% 12%

Euro Inflation Linked 50% 19%

EUR Corporate 40% 18%

Euro High Yield 20% 23%

US High Yield 20% 24%

Euro Govies 10% 23%

US Corporate 10% 13%

Emerging Debt 10% 7%

Average 28% 18%



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19. What do the results of our research mean for portfolio construction?

We have demonstrated in the analysis of the performance of active funds vs. their benchmark through different periods of the cycle, the interest of selecting the right investment vehicle in order to enhance portfolio returns.

We reiterate our view that on top of asset allocation, an appropriate choice between investment tools is key to help generating strong long-term portfolio returns.

To help investors building their allocation between active and passive investment styles, we now integrate an outlook into our Alpha Beta Allocator reports dedicated to what’s likely to be hot and what’s not for active managers across four equity markets (US, Europe, Japan and Emerging markets). Our view is that Active and Passive funds have different relative appeal all along the business cycle. Schematically, the cycle can be broken into four main phases:

- Recession, during which Active alternative and, to a lower extent, mutual funds should be favoured.

- Early phase of the cycle, during which, investors should largely favor Passive as markets gets driven by strong identifiable trends, with beta become the dominating source of performance.

- Mid and Late phase of the cycle, characterised by more frequent macro turns and more fragile market directionality, emphasize the benefits of a combination between Active and Passive.

ACTIVE PASSIVE COMBINATION THROUGH THE BUSINESS CYCLE

Recession Early Cycle Mid Cycle Late Cycle

Passive - -

Active Long -

Active AI + +

Passive + +

Active Long +

Active AI - -

Passive +/-

Active Long +/-

Active AI +/-

Passive +

Active Long + +

Active AI =

StraightforwardActive/Passive Allocation

ShiftingActive/Passive Allocation

Source: Lyxor Cross Asset Research.

Our outlooks are based on the analysis of the distinct sets of drivers, which we believe, matter the most for Passive and for Active environments. We evaluate these drivers out of thousands of macro and market data and translate them into scorings for each management style and regions.

Evaluating the stage of the business cycle with factors that can break or prolong it on the one hand, while scrutinizing the impact in equity and cross-asset markets on the other hand, are decisive for investors willing to get involved in Passive vehicles in our view.

In contrast, environments conducive for active management will display a diversity of market catalysts and themes, coherence between prices and fundamentals, with fresh enough arbitrage opportunities. The understanding of the market structures (correlations, risk of reversals etc.) and the in-depth analysis of corporate earnings provide useful insights to that regards.

ACTIVE PASSIVE ALLOCATION SCORING SUMMARY

PASSIVE ALLOCATION

SCORING

Business Cycle Stage

Monetary & Fiscal Policies

Tail Risks

Equities Directionality

Cross-Asset Directionality

ACTIVE ALLOCATION

SCORING

Arbitrage Potential

Nature of Stock Drivers

Fundamental Rationality

Opportunities Freshness

Reversal Risks

Catalysts Intensity+ Structural constraints

Source: Lyxor Cross Asset Research.

When it comes to generating strong and long-term returns, spending time on choosing the right investment tools should be taken into account in addition to making the right asset allocation choices.


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20. What are our key recommendations?

Using the long-term empirical results from our study, we have proposed a neutral allocation for an efficient strategic portfolio allocation composed of passive, traditional active and alternative funds. We have implemented it based on Lyxor Cross Asset Research asset allocation recommendations and the statistical results of our research to propose a portfolio combining Active and Passive funds.

To this neutral strategic allocation, we include a range within which this allocation could vary; any changes within this range could be viewed as the tactical allocation between investment tools. This tactical allocation would depend on market conditions together with investor ability to select funds, either traditional or alternative.

Based on our calculations namely the yearly 10-year average percentage of active managers outperforming, the proposed neutral allocation portfolio should be composed of 60% passive, 30% traditional active and 10% of alternatives funds. Depending on market conditions and investors’ ability to select outperforming funds, the neutral allocation can vary between the following ranges: 40–70% for passive, 20–40% for traditional active and 5–20% for alternatives.

PROPOSED LONG-TERM NEUTRAL ALLOCATION WITH TACTICAL ALLOCATION RANGES

INVESTMENT VEHICLE NEUTRAL ALLOCATION RANGE

10%

30%

60% 40-70%

20-40%

5-20%ALTERNATIVE FUNDS

PASSIVE

TRADITIONAL ACTIVE FUNDS

Source: Lyxor ETF, for illustrative purposes only.

Using the long-term empirical results from our study, we were able to build what we call a “neutral” allocation for an efficient, strategic portfolio split between passive, traditional active and alternative funds. These weights are, however, only half the job.

To bring it to life, we’ve used the asset allocation recommendations of Lyxor’s Cross Asset Research team (as at March 2019) and the results of our own research into the performance of each style, in each of the investment universes we cover, to construct a more detailed portfolio.

This portfolio goes deeper into asset allocation, but also exposes which vehicle to choose and where. It will be updated quarterly, as new recommendations are made, and new results come through.

A 4-step process:

1. Start with a “neutral” Asset Allocation

We start from a portfolio composed of 45% of stocks, 45% of fixed income and 10% of hedge funds.

2. Add current Lyxor Cross-Asset Research recommendations

We adapt that portfolio to take Lyxor Cross-Asset Research asset allocation recommendations into account.

3. Use our research to determine which investment vehicle to use

Based on our Active Passive statistical research, we deduce a combined Active Passive allocation for each asset classes of the portfolio.

4. Include the active/passive outlook to determine final portfolio structure

We will then adjust each quarter the weight of the active and passive components of the portfolio according to the unique tool we have developed in collaboration with Lyxor Cross Asset Research that gives outlooks on Passive and Active environments (see §19).

Check out our first portfolio on next page:


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PROPOSED PORTFOLIO INCLUDING BOTH ASSET ALLOCATION AND INVESTMENT STYLE SELECTION

Investment universesCAR Research

recommendation as of March 2019

Active weight

Passive weight

Total weight

Equity EM Large Caps OW 20% 0% 20%

Europe Large Caps UW 4% 4% 9%

Japan All Caps N 4% 10% 15%

US Large Caps N 0% 15% 15%

Total Equity 29% 29% 58%

Bonds Euro Corporate UW 3% 4% 7%

Euro Govies UW 0% 7% 7%

US Corporate UW 0% 7% 7%

Emerging Debt OW 0% 15% 15%

Total Bonds 3% 32% 35%

Total Bonds + Equity 32% 61% 93%

Hedge Funds Long Short UCITs HF EUROPE UW 2% 2%

Long Short UCITs HF US UW 2% 2%

Long Short UCITs HF EM UW 2% 2%

Total Hedge Funds 7% 7%

Total 39% 61% 100%

Source: Lyxor Cross Asset research, Lyxor ETF Research. OW: Overweight, UW: Underweight, N: Neutral.

THE FIGURES RELATING TO PAST PERFORMANCES REFER TO PAST PERIODS AND ARE NOT A RELIABLE INDICATOR FOR FUTURE RESULTS

analysing active & passive fund performance _analysing active passiv… · in conclusion, 2019...

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