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UCITS Risk Reporting
Dashboard
31.12.2019
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UCITS Risk Reporting Dashboard
CONTENTS
1. Introduction 3
1.1 Scope of the UCITS Risk Reporting 3 1.2 Coverage of the full reporting scope by investment policy type and global
exposure calculation method 4 2. Executive summary 5 3. Overall UCITS population 6
3.1 Main characteristics 6 3.2 Realised leverage 7
4. UCITS in the full reporting scope 9 4.1 Main characteristics 9 4.2 Global exposure and leverage 10 4.3 Stress testing and other risk indicators 13 4.4 Efficient portfolio management (EPM) techniques 15 4.5 Counterparty risk and collateral in relation to EPM techniques / OTC and
traded derivatives 17 4.6 Liquidity 19 4.7 Credit 23
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1. Introduction
1.1 Scope of the UCITS Risk Reporting
In the context of the UCITS Risk Reporting, all Luxembourg domiciled UCITS 1 authorised by the CSSF are required
to provide some general information/basic functional data including the global exposure calculation method and
the realised level of leverage, as well as, for UCITS under a VaR approach, the expected level of leverage. In
addition, detailed information on risks is requested for UCITS falling in the “ full reporting scope", i.e. UCITS
fulfilling at least one of the following two criteria:
- net assets above EUR 500 million;
- use of VaR for the calculation of global exposure covered by Article 42(3) of the 2010 Law with an average
gross leverage during the semester greater than 250%2.
1 In this report, the terms “UCITS” and “fund” will be used both for an entity in the case of a non -umbrella UCITS and for each sub-
fund in the case of an umbrella UCITS.
2 In accordance with the rules set out in the applicable regulation, the gross leverage is calculated as the notional sum of th e derivatives
used.
Not in the
reporting scope22%
883 Bn€
TNA >= 500M€
73%
2 877 Bn€TNA >= 500M€ and
real levg >= 250%3%
130 Bn€
Real levg >= 250%
1%38 Bn€
In the reporting
scope78%
3 045 Bn€
Overall UCITS Population and UCITS falling in the reporting scope (in terms of net assets)
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1.2 Coverage of the full reporting scope by investment policy type and global exposure
calculation method
Note: Fund classifications are based on the BCL investment policy types. The category “Hedge funds” includes
funds that implement alternative strategies while respecting the UCITS regulatory framework (often referred to
as “liquid alternative funds”).
0%
20%
40%
60%
80%
100%
0 Bn
500 Bn
1.000 Bn
1.500 Bn
Covera
ge r
ate
Net
assets
Coverage rate by investment policy type
0%
20%
40%
60%
80%
100%
0 Bn
500 Bn
1.000 Bn
1.500 Bn
2.000 Bn
2.500 Bn
3.000 Bn
Covera
ge r
ate
Net
assets
Coverage rate by global exposure calculation method
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2. Executive summary
• The overall UCITS population, as at 31 December 2019, is made of 10 993 funds (incl. dormant /
unlaunched funds) totaling net assets of EUR 3 928 Bn€, mainly Equity and Bond funds (resp. 35% and
34% in terms of net assets), and funds under the Commitment approach (66% in terms of net assets).
• The Full reporting scope is made of 1 972 funds totaling net assets of EUR 3 045 Bn€. It fairly covers
the overall UCITS population. The predominant criterion for falling in the full reporting scope remains size
(i.e. TNA above EUR 500 million).
• The main change compared to December 2018 is a decrease in gross leverage from 70% to 63%,
o mainly due to bond funds and hedge funds / funds under the absolute VaR approach and
o mainly explained by a lower use of short-term interest rate derivatives (
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3. Overall UCITS population
3.1 Main characteristics
3.1.1 Net assets
3.1.2 Investment policy types
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Fund size
Market concentration
units net assets
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
% o
f to
tal net
assets
number of funds
Market concentration
1.337 bn€
34%
1.357 bn€
35%
770 bn€
20%
130 bn€
3%
15 bn€
0%
319
bn€8%
Investment policy types
(in terms of net assets)
Bond funds Equity funds Mixed funds
Hedge funds Other funds MMF
3.115
28%
4.034
37%
2.851
26%
616
6%
246
2%131
1%
Investment policy types
(in terms of units)
Bond funds Equity funds Mixed funds
Hedge funds Other funds MMF
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3.1.3 Global Exposure calculation methods
3.2 Realised leverage
3.2.1 Realised leverage by investment policy type and by global exposure calculation method
Methodology note: For the purpose of the 2 graphs above, the realised leverage is
- for funds under a VaR approach, the semester-average value;
- for funds under the commitment approach and TNA above 500M EUR, the semester-end value; and
- for funds under the commitment approach and with TNA below 500M EUR, the TNA-weighted average of
the semester-end leverage of all funds in the same category under the commitment approach and with
TNA above 500M EUR.
2.600
bn€ 66%
644 bn€
16%
684 bn€
18%
Global exposure calculation method (in terms of net assets)
Commitment Absolute VaR Relative VaR
7.565
69%
1.802
16%
1.626
15%
Global exposure calculation method (in terms of units)
Commitment Absolute VaR Relative VaR
84%
14%
96%
318%
120%
3%0%
50%
100%
150%
200%
250%
300%
350%
400%
Realised levera
ge
Average TNA-weighted realised leverage
Dec 2016 June 2017 Dec 2017 June 2018Dec 2018 June 2019 Dec 2019
23%
81%
204%
63%
0%
50%
100%
150%
200%
250%
300%
Realised levera
ge
Average TNA-weighted realised leverage
Dec 2016 June 2017 Dec 2017 June 2018Dec 2018 June 2019 Dec 2019
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3.2.1 Realised leverage for funds under the commitment approach
Methodology note: The realised leverage level is based on the commitment approach, as defined by CESR 10/788.
3.2.2 Realised and expected leverage for funds under the VaR approach
Methodology note: The realised leverage level is based on the sum of the notionals method as defined by CESR
10/788. Where several levels of leverage are disclosed in the prospectus (for example an expected and a
maximum or a range with minimum and maximum), the expected leverage shown on the graph refers to the
highest number.
0%
20%
40%
60%
80%
100%
Realised leverage (Commitment)
units net assets
0%
20%
40%
60%
80%
100%
Realised leverage (VaR)
units net assets
0%
20%
40%
60%
80%
100%
Expected leverage (VaR)
units net assets
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4. UCITS in the full reporting scope
4.1 Main characteristics
LongShortLong-ShortMarket-neutral
Arbitrage
Unconstrained/Multi-strategy
0 Bn
200 Bn
400 Bn
600 Bn
800 Bn
1.000 Bn
net
assets
(Bn€)
Net assets by principal asset class and investment strategy
1.791 bn€
59%714 bn€
23%
180 bn€
6%
10 bn€
0%
351 bn€
12%
Investment regions(in terms of net assets)
Multiple Region Europe
Asia & Pacific Central & South America
North America
1.200
61%
465
24%
128
6%
8
0%
171
9%
Investment regions(in terms of units)
Multiple Region Europe
Asia & Pacific Central & South America
North America
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4.2 Global exposure and leverage
4.2.1 Funds under the Commitment approach
4.2.2 Funds under the VaR approach
0%
5%
10%
15%
20%
25%
30%
Gross leverage per derivative category (Commitment funds)
Futures Swaps Forwards Options
0%
5%
10%
15%
20%
25%
30%
Gross leverage per risk factor (Commitment funds)
Equity IR Credit FX Other (incl TRS)
0%
50%
100%
150%
200%
Gross leverage per derivative category (VaR funds)
Futures Swaps Forwards Options
0%
50%
100%
150%
200%
Gross leverage per risk factor (VaR funds)
Equity IR Credit FX Other (incl TRS)
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Note: As set out in the guidelines, “positive” interest rate and credit spread duration correspond to long exposure
on bonds, i.e. exposures such as fixed rate receiver of an IRS or protection seller of a CDS.
4.2.3 Usage of leverage
Note: For the purpose of this report, the usage of leverage is defined as the ratio of the realised to the regulatory
limit for funds under the commitment approach, respectively the ratio of the realised to the expected level of
gross leverage disclosed in the prospectus for funds under the VaR approach.
12%
5%
2%
5%
9%
4%
1%
1%
-8%
-6%
-2%
-9%
-8%
-5%
-1%
0%
-25% -15% -5% 5% 15% 25%
Equity
FI / IR < 3M
FI / IR 3-12M
FI / IR 1-5Y
FI / IR > 5Y
Credit spread duration
Commodity
Volatility
Gross leverage per risk factors (VaR funds) - ex-FX and "other"
Dec 2019 Short / neg duration Dec 2019 Long / pos duration
June 2019 Short / neg duration June 2019 Long / pos duration
962
112
44
22
1
1045
65
28
3
0
0% 20% 40% 60% 80% 100%
0 - 25%
25% - 50%
50% - 75%
75% - 100%
> 100%
% of the population
Usage
Usage of leverage (Commitment funds)
Average
Maximum
174
117
146
147
143
104
245
166
210
112
74
24
0% 10% 20% 30% 40%
0 - 25%
25% - 50%
50% - 75%
75% - 100%
100% - 150%
> 150%
% of the population
Usage
Usage of leverage (VaR funds)
Average
Maximum
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4.2.4 Value-at-Risk (VaR)
Net assets and average TNA-weighted VaR by principal asset class and principal investment strategy
Note: The “heatmap” graph represents each fund category by a rectangle whose size is proportional to its net
assets and whose colour reflects its average absolute VaR (confidence interval of 99% and holding period of 1
month). For the avoidance of doubt, the graph is based on the absolute VaR levels of both UCITS under an
absolute and a relative VaR approach.
0%
2%
4%
6%
8%
10%
12%
14%
Avera
ge A
bsolu
te V
aR
Average VaR (TNA-weighted)
Bond funds Equity funds Mixed funds
Hedge funds Other funds MMF
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4.3 Stress testing and other risk indicators
4.3.1 Univariate stress test results
-12,6%
-0,6%
-28,9%
-8,8%
-8,7%
0,0%
-35%
-30%
-25%
-20%
-15%
-10%
-5%
0%
Result in %
of
net
assets
Equities -30%
Dec 2016 June 2017 Dec 2017 June 2018Dec 2018 June 2019 Dec 2019
0% 20% 40% 60%
< -35%
-35% to -25%
-25% to -15%
-15% to -5%
-5% to 0%
0%
0% to 5%
>= 5%
% of funds (Bond funds and MMF excluded)
Result a
s %
of
net
assets
Equities -30%
June 2019
December 2019
-3,6%
-8,1%
-0,1%
-2,4%
-3,9%
-0,3%
-10%
-8%
-6%
-4%
-2%
0%
2%
Result in %
of
net
assets
Interest rates +200bps
Dec 2016 June 2017 Dec 2017 June 2018Dec 2018 June 2019 Dec 2019
0% 10% 20% 30% 40% 50%
< -35%
-35% to -25%
-25% to -15%
-15% to -5%
-5% to 0%
0
0% to 5%
>= 5%
% of funds (Equity funds excluded)
Result a
s %
of
net
assets
Interest rates +200bps
June 2019
December 2019
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Note: As set out in the guidelines, the univariate stress test results should not take into account
dependencies/correlations between risk factors. For the sake of readability, Bond funds and MMF (resp. Equity
funds) are excluded from the graph illustrating the univariate stress test on equities (resp. on interest rates and
on credit spreads).
4.3.2 Annualised realised volatility
-2,8%
-6,4%
-0,1%
-1,8%
-1,1%
-0,1%
-10%
-9%
-8%
-7%
-6%
-5%
-4%
-3%
-2%
-1%
0%
Result in %
of
net
assets
Credit spreads +100%
Dec 2016 June 2017 Dec 2017 June 2018Dec 2018 June 2019 Dec 2019
0% 20% 40% 60% 80%
< -35%
-35% to -25%
-25% to -15%
-15% to -5%
-5% to 0%
0
0% to 5%
>= 5%
% of funds (Equity funds excluded)
Result a
s %
of
net
assets
Credit spreads +100%
June 2019
December 2019
0%
5%
10%
15%
20%
Realised volatility (TNA-weighted)
Bond funds Equity funds Mixed funds
Hedge funds Other funds MMF
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4.4 Efficient portfolio management (EPM) techniques
4.4.1 Evolution of volumes and number of active funds by EPM type
4.4.2 Main active Investment Fund Managers (IFMs) per EPM type
Note: Repos are not pictured above as their volumes are much lower (total 1.3Bn€). Similarly to Reverse repos,
repos are dominated by a few actors (~80% of volumes from funds managed by 3 IFMs).
1
35
72
-
109
0 Bn
20 Bn
40 Bn
60 Bn
80 Bn
100 Bn
120 Bn
140 Bn
EPM volumes at semester-end
Dec 2016 June 2017 Dec 2017 June 2018
Dec 2018 June 2019 Dec 2019
33
98
634
-
696
0
100
200
300
400
500
600
700
800
Number of funds engaged in EPM transactions
Dec 2016 June 2017 Dec 2017 June 2018
Dec 2018 June 2019 Dec 2019
IFM 1
IFM 2
IFM 3
Securities lending (72 Bn €)
IFM 1
IFM 2
IFM 3
Reverse repos (35 Bn €)
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4.4.3 EPM volumes by investment strategy
4.4.4 Securities Lending: Use of Agent lenders & indemnification against borrower default
38
23
10
32
0 Bn
10 Bn
20 Bn
30 Bn
40 Bn
50 Bn
EPM volumes by investment strategy
Sec Lending Sec Borrowing Repos Reverse Repos
31%
22 bn€
43%
31 bn€
27%
19 bn€
69%
50 bn€
Sec Lending (in volume)
No use of agent lenders or other intermediaries
use... with indemnification
use... without indemnification
19%
130
60%
372
21%
132
81%
504
Sec Lending (in units)
No use of agent lenders or other intermediaries
use... with indemnification
use... without indemnification
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4.5 Counterparty risk and collateral in relation to EPM techniques / OTC and traded
derivatives
Methodology note: The graph represents the largest counterparties of UCITS in terms of (positive and negative)
net counterparty exposure of UCITS in the full reporting scope. More specifically, the main counterparties are
determined based on the sum of the absolute values of the net exposures of all UCITS in the full reporting scope
to their three counterparties with the largest positive net exposure and their three counterparties with the largest
negative net exposure at semester-end. It is determined at group rather than at legal entity level.
363 bn€
24%
156 bn€
10%
1.012 bn€
66%
1.169 bn€
76%
Trading and clearing of financial derivative
instruments (based on gross assets)
Listed OTC - CCP cleared OTC - Bilaterally cleared
Ctpy1
Ctpy 2
Ctpy 3
Main counterparties on EPM and OTC derivatives transactions
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1106
110
35
19
10
52
675
8
2
2
0
9
0% 20% 40% 60% 80% 100%
0% - 1%
1% - 2%
2% - 3%
3% - 4%
4% - 5%
>= 5%
% of funds engaged in OTC derivatives / EPM transactions
exposure
in %
of
net
assets
Overall net positive counterparty exposure
on OTC derivatives / EPM transactions
EPM
OTC
94%
112 Bn€
4% / 5 Bn€
1% / 1,1 Bn€
1% / 1,1 Bn€
0% / 0,5 Bn€
Reinvestment of
cash collateral
Collateral received on EPM / OTC derivative
transactions and reinvestment of cash collateral
Non cash collateral Deposits Govt bonds Rev repos Short-Term MMF
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4.6 Liquidity3
4.6.1 Portfolio liquidity at semester-end in normal market conditions
3 The figures are based on the self -assessment of the Inves tment Fund Managers on the time to liquidate of their funds and
may appear relatively over-optimis tic.
0%
20%
40%
60%
80%
100%
Asset
liquid
ity in %
of
net
assets
Time to liquidate (normal market conditions)
All funds Bond funds Equity funds Mixed fundsHedge funds Other funds MMF
85% 82% 84%88%
96% 99%
86%
0%
20%
40%
60%
80%
100%
Evolution of 7-days liquidity (all fund categories, normal market conditions)
Dec 2016 June 2017 Dec 2017 June 2018 Dec 2018 June 2019 Dec 2019
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4.6.2 Portfolio liquidity at semester-end in normal market conditions (bond funds)
0%
20%
40%
60%
80%
100%
Asset
Liq
uid
ity in %
of
net
assets
Time to liquidate (normal market conditions)focus on bond funds
All bond funds Investment Grade Bonds General Bonds
Emerging Markets Bonds High Yield Bonds
82%
91%
82% 80%73%
0%
20%
40%
60%
80%
100%
Evolution of 7-days liquidity (bond funds, normal market conditions)
Dec 2016 June 2017 Dec 2017 June 2018 Dec 2018 June 2019 Dec 2019
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4.6.3 Portfolio liquidity at semester-end in stressed market conditions4
4 As set out in the guidelines , this sub-section is optional and was filled in by a minority of funds (~30% of the full reporting scope). It
is critical to s tress that the results are based on different methodologies and/or assumptions .
0%
20%
40%
60%
80%
100%
Asset
Liq
uid
ity in %
of
net
assets
Time to liquidate (stressed market conditions)
All funds Bond funds Equity funds Mixed funds
Hedge funds Other funds MMF
69%63%
71%67%
89%
99%
74%
0%
20%
40%
60%
80%
100%
Evolution of 7-days liquidity (all fund categories, stressed market conditions)
Dec 2016 June 2017 Dec 2017 June 2018 Dec 2018 June 2019 Dec 2019
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4.6.4 Portfolio liquidity at semester-end in stressed market conditions (bond funds)
0%
20%
40%
60%
80%
100%
Asset
Liq
uid
ity in %
of
net
assets
Time to liquidate (stressed market conditions)focus on bond funds
All bond funds Investment Grade Bonds General Bonds
Emerging Markets Bonds High Yield Bonds
63%
77% 64%
55%
43%
0%
20%
40%
60%
80%
100%
Evolution of 7-days liquidity (bond funds, stressed market conditions)
Dec 2016 June 2017 Dec 2017 June 2018 Dec 2018 June 2019 Dec 2019
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4.6.5 Liquidity Management Tools
4.7 Credit
4.7.1 Aggregate credit exposure by internal ratings and by credit spreads
89%
63%
17%
98%
1%0%
20%
40%
60%
80%
100%
Available liquidity management tools (TNA-weighted)
Dec 2016 June 2017 Dec 2017 June 2018
Dec 2018 June 2019 Dec 2019
0%
36%
3% 0%0%
20%
40%
60%
80%
100%
Usage of liquidity management tools (at least once)
Dec 2016 June 2017 Dec 2017 June 2018
Dec 2018 June 2019 Dec 2019
-
200
400
600
800
1.000
1.200
0%
20%
40%
60%
80%
100%
120%
Num
ber
of
funds
% o
f net
assets
Aggregate credit exposure by internal ratings
rating = 1 rating = 2 rating = 3 rating = 4
rating = 5 rating = 6 rating = 7 rating = 8
rating = 9 rating = 10 Number of funds (rhs)
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Methodology note: As set out in the guidelines, this sub-section is only applicable, with a few exceptions (e.g.
funds of funds), to UCITS within the full reporting scope which have a total debt portfolio exposure (direct or
indirect) at semester-end greater than or equal to 50% of the UCITS total net assets. Exposures to debt securities
should be broken down by credit rating from 1 to 10 with reference to an internal assessment of the credit quality
of the said instruments, whereby rating 1 is deemed to be the upper credit rating (i.e. the highest quality) and
10 relates to defaulted securities.
-
200
400
600
800
1.000
1.200
0%
20%
40%
60%
80%
100%
120%
Num
ber
of
funds
% o
f net
assets
Aggregate credit exposure by credit spreads
cr spread < 100 bps cr spread > 100 and < 350 bps cr spread > 350 and < 1000 bps
cr spread > 1000 bps Number of funds (rhs)
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Commission de Surveillance du Secteur Financier
283, route d’Arlon
L-2991 Luxembourg (+352) 26 25 1-1
www.cssf.lu
mailto:[email protected]://www.cssf.lu/