Does Regulation Matter?
Riskiness and Procyclicality of Pension Asset Allocation
L.N. Boon Amundi, Netspar, Paris Dauphine...
2
Ongoing debate on pension regulation in Europe: application of a
Solvency Framework (EIOPA, 2012) ?
Our question: does t...
3
Related Literature: Drivers of pension fund’s allocation
Individual characteristics of the funds are a major determinant...
4
Related Literature: Debate on the efficiency of regulation
Use of risk models to calibrate solvency buffers
– Limit fina...
5
Empirical investigation of the drivers of pension fund’s asset
allocations
– Expanding the literature over all regulator...
6
Regulatory changes induced a significant reduction in risky asset
allocation
Risk-based capital requirements have the st...
7
We build two original procyclicality measures
– Funds are procyclical in the sense that they do not fully rebalance
– St...
8
Differences in Pension Funds’ Regulatory Environment
US public US private Canada public and private
Dutch public
and pri...
9
Differences in Pension Funds’ Regulatory Environment
US public US private
Canada public and
private
Dutch public
and pri...
10
Differences in Pension Funds’ Regulatory Environment
US public US private
Canada public
and private
Dutch public
and pr...
11
Differences in Pension Funds’ Regulatory Environment
US public US private
Canada public and
private
Dutch public and
pr...
12
Methodology : Regulatory variables definition
Variable Definition Riskiness Procyclicality
Investment requirements
Quan...
13
Methodology : Individual and institutional variables definition
Variable Definition Riskiness Procyclicality
Individual...
14
Panel regression analysis with the following explanatory variables
Methodology
InstitutionalFactor
FundCharacteristics
...
15
Allocation to risky assets
We estimate the following pooled panel regression model
Methodology
• is the allocation to r...
16
Procyclicality of Equity Investment
Definition of the procyclicality measure
Methodology
,-
(/)
= 1
1
0
if sign( - /
)=...
17
Procyclicality of Equity Investment
We define two alternative definitions of the reference weight
– A full rebalancing ...
18
Procyclicality of Equity Investment
We estimate the following logit regression model
Methodology
• ,-
@
is the procycli...
19
CEM Benchmarking Database
– More than 800 DB pension funds
– Around 500 in the US, 250 in Canada and 80 in the Netherla...
20
Pension Funds’ Measure of Procyclicality
Procyclicality measure
based on equity market
Average over all funds
More proc...
21
Pension Funds’ Measure of Procyclicality
Procyclicality measure
based on equity market
Average over all funds
Evidence ...
22
Results: risky asset allocation
Dependent variable:
Percentage Allocation to
Risky Assets Equities Risky Fixed
Income
A...
23
Results: risky asset allocation (alternatives)
Dependent variable:
Percentage Allocation to
Commo Infra RE PE, VC, LBO ...
24
Results: risky asset allocation (risky fixed income)
s Dependent variable:
Percentage Allocation to
High Yield Mortgage...
25
Regulatory factors have much more economic impact than individual
characteristics, similar to institutional factors
– S...
26
Results: procyclicality (comparison to full rebalancing strategy)
Dependent variable:
,-
Risky Assets Equities Risky Fi...
27
Results: procyclicality (comparison to no-rebalancing strategy)
Dependent variable:
,-^
Risky Assets Equities Risky Fix...
28
We find evidence of procyclicality
– Funds do not set their weights equal to full-rebalancing
– Additional procyclicali...
29
Our objective: quantify the importance of regulatory factors on top of
individual / structural characteristics of the f...
30
We find evidence of some form of procyclicality, more pronounced
during financial crises
Counterintuitively, we do not ...
A joint stock company (Société anonyme) with registered capital of 546,162,915 euros
An investment management company appr...
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Does Regulation Matter? Riskiness and Procyclicality of Pension Asset Allocation - Marie Briere - OECD-Risklab-APG Workshop on pension fund regulation and long-term investment

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This presentation by Marie Briere, Amundi, was made at the OECD-Risklab-APG Workshop on pension fund regulation and long-term investment held in Amsterdam on 7 April 2014. Discussions focused on: long-term pension investment strategies under risk-based regulation; riskiness and procyclicality in pension asset allocation; and, regulatory challenges for long-term illiquid assets.

For more information, please visit:
http://www.oecd.org/daf/fin/private-pensions/OECD-APG-workshop-pension-fund-regulation-LTI.htm

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Does Regulation Matter? Riskiness and Procyclicality of Pension Asset Allocation - Marie Briere - OECD-Risklab-APG Workshop on pension fund regulation and long-term investment

  1. 1. Does Regulation Matter? Riskiness and Procyclicality of Pension Asset Allocation L.N. Boon Amundi, Netspar, Paris Dauphine and Tilburg University M. Brière Amundi, Paris Dauphine University and Université Libre de Bruxelles S. Rigot Université Paris Nord, CEPN OECD–APG Workshop – April 2014 Pension Funds Regulation and Long Term Investment Preliminary – Do not quote
  2. 2. 2 Ongoing debate on pension regulation in Europe: application of a Solvency Framework (EIOPA, 2012) ? Our question: does the type of regulation have an influence on the asset allocation of DB pension funds? – % of risky assets – Procyclicality We attempt to quantify the importance of regulatory factors on top of individual/ structural characteristics US, Canada and the Netherlands are particularly interesting cases : – They underwent notable regulatory changes: Pension Protection Act in 2006 in the US, Financial Assessment Framework in 2007 in the Netherlands – Fund regulation varies across countries and types of funds Motivation
  3. 3. 3 Related Literature: Drivers of pension fund’s allocation Individual characteristics of the funds are a major determinant of the riskiness of pension plan’s asset allocation – Size (Dyck and Pomorski, 2011) – Maturity (Rauh, 2009 ; Bikker, 2011) – Inflation indexation (Sundaresan and Zapatero, 1997; Lucas and Zeldes, 2006) Institutional characteristics of the plan: presence of a guaranteeing mechanism (PBGC in the US, PBGF in Ontario) – This insurance is in effect a put option that reduces the negative impact of pension liabilities on the firm’s value (Sharpe, 1976 ; Treynor, 1977; Nielson and Chan, 2007; Crossley and Jametti, 2013) Regulatory environment – US public funds increased their risky asset allocation to maintain high discount rates and present lower liabilites (Pennachi and Rastad, 2011; Andonov et al. 2013)
  4. 4. 4 Related Literature: Debate on the efficiency of regulation Use of risk models to calibrate solvency buffers – Limit financial insitutions’ ability to take risk (Severinson and Yermo, 2012) – Generate procyclical investment (Bec and Gollier, 2009) – Generate substantial economic costs when repeated short term VaR constraints are imposed on long term investors (Shi and Werker, 2012) Mark-to-market accounting methods – Constitute an additional source of price volatility, especially for long maturity or illiquid assets (Plantin et al., 2008) – Limit investors’ ability to take risk (Severinson and Yermo, 2012) – Generate procyclical investment (Novoa, Scarlata and Solé, 2009) – Generate contagion (Allen and Carletti, 2008)
  5. 5. 5 Empirical investigation of the drivers of pension fund’s asset allocations – Expanding the literature over all regulatory dimensions – Quantifying / comparing the impact of regulation with other explanatory factors Main Findings – Regulatory factors play a strong role in explaining pension fund’s asset allocation choices – They have a much larger economic impact than individual characteristics – Similar in amplitude to institutional factors Our Paper
  6. 6. 6 Regulatory changes induced a significant reduction in risky asset allocation Risk-based capital requirements have the strongest impact – They induce a strong reduction in risky asset weights, especially equities – They have positive impact on alternatives (especially private equity, real estate) and risky fixed income (mainly high yield) The choice of the liabilities discount rate comes as the second largest factor Our Results: Riskiness of asset allocation
  7. 7. 7 We build two original procyclicality measures – Funds are procyclical in the sense that they do not fully rebalance – Strong evidence of additional procyclicality during financial crises (asset weight decrease stronger than implied by asset drift) Little evidence of the impact of regulation on procyclicality – Quantitative investment restrictions reduce procyclicality on the restricted asset classes – Counterintuitively, risk-based regulation induced a slighly lower procyclical behavior – Result driven by the temporary regulatory slackening during the last crisis in the Netherlands Our Results: Procyclicality
  8. 8. 8 Differences in Pension Funds’ Regulatory Environment US public US private Canada public and private Dutch public and private INVESTMENT RESTRICTIONS Quantitative investment restrictions Yes No unified regulation None Prior to 2005: Max 30% on foreign assets 2005-2010: Max 15% on resource property, 25% real estate and Canadian natural resource property. After 2010: None None
  9. 9. 9 Differences in Pension Funds’ Regulatory Environment US public US private Canada public and private Dutch public and private VALUATION REQUIREMENTS : ASSETS Asset valuation GASB 27: Actuarial value Before 2006: ERISA+FAS87 Fair value, discounted cash flow, book value, smoothed value After 2006: PPA +FAS157 Fair value with 24M smoothing (smoothed value bounded between 90%-110% of asset’s current market value) Before 2000: CICA3460 Market value or market related value. After 2000: CICA3461 Fair value or market related value adjusted to moderate its volatility, discounted cash flows, constant yield to maturity for illiquid assets. After 2011: IAS19 Market value Before 2007: PSW Market value After 2005: IAS19 Market value to calculate the unfunded pension liabilities for listed corporate sponsors After 2007: FTK Market value In red: funding regulation In blue: accounting regulation
  10. 10. 10 Differences in Pension Funds’ Regulatory Environment US public US private Canada public and private Dutch public and private VALUATION REQUIREMENTS: LIABILITIES Liability discount rate GASP: Expected return of assets Before 2004: ERISA Corridor around 4Y average of 30Y T-Bond. 2004-06: PFEA Corporate bond market rate, 4Y average. Since 2006: PPA+FAS158 Corporate bond market rate (smoothing for PPA) Before 2000 : CICA3460 Long term expected return of assets (“best estimate”) After 2000: CICA3461 Government bond rate Before2007: PSW Fixed actuarial interest rate with a maximum. Since 2007: FTK Swap rate. Liabilities recognized in sponsor/ gvt balance sheet No Before 2006: FAS87 In footnotes. Since 2006 : FAS158 Yes Private plans: Yes since 2000 (CICA3461) Public plans: Yes with exceptions No
  11. 11. 11 Differences in Pension Funds’ Regulatory Environment US public US private Canada public and private Dutch public and private FUNDING REQUIREMENTS Quantitative risk requirements None None None Since 2007: FTK Yes Fixed minimum funding requirements No min (0%) 1994-2006: Retirement Protection Act 90% Since 2006 : PPA 92% in 2008 94% in 2009 96% in 2010 100% in 2011 100% Before 2007: PSW 100% Since 2007: FTK 105% at confidence level of 97.5% with 1Y horizon. Recovery period None Before 2006: ERISA 30Y Since 2006: PPA 7Y Usually 5Y Federal plans + Alberta and Ontario plans have a max amortization period of 10Y since 2009 Before 2007: PSW 10Y Since 2007: FTK 3 – 15 years depending on continuity analysis
  12. 12. 12 Methodology : Regulatory variables definition Variable Definition Riskiness Procyclicality Investment requirements Quantitative investment restrictions (QIR) Dummy: 1 on the existence of limits on any asset class - - Valuation requirements Asset valuation (Mkt Val) Dummy: 1 if market valuation without discretion, 0 otherwise - + Excess liability discount rate (eLDR) Discount rate level disclosed by the fund minus the fund’s home country government 10Y interest rate + ≈ Liabilities’ recognition in sponsor/ gvt balance sheet (LiabRecog) Dummy: 1 if liabilities are recognized on the sponsor’s (i.e., enterprise or government) balance sheet - + Funding requirements Min funding requirement (Fund Req) Level of funding requirement ≈ + Quantitative risk- based capital requirements (QRR) Dummy: 1 on the existence of mandatory quantitative risk-based capital requirements - + Recovery period (Recov) Average recovery period in years + -
  13. 13. 13 Methodology : Individual and institutional variables definition Variable Definition Riskiness Procyclicality Individual characteristics Maturity (Maturity) Percentage of retired members - ≈ Inflation indexation (InfIndx) Percentage of member’s benefits contractually indexed to inflation + ≈ Size (Size) Market value of Assets Under Management in billions of USD + (for alternatives) ≈ Institutional characteristics Guarantee (Guarantee) Dummy: 1 if pension benefits are collectively insured by a guarantee fund + ≈
  14. 14. 14 Panel regression analysis with the following explanatory variables Methodology InstitutionalFactor FundCharacteristics RegulatoryFactors Quantitative Investment Restriction Excess liability discount rate Mark-to-market asset valuation, min funding requirements and recovery period Liabilities in sponsor’s balance sheet Quantitative risk-based capital requirements Maturity Indexation Size of AUM External guarantee
  15. 15. 15 Allocation to risky assets We estimate the following pooled panel regression model Methodology • is the allocation to risky assets, or its sub-categories: equities, risky fixed income, and alternatives for fund i at time t. • Standard errors are clustered by Year =∝ + 1 + 2 + 3 + 4 + 5 + 6 + 7 "# "$% + 8' ( + 9* " + +
  16. 16. 16 Procyclicality of Equity Investment Definition of the procyclicality measure Methodology ,- (/) = 1 1 0 if sign( - / )=sign( 9 ) otherwise • is the fund i’s allocation to risky assets at time t • @ is a reference weight the fund would have if it were not procyclical • A fund is considered procyclical if it increases its asset allocation to risky assets in response to high performances that year (and the reverse)
  17. 17. 17 Procyclicality of Equity Investment We define two alternative definitions of the reference weight – A full rebalancing strategy: reference weights are considered constant and equal to the fund’s average reported allocation over time – A no-rebalancing strategy: reference weights are defined as the weights that the fund would have if it lets assets drift along with market performance Methodology AB = CD DEFGH IGJKL DEFGH M is the asset drift weight. F NOP is the risky asset return Q is the total return of the fund. RS = 1 T U Q VD
  18. 18. 18 Procyclicality of Equity Investment We estimate the following logit regression model Methodology • ,- @ is the procyclicality indicator for fund i at time t ln X ,Y,- (/) = 1Z 1 − ,Y,- (/) = 1Z =] + 1 + 2 + 3 + 4 + 5 + 6 + 7 "# "$% + 8' ( + 9* " + +
  19. 19. 19 CEM Benchmarking Database – More than 800 DB pension funds – Around 500 in the US, 250 in Canada and 80 in the Netherlands, representing respectively 40%, 90% and 30% of US, Canadian and Dutch DB funds – Yearly asset allocation and performance over 1990-2011 Data
  20. 20. 20 Pension Funds’ Measure of Procyclicality Procyclicality measure based on equity market Average over all funds More procyclicality during periods of expansion US public funds much more procyclical since 2008 Procyclicality Measure (comparison to full rebalancing strategy)
  21. 21. 21 Pension Funds’ Measure of Procyclicality Procyclicality measure based on equity market Average over all funds Evidence of procyclicality during the 2 crises (2001 – 2007) Procyclicality Measure (comparison to no-rebalancing strategy)
  22. 22. 22 Results: risky asset allocation Dependent variable: Percentage Allocation to Risky Assets Equities Risky Fixed Income Alternatives Quantitative Investment Restrictions -0.573 (1.3) 9.490*** (1.470) -2.740*** (1.020) -7.320*** (1.360) Excess Liability Discount Rate 4.670*** (0.673) 3.660*** (0.876) -0.204 (0.253) 1.210* (0.687) Funding, Recovery, Market Valuation -2.420 (1.810) -8.760*** (2.180) 2.400** (1.220) 3.940** (1.880) Liabilities Recognized in Sponsor's Balance Sheet -1.610* (0.832) -2.690** (1.190) -0.153 (0.166) 1.230** (0.499) Quantitative Risk-based Capital Requirements -8.200*** (1.710) -12.700*** (2.750) 0.691 (1.130) 3.810*** (1.290) Maturity -2.480*** (0.414) -3.180*** (0.377) -0.082 (0.062) 0.779*** (0.201) Inflation Indexation 0.648** (0.283) -2.030*** (0.646) -0.068 (0.099) 2.750*** (0.467) Size 2.540*** (0.200) -1.910*** (0.595) 0.305*** (0.094) 4.140*** (0.470) Guarantee 7.330*** (1.240) 11.800*** (2.260) -2.670** (1.200) -1.760 (1.920) Intercept 64.700*** (1.360) 57.900*** (1.260) 1.560*** (0.318) 5.230*** (0.545) 2 0.213 0.182 0.084 0.174 Adjusted- 2 0.211 0.180 0.081 0.172 Nobs. 3932 3932 3932 3932 Significance: *0.1, **0.05,***0.01
  23. 23. 23 Results: risky asset allocation (alternatives) Dependent variable: Percentage Allocation to Commo Infra RE PE, VC, LBO HF Quantitative Investment Restrictions -0.278*** (0.076) -0.263 (0.302) -3.120*** (0.618) -2.210*** (0.319) -2.400*** (0.845) Excess Liability Discount Rate -0.081 (0.051) 0.179** (0.072) -0.351 (0.289) 1.220*** (0.290) 0.591*** (0.203) Funding, Recovery, Market Valuation 0.230** (0.095) 0.684* (0.390) -0.576*** (0.194) 0.777*** (0.282) 1.260*** (0.276) Liabilities Recognized in Sponsor's Balance Sheet 0.045 (0.030) -0.112 (0.081) 1.210* (0.635) 2.140*** (0.539) 2.630** (1.210) Quantitative Risk-based Capital Requirements 1.410*** (0.180) 0.0305 (0.290) 2.850*** (0.537) 7.250*** (0.392) -1.070 (0.869) Maturity 0.0003 (0.024) -0.005 (0.010) 0.235* (0.137) 0.238*** (0.059) 0.088 (0.151) Inflation Indexation 0.090*** (0.023) 0.131*** (0.031) 1.200*** (0.134) 0.778*** (0.233) 0.925*** (0.159) Size 0.098*** (0.038) 0.185*** (0.046) 1.550*** (0.120) 2.420*** (0.268) 0.316*** (0.075) Guarantee -0.193* (0.106) -0.525 (0.364) -2.060*** (0.703) -0.693 (0.490) -1.410 (1.160) Intercept 0.118* (0.063) -0.234*** (0.083) 4.150*** (0.294) -0.309 (0.295) -0.330** (0.147) 2 0.112 0.052 0.168 0.214 0.079 Adjusted- 2 0.110 0.050 0.166 0.212 0.077 Nobs. 3932 3932 3932 3932 3932 Significance: *0.1, **0.05,***0.01
  24. 24. 24 Results: risky asset allocation (risky fixed income) s Dependent variable: Percentage Allocation to High Yield Mortgages Quantitative Investment Restrictions -1.560*** (0.161) -1.180*** (0.134) Excess Liability Discount Rate 0.281*** (0.079) -0.485*** (0.066) Funding, Recovery, Market Valuation 1.140*** (0.206) 1.260*** (0.172) Liabilities Recognized in Sponsor's Balance Sheet 0.154* (0.086) -0.307*** (0.072) Quantitative Risk-based Capital Requirements 0.672** (0.277) 0.019 (0.231) Maturity -0.042 (0.065) -0.0406 (0.054) Inflation Indexation 0.117* (0.070) -0.185*** (0.058) Size 0.174*** (0.065) 0.131** (0.054) Guarantee -1.040*** (0.194) -1.630*** (0.162) Intercept 0.614*** (0.121) 0.950*** (0.101) 2 0.070 0.070 Adjusted- 2 0.068 0.068 Nobs. 3932 3932 Significance: *0.1, **0.05,***0.01
  25. 25. 25 Regulatory factors have much more economic impact than individual characteristics, similar to institutional factors – Significant reduction in risky asset allocation Risk-based capital requirements have the strongest impact – Strong reduction in risky asset weights, especially equities – Positive impact on alternatives (especially private equity, real estate) and risky fixed income (mainly high yield) The choice of the liabilities discount rate comes as the second largest impact Results: risky asset allocation
  26. 26. 26 Results: procyclicality (comparison to full rebalancing strategy) Dependent variable: ,- Risky Assets Equities Risky Fixed Income Alternatives Quantitative Investment Restrictions 0.259 (0.185) 0.990*** (0.309) -2.030** (0.905) -0.857*** (0.277) Excess Liability Discount Rate 0.679*** (0.156) 0.315 (0.208) 0.581 (0.269) 0.256 (0.234) Funding, Recovery, Market Valuation 0.221 (0.293) -0.940** (0.419) 2.310 (1.170) 0.831*** (0.25) Liabilities Recognized in Sponsor's Balance Sheet -0.510** (0.228) -0.533** (0.248) -0.223 (0.215) 0.306* (0.185) Quantitative Risk-based Capital Requirements -0.375 (0.419) 0.167 (0.603) -0.718 (0.976) -0.258 (0.420) Maturity 0.104 (0.086) 0.008 (0.089) 0.072 (0.091) 0.014 (0.066) Inflation Indexation 0.049 (0.109) -0.093 (0.125) 0.211*** (0.085) 0.216 (0.135) Size 0.203 (0.123) -0.001 (0.151) 0.695*** (0.110) 0.238* (0.132) Guarantee 0.021 (0.236) 0.908** (0.393) -1.900 (1.150) -0.731*** (0.278) Intercept -0.486** (0.197) 0.176 (0.254) -2.200 (0.404) -0.819*** (0.192) Pseudo- 2 0.024 0.027 0.074 0.019 Nobs. 3932 3932 3932 3932 Significance: *0.1, **0.05,***0.01 VIII This is 1 − 1 0 , 1 is the log likelihood of the estimated model. 0 is the log likelihood of the null model with only the constant term.
  27. 27. 27 Results: procyclicality (comparison to no-rebalancing strategy) Dependent variable: ,-^ Risky Assets Equities Risky Fixed Income Alternatives Quantitative Investment Restrictions -0.534** (0.269) 1.140** (0.558) -1.640** (0.721) -0.691 (0.468) Excess Liability Discount Rate -0.322 (0.218) -0.310 (0.230) 0.087 (0.290) -0.305** (0.127) Funding, Recovery, Market Valuation 0.484 (0.327) -1.350** (0.534) 1.040 (1.180) 0.164 (0.477) Liabilities Recognized in Sponsor's Balance Sheet 0.190 (0.263) -0.374 (0.348) 0.074 (0.595) 0.375 (0.343) Quantitative Risk-based Capital Requirements -1.030* (0.573) 0.803 (0.597) -0.477 (1.160) -0.575 (0.607) Maturity -0.066 (0.071) -0.195* (0.116) 0.117 (0.121) -0.171 (0.111) Inflation Indexation 0.050 (0.131) -0.042 (0.084) 0.260 (0.173) 0.179 (0.133) Size -0.0217 (0.213) 0.082 (0.089) 0.484*** (0.108) 0.0264 (0.194) Guarantee -0.468* (0.279) 1.500*** (0.541) -0.980 (1.100) -0.493 (0.398) Intercept -0.744* (0.400) 1.450*** (0.373) -2.440*** (0.419) -0.473*** (0.163) Pseudo- 2 0.007 0.025 0.049 0.012 Nobs. 3932 3932 3932 3932 Significance: *0.1, **0.05,***0.01
  28. 28. 28 We find evidence of procyclicality – Funds do not set their weights equal to full-rebalancing – Additional procyclicality during financial crises (asset weight decrease stronger than implied by asset drift) Little evidence of regulatory impact on procyclicality – Except for quantitative investment restrictions Counterintuitively, risk-based regulation induced lower procyclical behavior – Result driven by the temporary regulatory slackening during the last crisis in the Netherlands (extension of recovery period, suspension of pension indexation or reduction in nominal pensions, higher contribution rates allowed, etc.) Results: procyclicality
  29. 29. 29 Our objective: quantify the importance of regulatory factors on top of individual / structural characteristics of the funds Regulation plays a strong role in pension funds’ asset allocation choices, compared to institutional / individual funds’ variables All regulatory measures (asset valuation, funding requirements) and in particular risk-based capital requirements decreased the overall risky asset allocation Strong reduction of equities, but paradoxically risk-based regulations led to an increase in alternatives, especially real estate and private equity Conclusion
  30. 30. 30 We find evidence of some form of procyclicality, more pronounced during financial crises Counterintuitively, we do not find that risk-based regulation induced a more procyclical behavior – Unique to the Netherlands: the DNB authorized numerous waivers to the standing regulation during the Subprime crisis (especially extension of the recovery period) to assist pension funds – This argues for a « dynamic » setting of regulatory rules ? Conclusion
  31. 31. A joint stock company (Société anonyme) with registered capital of 546,162,915 euros An investment management company approved by the French Securities Authority (Autorité des marchés financiers) under no. GP 04000036 Registered office: 90 boulevard Pasteur 75015, RCS Paris no. 437 574 452

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