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Institutional Investors:
From Myth to Reality
Policy Research TalkJune 1, 2015
Sergio Schmukler
Development Research Group
Background Work
de la Torre, Ize, and Schmukler (2011). Financial Development in Latin America and the Caribbean: The Road Ahead, World Bank.
Didier, Rigobon, and Schmukler (2013). Unexploited Gains from International Diversification: Patterns of Portfolio Holdings around the World. Review of Economics and Statistics.
Raddatz and Schmukler (2013). Deconstructing Herding: Evidence from Pension Fund Investment Behavior. Journal of Financial Services Research.
Raddatz and Schmukler (2012). On the International Transmission of Shocks: Micro-Evidence from Mutual Fund Portfolios. Journal of International Economics.
Opazo, Raddatz, and Schmukler (2015). Institutional Investors and Long-term Investment: Evidence from Chile. World Bank Economic Review.
Raddatz, Schmukler, and Williams (2015). International Asset Allocations and Capital Flows: The Benchmark Effect. World Bank Policy Research Working Paper No. 6866 and HKIMR Working Paper No.04/2015.
GFDR (2015) on Long-term Finance.
Introduction: Some Myths
Large institutional investors expected to play crucial role, thus they received significant push
Manage long-term retirement (and voluntary) savings
Invest in many companies, including SMEs, and countries
Diversify risk and foster access to finance
Informed investors, able to make independent decisions
Invest long term, including bonds and infrastructure projects
Follow fundamentals
Take advantage of arbitrage opportunities and provide liquidity
Absorb shocks, particularly equity investors
Help stabilize and develop the financial system
Big, but far away from model of capital markets as envisioned
Invest differently than expected, even counter-intuitively
Institutional investors invest in few companies and few countries
Constraints not on lack of available funds: domestic/foreign savers
Many assets available for investment not purchased by investors
They hold large resources/investment in few large, liquid assets
Institutional investors shy away from risk, including good ones
Forego higher risk-adjusted returns
Incentives for asset managers seem to play an important role
Delegated portfolios: trade-off between monitoring & risk taking
Introduction: Some Realities
Hard to have a unified framework to analyze the evidence
Findings from many different sources and papers, using data from Chile, the U.S., and world financial centers
Findings on different aspects of institutional investors’ behavior, in particular their asset allocation
Emphasis on regulated investors (mutual funds & pension funds), for which data could and can be collected
Relative to banks and households, we can observe their portfolios, goals, benchmarks, and injections/redemptions
Different findings point to similar factors, offer food for thought
What to expect of institutional investors
Public policy discussion going forward
Organization of the Evidence
Overview
Size of institutional investors
Pension funds in Chile
Trading and herding
Long-term investors?
International evidence
Diversification
Pro-cyclicality
Benchmark effect
Evidence on Institutional Investors
Overview
Size of institutional investors
Pension funds in Chile
Trading and herding
Long-term investors?
International evidence
Diversification
Pro-cyclicality
Benchmark effect
Evidence on Institutional Investors
Financial Markets Size
Source: Didier, Levine, and Schmukler (2014).
81%
35%
27%
84%
64%
31%
107%
75%
38%
117%
84%
41%
0%
20%
40%
60%
80%
100%
120%
Bank Claims on Private Sector Equity Market Capitalization Bond Market Capitalization
Size
of
Fin
anci
al S
yste
m, %
of
GD
P
1991-1995 1996-2000 2001-2005 2006-2011
Size of Financial System: Developed CountriesMedian Country
Financial Markets Size
Source: Didier, Levine, and Schmukler (2014).
Size of Financial System: Emerging CountriesMedian Country
28%
17%
2%
30%27%
5%
25%
37%
9%
36%
59%
14%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Bank Claims on Private Sector Equity Market Capitalization Bond Market Capitalization
Size
of
Fin
anci
al S
yste
m, %
of
GD
P
1991-1995 1996-2000 2001-2005 2006-2011
Assets under Management by Institutional Investors
Growing Size of Institutional Investors
Source: OECD. Only OECD countries included.
0
10
20
30
40
50
60
70
80
90
100
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
No
n-b
ank
Ass
ets,
Tri
llio
ns
of
USD
No
n-b
ank
Ass
ets,
% o
f G
DP
Pension Funds Insurance Companies Investment Funds Assets, Total (RHS)
Institutional Investors vs Banks
Growing Size of Institutional Investors
Source: OECD. Only OECD countries included. Given data constraints, the figure does not include the following OECD countries: Czech Republic, Greece, Hungary, Portugal, Slovenia, Turkey, and United Kingdom.
0
10
20
30
40
50
60
70
80
2001 2002 2003 2004 2005 2006 2007 2008
Tota
l Ass
ets,
Tri
llio
ns
of
USD
Non-bank Institutional Investors' Assets Banks' Assets
Growing Size of Institutional Investors
Source: OECD.
92%
76%
252%
100%
80%
182%
95% 92%
254%
113%
93%
200%
97%
117%
219%
0%
50%
100%
150%
200%
250%
300%
Banks Non-banks Banks Non-banks Banks Non-banks
Chile . Germany . United States
Tota
l Ass
ets,
% o
f G
DP
1999-2003 2004-2009 2010-2012
Institutional Investor vs Bank, Assets
Overview
Size of institutional investors
Pension funds in Chile
Trading and herding
Long-term investors?
International evidence
Diversification
Pro-cyclicality
Benchmark effect
Evidence on Institutional Investors
Is Chile Different?
Yes, but for the good reasons
Innovative in macro and institutional policy, plus development of institutional investors – benchmark case
Has long history, rich data, and good collaboration with the Bank
Can compare different institutional investors within same framework
No, because many countries have followed it and patterns present several similarities
Chile has been a model for many countries in pension fund reform
Regulations have improved and cannot be much different in other countries
When managers need monitoring, incentives play similar role
Defined contribution systems are expanding, similar to Chile
Defined Contribution Pension Funds Important
Source: OECD. Selected OECD countries in 2013.
0% 20% 40% 60% 80% 100%
SwitzerlandGermany
FinlandCanada
PortugalLuxembourg
KoreaIsrael
TurkeyUnited States
SpainIceland
New ZealandMexico
AustraliaItaly
DenmarkSlovenia
Slovak RepublicPoland
HungaryGreeceFrance
EstoniaCzech Republic
Chile
Share of Total Assets
Defined Benefit / Hybrid-Mixed
Defined Contribution
Share of Defined Contribution Assets, by Country
Pension Funds Trade Infrequently
Note: Data from 2002-2005. Source: Raddatz and Schmukler (2013).
Fixed-income Instruments Bought Initially and Held Until Expiration
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Corporate Bonds Financial InstitutionBonds
Government Bonds Mortage Bonds
Rat
io
Ratio of Units at First Purchase to Maximum Units in Portfolio
Ratio of Units at Expiration to Maximum Units in Portfolio
Note: Data from 2002-2005. The percentage of assets traded is calculated on a monthly basis. Source: Raddatz and Schmukler (2013).
Herding within Fund Types Across PFAs, by Fund Type
(1) (2) (3) (4) (5)
All Asset Classes 5.87 *** 3.54 *** 7.99 *** 5.65 *** 4.67 ***
(0.92) (0.65) (0.49) (0.66) (0.84)
Domestic Assets
Corporate Bonds 13.61 *** 11.47 *** 20.80 *** 10.51 *** 13.02 ***
(1.93) (0.85) (0.08) (0.88) (1.06)
Financial-Institution Bonds 6.63 *** 10.78 *** 15.33 *** 9.49 *** 13.56 ***
(2.61) (1.29) (1.21) (1.25) (1.70)
Government Bonds 1.21 4.91 *** 2.96 *** 4.94 *** 2.08 ***
(1.72) (0.84) (0.44) (0.67) (0.80)
Mortgage Bonds 5.02 *** 2.89 *** 1.24 *** 2.52 *** 3.26 ***
(0.85) (0.17) (0.08) (0.14) (0.32)
Equity 6.32 *** 0.69 * 10.43 *** 6.68 *** -
(0.43) (0.45) (0.60) (0.64) -
Herding Statistic
Fund D Fund EFund A Fund B Fund C
When They Trade, They Do It Similarly: Herding
Along with MFs, They Tend to Invest Short Term
Maturity Structure of Chilean Domestic Mutual Funds and PFAsvs. Insurance Companies
Note: This figure compares the maturity structure of Chilean insurance companies to that of Chilean domestic mutual funds and PFAs. Only medium- and long-term bond mutual funds are taken into account. Sample period: 2002-08. Source: Opazo, Raddatz, and Schmukler (2015).
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3 4 5 6 7 8 9 10
Po
rtfo
lio S
har
e
Years to Maturity
Chilean Domestic Mutual Funds
Chilean PFAs
Chilean Insurance Companies
Along with MFs, They Tend to Invest Short Term
Note: Only medium- and long-term bond mutual funds are taken into account. Sample period: 2002-08. Source: Opazo, Raddatz, and Schmukler (2015).
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
<1y 1-3y 3-5y 5-7y 7-10y 10-15y 15-20y 20-30y
Po
rtfo
lio S
har
e
Years to MaturityChilean Insurance Companies Chilean Domestic Mutual Funds Chilean PFAs
Maturity Structure of Chilean Domestic Mutual Funds and PFAsvs. Insurance Companies
Avg. Maturity
Insurance Companies 9.77
Domestic Mutual Funds 3.97
Pension Funds 4.36
Pension Funds Not Exposed to Large Net Outflows
Net Inflows to Chilean MFs, PFAs, and US MFs
Note: Sample period: 2005-05. Source: Opazo, Raddatz, and Schmukler (2015).
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
-5% -4% -3% -2% -1% 0% 1% 2% 3% 4% 5%
Cu
mu
lati
ve P
rob
abili
ty
Net Inflows as a Fraction of Fixed-term Assets
US Multi-Sector Mutual Funds Chilean Domestic Mutual Funds Chilean PFAs
Insurance Companies Bid More for Longer Bonds
Source: Opazo, Raddatz, and Schmukler (2015).
Ratio between Insurance Companies and Pension Funds
(i) (ii)
Ratio between Shares Requested
Time to Maturity (Years)
Indexed Pesos Indexed Pesos, Pesos, and US
Dollars, Controlling by Currency
Coef. Std. Error Coef. Std. Error
1 0.105 (0.082)
2 0.168 (0.145) 0.053 (0.076)
5 0.218 (0.115) 0.184 (0.098)
10 0.119 (0.044) 0.167 (0.044)
20 0.609 (0.113) 0.609 (0.112)
30 3.473 (1.701) 3.473 (1.701)
No. of Observations 418 666
Bids by Pension Funds and Insurance Companies in Government Bond Auctions
Even When Investing Long Term Pays Off
Sharpe Ratio
Indices of Chilean Government Inflation-Indexed Bonds
Note: Sample period: 2002-07. Source: Opazo, Raddatz, and Schmukler (2015).
0%
2%
4%
6%
8%
10%
12%
14%
1 2 3 4 5 6 7 8 9 10 11
An
nu
aliz
ed R
etu
rn
Years to Maturity
0
0.5
1
1.5
2
2.5
1 2 3 4 5 6 7 8 9 10 11
Shar
pe
Rat
io
Years to Maturity
Return
Composition of Pension Fund Investments in Latin America
Portfolios Tilted toward Deposits and Public Bonds
Source: OECD, ABRAPP, AIOSFP, FIAP, and local sources.
64%59%
30%
13%
49% 47%
88%
73%
14%21%
61% 59%
9%
3%
32%
29%
17%
9%
3%
5%
29%11%
34% 36%2%
2% 6%
8%
20%
11%
9%
11%
15%
12%
3% 2%
6%
9%
17%
32%
7%
10%
8%
6%
11%
12%
14%
12% 15%
6%
17%
3%
33%
36%
5%11%
3% 3% 2%2%
1%2%
2% 2% 3% 2%6%
1% 2%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
19
99
-4
20
05
-8
19
99
-4
20
05
-8
19
99
-4
20
05
-8
19
99
-4
20
05
-8
19
99
-4
20
05
-8
19
99
-4
20
05
-8
Argentina Chile Colombia Mexico Peru Uruguay
% o
f To
tal
Po
rtfo
lio
Govt. Securities Fin. Inst. Sec/Deposits Private Bonds Foreign Securities
Equities Mutual Funds Other Investments
Mutual Funds - Portfolio HoldingsChile
Mutual Funds Also in Deposits and Public Bonds
Source: IMF’s IFS, FGV-Rio, Conasev, Superfinanciera, Andimia, and Banxico.
63% 63%
17% 13%
4% 9%2%
8%14%
6%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2000-4 2005-9
% o
f T
ota
l A
sse
ts
Deposits Private Bonds Domestic Equity Foreign Equity Public Bonds
Overview
Size of institutional investors
Pension funds in Chile
Trading and herding
Long-term investors?
International evidence
Diversification
Pro-cyclicality
Benchmark effect
Evidence on Institutional Investors
Similar Number of Holdings Across Fund Types
Source: Didier, Rigobon, and Schmukler (2013).
0
20
40
60
80
100
120
140
160
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Med
ian
Nu
mb
er o
f St
ock
Ho
ldin
gs
World Funds
World Funds - Excluding U.S. Holdings
Foreign Funds
Emerging Market Funds
Regional Funds
Median Number of Stocks Held by Mutual Funds
Similar Number of Holdings Across Fund Types
Source: Didier, Rigobon, and Schmukler (2013).
0
20
40
60
80
100
120
140
160
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Med
ian
Nu
mb
er o
f St
ock
Ho
ldin
gs
Asia Funds Europe Funds Latin America Funds Country Funds
Median Number of Stocks Held by Mutual Funds
Changes Within Families
Source: Didier, Rigobon, and Schmukler (2013).
Fund Type Asia Developed Europe Latin America
Regional Funds
Median Number of Countries 8 12 6
Emerging Market Funds -10% - -17%
Foreign Funds -30% 0% -72%
World Funds -36% -14% -75%
(In Percent, Relative to Regional Funds)
Number of Countries
Drop in the Number of Countries in Each Region by Fund Type
Mutual Funds Hold Relatively Few Stocks
Note: The sample period is 1997-2004. Source: Didier, Rigobon, and Schmukler (2013).
Mutual Fund Holdings as a Proportion of the Total Number of Listed Stocks
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Nig
eri
aSa
ud
i Ara
bia
Ro
man
iaLi
thu
ania
Latv
iaSl
ova
k R
epu
blic
Ban
glad
esh
Bu
lgar
iaTu
nis
iaIc
ela
nd
Om
anJo
rdan
Cyp
rus
Pak
ista
nEg
ypt
Ind
iaC
roat
iaU
rugu
aySl
ove
nia
Ecu
ado
rSr
i Lan
kaP
eru
Co
lom
bia
Kaz
akh
stan
Esto
nia
Zim
bab
we
Ch
ileC
zech
Rep
ub
licSp
ain
Isra
elP
anam
aV
en
ezu
ela
Mo
rocc
oK
en
yaB
ots
wan
aSo
uth
Afr
ica
Leb
ano
nB
razi
lP
ola
nd
Can
ada
Ph
ilip
pin
esR
uss
iaA
ll C
hin
a*A
ust
ralia
Ind
on
esi
aM
auri
tiu
sTu
rke
yTh
aila
nd
Mal
aysi
aG
ree
ceSo
uth
Ko
rea
Po
rtu
gal
Gh
ana
Arg
en
tin
aG
erm
any
Hu
nga
ryM
exi
coN
orw
ayFr
ance
Un
ite
d K
ingd
om
Au
stri
aSi
nga
po
reD
en
mar
kB
elg
ium
New
Zea
lan
dFi
nla
nd
Swit
zerl
and
Swed
en
Jap
anIt
aly
Ire
lan
dN
eth
erla
nd
s
Nu
mb
er o
f M
utu
al F
un
d H
old
ings
/Lis
ted
Sto
cks
Having Managers in Common Increases Entropy
Source: Didier, Rigobon, and Schmukler (2013).
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
1997 1998 1999 2000 2001 2002 2003 2004 2005
Entr
op
y
All funds No Common Manager
At least 1 Common Manager More than 3 Common Managers
Entropy Measure by Number of Common Managers
Family Effects Are Relevant
Source: Didier, Rigobon, and Schmukler (2013).
(1) (2) (3) (4) (5)
Adjusted R-squared 0.01 0.42 0.42 0.44 0.44
Independent Variables
Year Dummies Yes No Yes No Yes
Fund Type Dummies No No No Yes Yes
Family Dummies No Yes Yes Yes Yes
No. of Observations 6,394 6,394 6,394 6,394 6,394
(1) (2) (3) (4) (5)
Adjusted R-squared 0.01 0.32 0.33 0.39 0.40
Independent Variables
Year Dummies Yes No Yes No Yes
Fund Type Dummies No No No Yes Yes
Family Dummies No Yes Yes Yes Yes
No. of Observations 6,379 6,379 6,379 6,379 6,379
Number of Stock Holdings
% of Net Assets in Top Ten Holdings
Holding Patterns Are Costly
Source: Didier, Rigobon, and Schmukler (2013).
Type of Global Funds
Global
Funds
Simulated
Global Funds
Global
Funds
Simulated
Global Funds
Number of
Comparisons
Daily Data
World Funds 6.22% 11.01% 4.85% 0.87% 0.78% 63
Foreign Funds 6.03% 9.95% 4.03% 0.97% 0.89% 77
Pools of World or Foreign Funds 10.53% 15.23% 4.55% 0.86% 0.80% 25
Total 6.78% 11.14% 4.42% 0.92% 0.84% 165
Weekly Data
World Funds 6.28% 11.33% 5.08% 2.05% 1.92% 63
Foreign Funds 6.04% 9.70% 3.74% 2.25% 2.13% 77
Pools of World or Foreign Funds 10.54% 15.16% 4.44% 1.99% 1.90% 25
Total 6.80% 11.13% 4.36% 2.14% 2.01% 165
Average Returns
(Per Year)Average
Difference in
Accumulated
Returns
Minimizing the Variance
Standard Deviation of
Returns
Volatile Total Assets in Global Equity Funds
1996-2000 2001-2010
0
10
20
30
40
50
60
70
80
90
Jan
. 96
Jul.
96
Jan
. 97
Jul.
97
Jan
. 98
Jul.
98
Jan
. 99
Jul.
99
Jan
. 00
Jul.
00
Tota
l Ass
ets,
Bill
ion
so
f U
SD
0
100
200
300
400
500
600
700
800
Jun
. 01
Jun
. 02
Jun
. 03
Jun
. 04
Jun
. 05
Jun
. 06
Jun
. 07
Jun
. 08
Jun
. 09
Jun
. 10
Tota
l Ass
ets,
Bill
ion
so
f U
SD
Source: Raddatz and Schmukler (2012).
Volatile Portfolios
Global Equity Funds
Average portfolio shares
40%
42%
44%
46%
48%
50%
52%
54%
56%
Jan
. 07
May
. 07
Sep
. 07
Jan
. 08
May
. 08
Sep
. 08
Jan
. 09
May
. 09
Sep
. 09
Po
rtfo
lio S
har
e
Developed Europe
Northern Rock
Bear Stearns
Lehman Brothers AIG
7%
8%
9%
10%
11%
12%
13%
14%
15%
Jan
. 07
May
. 07
Sep
. 07
Jan
. 08
May
. 08
Sep
. 08
Jan
. 09
May
. 09
Sep
. 09
Po
rtfo
lio S
har
e
Emerging Countries
16%
17%
18%
19%
20%
21%
22%
Jan
. 07
May
. 07
Sep
. 07
Jan
. 08
May
. 08
Sep
. 08
Jan
. 09
May
. 09
Sep
. 09
Po
rtfo
lio S
har
e
North America
Source: Raddatz and Schmukler (2012).
Volatile Portfolios
Global Bond Funds
Average portfolio shares
0%
10%
20%
30%
40%
50%
60%
Jan
. 07
May
. 07
Sep
. 07
Jan
. 08
May
. 08
Sep
. 08
Jan
. 09
May
. 09
Sep
. 09
Po
rtfo
lio S
har
e
Developed Europe
Northern Rock
Bear Stearns
Lehman Brothers AIG
10%
15%
20%
25%
30%
Jan
. 07
May
. 07
Sep
. 07
Jan
. 08
May
. 08
Sep
. 08
Jan
. 09
May
. 09
Sep
. 09
Po
rtfo
lio S
har
e
Emerging Countries
0%
5%
10%
15%
20%
25%
30%
Jan
. 07
May
. 07
Sep
. 07
Jan
. 08
May
. 08
Sep
. 08
Jan
. 09
May
. 09
Sep
. 09
Po
rtfo
lio S
har
e
North America
Source: Raddatz and Schmukler (2012).
Growing Number of Funds Follow Benchmarks
%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%1
99
6
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
Shar
e o
f TN
As
Explicit Indexing Closet Indexing Mildly Active Truly Active
Equity Funds
Source: Raddatz, Schmukler, and Williams (2015).
Motivation: Israel upgrade from EM to DM
%
1%
2%
3%
4%
5%
Jan
-09
May
-09
Sep
-09
Jan
-10
May
-10
Sep
-10
Jan
-11
May
-11
Sep
-11
Co
un
try
Wei
ght
Global Emerging Funds and MSCI Emerging Markets Index
Announcement
Date
Effective Date
0.0%
0.1%
0.2%
0.3%
0.4%
0.5%
0.6%
Jan
-09
May
-09
Sep
-09
Jan
-10
May
-10
Sep
-10
Jan
-11
May
-11
Sep
-11
Global Funds and MSCI World Index
Explicit Indexing Funds
Truly Active Funds
%
1%
2%
3%
4%
5%
Jan
-09
May
-09
Sep
-09
Jan
-10
May
-10
Sep
-10
Jan
-11
May
-11
Sep
-11
Co
un
try
Wei
ght
Global Emerging Funds and MSCI Emerging Markets Index
0.0%
0.1%
0.2%
0.3%
0.4%
0.5%
0.6%
Jan
-09
May
-09
Sep
-09
Jan
-10
May
-10
Sep
-10
Jan
-11
May
-11
Sep
-11
Global Funds and MSCI World Index
Average Mutual Fund Weight Benchmark Weight
Source: Raddatz, Schmukler, and Williams (2015).
Benchmarks Help with Identification
Benchmarks important beyond country-time (fundamentals)
and industry-time effects
Changes in benchmark weights relate to relative returns
𝑤𝑐𝑡𝐵 = 𝑤𝑐𝑡−1
𝐵 (𝑅𝑐𝑡/𝑅𝑡𝐵)
𝐵𝑢𝑦 𝑎𝑛𝑑 𝐻𝑜𝑙𝑑
+ 𝐸𝑐𝑡𝐵
"𝐸𝑥𝑜𝑔𝑒𝑛𝑜𝑢𝑠"
Weights can move in opposite directions in different
benchmarks (same country, same time)
Exogenous shocks that shed light on identification
Source: Raddatz and Schmukler (2012)Source: Raddatz, Schmukler, and Williams (2015).
Mutual Fund Weights vs. Benchmark Weights𝑤𝑖𝑐𝑡 − 𝑤𝑐𝑡vs. 𝑤𝑖𝑐𝑡
𝐵 − 𝑤𝑐𝑡𝐵
Explicit Indexing Closet Indexing
Mildly Active Truly Active
Source: Raddatz, Schmukler, and Williams (2015).
Effects on Capital Flows
Benchmark weights and capital flows linked through identity
𝐹𝑖𝑐𝑡 = 𝑤𝑖𝑐𝑡𝐹𝑖𝑡
Net Inflows
+ 𝐴𝑖𝑡 𝑤𝑖𝑐𝑡 − 𝑤𝑖𝑐𝑡𝐵𝐻
Reallocation
Direct benchmark effect
Sensitivity effect
Amplification effect
Contagion effect
Source: Raddatz and Schmukler (2012)Source: Raddatz, Schmukler, and Williams (2015).
Direct Benchmark Effect: Israel’s Upgrade (5/2010)
Capital Flows in Levels: All Types of Funds
Source: Raddatz and Schmukler (2012)Source: Raddatz, Schmukler, and Williams (2015).
-2,073
159
-1,913
-2,500
-2,000
-1,500
-1,000
-500
0
500
Emerging Markets Funds Developed Markets Funds Total Country Flows
Cap
ital
Flo
ws,
Mill
ion
s o
f U
SD
Direct Benchmark Effect in Israel’s BoP
Source: Raddatz and Schmukler (2012)Source: Raddatz, Schmukler, and Williams (2015).
-3,000
-2,000
-1,000
0
1,000
2,000
3,000
4,000
5,000
Bo
P, M
illio
ns
of
USD
Portfolio Equity Inflows Portfolio Debt Inflows
Announcementdate
Effectivedate
Direct Benchmark Effect in Colombian TES bonds
Source: Raddatz, Schmukler, and Williams (2015).
-500
0
500
1,000
1,500
2,000
2,500
%
2%
4%
6%
8%
10%
12%
14%
16%
Feb
20
10
Ap
r 2
01
0
Jun
20
10
Au
g 2
01
0
Oct
20
10
De
c 2
01
0
Feb
20
11
Ap
r 2
01
1
Jun
20
11
Au
g 2
01
1
Oct
20
11
De
c 2
01
1
Feb
20
12
Ap
r 2
01
2
Jun
20
12
Au
g 2
01
2
Oct
20
12
De
c 2
01
2
Feb
20
13
Ap
r 2
01
3
Jun
20
13
Au
g 2
01
3
Oct
20
13
De
c 2
01
3
Feb
20
14
Ap
r 2
01
4
Jun
20
14
Au
g 2
01
4
Oct
20
14
Pu
rch
ases
by
Fore
ign
Inve
sto
rs,
Mill
ion
s o
f U
SD
Shar
e H
eld
by
Fore
ign
Inve
sto
rs
Total Purchases of TES by Foreigners (RHS) Percentage Holdings of TES by Foreigners
J.P. Morgan weight increase
Participation of Foreigners in TES bonds
Amplification and Sensitivity Effect
Source: Raddatz and Schmukler (2012)Source: Raddatz, Schmukler, and Williams (2015). The pre-crisis period is May 2003 – May 2004. The crisis and post-crisis period are Sep. 2010 – Sep. 2011.
MSCI Emerging Markets Index ETF
143.5
96.3
7%
5%
%
1%
2%
3%
4%
5%
6%
7%
8%
0
20
40
60
80
100
120
140
160
China Russia
Flo
ws,
Mill
ion
s o
f U
SD
Pre-Crisis Period
-1,352.3
-537.3
17%
6%
-20%
-15%
-10%
-5%
%
5%
10%
15%
20%
-1,800
-1,200
-600
0
600
1,200
1,800
China Russia
Ben
chm
ark
We
igh
t
Global Financial Crisis and Post-Crisis Period
Country Flows (LHS)
Benchmark Weight (RHS)
Price Effects: Israel's Upgrade and Stock Returns
Source: Raddatz and Schmukler (2012)Note: Index returns is a market capitalization price index of firms covered by MSCI. Non Index returns is a market capitalization price index of firms not covered byMSCI. Source: Raddatz, Schmukler, and Williams (2015).
Stock Market Prices of Israeli Firms Around Israel's Upgrade
96
97
98
99
100
101
102
103
Jun
e 2
, 20
09
Jun
e 4
, 20
09
Jun
e 8
, 20
09
Jun
e 1
0, 2
009
Jun
e 1
2, 2
009
Jun
e 1
6, 2
009
Jun
e 1
8, 2
009
Jun
e 2
2, 2
009
Jun
e 2
4, 2
009
Jun
e 2
6, 2
009
Jun
e 3
0, 2
009
Ind
ex (
Jun
16
, 20
09
=10
0) Announcement date
85
87
89
91
93
95
97
99
101
103
105
May
10,
20
10
May
12
, 20
10
May
14
, 20
10
May
18
, 20
10
May
20
, 20
10
May
24,
20
10
May
26
, 20
10
May
28
, 20
10
Jun
e 1
, 20
10
Jun
e 3
, 20
10
Jun
e 7
, 20
10
Jun
e 9
, 20
10
Jun
e 1
1, 2
010
Jun
e 1
5, 2
010
Jun
e 1
7, 2
010
Jun
e 2
1, 2
01
0
Jun
e 2
3, 2
010
Jun
e 2
5, 2
010
Ind
ex (
May
14
, 20
10
=1
00
)
Two weeks prior
effective dateEffective
date
Price Effects: Direct Benchmark Effect – Argentina
Source: Raddatz and Schmukler (2012)Note: The figure illustrates the log difference between stock price of firms entering Argentina's MSCI index (ADRs) and the stock price of firms going out of theindex. Source: Raddatz, Schmukler, and Williams (2015).
-10%
-5%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Jan
01
, 200
9
Jan
21
, 200
9
Feb
10
, 200
9
Mar
02
, 20
09
Mar
20
, 20
09
Ap
r 0
9, 2
009
Ap
r 2
9, 2
009
May
19
, 20
09
Jun
08
, 20
09
Jun
26
, 20
09
AD
R P
rem
ium
Effective date
Announcement date
Two weeks prior effective date
Argentina's Equity Market Around MSCI's Downgrade
Price Effects: Direct Benchmark Effect – Colombia
Source: Raddatz and Schmukler (2012)Note: Index returns is a local currency debt index (in USD) containing all bonds entering the benchmark and non index returns is a local currency debt index (inUSD) from bonds not affected by the benchmark change. Source: Raddatz, Schmukler, and Williams (2015).
98
99
100
101
102
103
104
105
106
Jan
16
, 201
4
Jan
30
, 201
4
Feb
13
, 201
4
Feb
27
, 201
4
Mar
13
, 20
14
Mar
27
, 201
4
Ap
r 1
0, 2
014
Ap
r 2
4, 2
014
May
08,
20
14
May
22,
20
14
Jun
05,
20
14
Jun
19,
20
14
Jul 0
3, 2
01
4
Jul 1
7, 2
014
Jul 3
1, 2
014
Au
g 1
4, 2
014
Au
g 2
8, 2
014
Sep
11
, 201
4
Sep
25
, 201
4
Oct
09
, 201
4
Ind
ex (
Mar
19
, 20
14
=10
0)
Index Returns Non Index Returns
Announcement date Completion
date
Colombia's Sovereign Debt Market Around J.P. Morgan's Upgrade
Price Effects: Contagion in Frontier Markets
Announcement Date
94
96
98
100
102
104
106
108
MSCI Frontier Markets Index (exc. Qatar and UAE) MSCI Emerging Markets Index MSCI World Index
Source: Raddatz and Schmukler (2012)Source: Raddatz, Schmukler, and Williams (2015).
Impact on Frontier Countries Due to the MSCI Upgrade of Qatar and UAE
Price Effects: Contagion in Frontier Markets
Source: Raddatz and Schmukler (2012)Source: Raddatz, Schmukler, and Williams (2015).
Impact on Frontier Countries Due to the MSCI Upgrade of Qatar and UAE
98
99
100
101
102
103
104
Mar
ch 1
3, 2
014
Mar
ch 1
4, 2
014
Mar
ch 1
7, 2
014
Mar
ch 1
8, 2
014
Mar
ch 1
9, 2
014
Mar
ch 2
0, 2
014
Mar
ch 2
1, 2
014
Mar
ch 2
4, 2
014
Mar
ch 2
5, 2
014
Mar
ch 2
6, 2
014
Mar
ch 2
7, 2
014
Mar
ch 2
8, 2
014
Mar
ch 3
1, 2
014
Ap
ril 1
, 20
14
Ap
ril 2
, 20
14
Ap
ril 3
, 20
14
Ap
ril 4
, 20
14
Ap
ril 7
, 20
14
Ap
ril 8
, 20
14
Ap
ril 9
, 20
14
Ap
ril 1
0, 2
01
4
Ap
ril 1
1, 2
01
4
Ap
ril 1
4, 2
01
4
Ap
ril 1
5, 2
01
4
Ap
ril 1
6, 2
01
4
Ap
ril 1
7, 2
01
4
Ind
ex (
Mar
31
, 20
14
=10
0)
Index Returns Non Index Returns
Announcement date
Price Effects: Contagion in Frontier Markets
Source: Raddatz and Schmukler (2012)Source: Raddatz, Schmukler, and Williams (2015).
96
97
98
99
100
101
102
103
104
105
May
19,
20
14M
ay 2
1, 2
014
May
23,
20
14M
ay 2
7, 2
014
May
29,
20
14Ju
ne
2, 2
014
Jun
e 4
, 20
14Ju
ne
6, 2
014
Jun
e 1
0, 2
014
Jun
e 1
2, 2
014
Jun
e 1
6, 2
014
Jun
e 1
8, 2
014
Jun
e 2
0, 2
014
Jun
e 2
4, 2
014
Jun
e 2
6, 2
014
Jun
e 3
0, 2
014
July
2, 2
014
July
4, 2
014
July
8, 2
01
4Ju
ly 1
0, 2
014
July
14
, 201
4Ju
ly 1
6, 2
014
July
18
, 201
4Ju
ly 2
2, 2
014
July
24
, 201
4Ju
ly 2
8, 2
014
July
30
, 201
4A
ugu
st 1
, 20
14A
ugu
st 5
, 20
14A
ugu
st 7
, 20
14
Ind
ex (
May
28
, 20
14
=10
0)
Index Returns Non Index Returns
First effective date
Second effective date
Third effective date
Impact on Frontier Countries Due to the MSCI Upgrade of Qatar and UAE
Constraints not on the supply side of funds
Constraints not on the availability of investable assets
Constraints likely not on specific regulatory issues
These get much attention at country level, but this is a cross-country issue
Financial intermediation process more difficult than thought
Governments and large firms receive most of the financing
Incentives and organizational issues seem to play crucial role and restrict (good) risk taking options
Might not yield socially optimal outcome
Financial intermediaries brain of the economy …
… but work differently than expected
Concluding Remarks: Bottom Line
Some General Policy Challenges
Generate healthy competition among financial intermediaries and market discipline, consistent with intended goals
Reduce fees and foster benchmarking without boosting short-termism, herding, coordination effects, pro-cyclicality, volatility
Foster long-term risk taking while being able to monitor managers
Generate contrarian behavior and long-term arbitrage opportunities without backlash due to negative outcomes
Take advantage of useful international diversification
Think of alternative ways of managing retirement assets
How will the change come about?
Regulators in tight spot
Regulatory incentives to minimize risk relative to benchmark
Having similar portfolios minimizes that risk (herding type of behavior)
Difficult to come up with very different regulatory structure
Why is the industry tilted toward low (idiosyncratic) risk with short maturity, as one example of low risk taking?
Some factors have pushed equilibrium to short term, kept it there
Equilibria can be quite persistent, displaying hysteresis
Can long-term benchmarks shift portfolios to the long term?
Pension and Mutual Funds: Incentives
Investor side – Market discipline
Outflows (or the threat of) / redemptions
Based on short-term returns
Outflows potentially more important for MFs – systemic
Pay structure (tracking error)
Tracking error investment model (tracking the mean)?
Asset return volatility
Incentives to produce stable returns in the short run
Link to “liability structure”
Loss aversion by underlying investors?
Cost of information acquisition?
Focus on low information intensity assets
Pension and Mutual Funds: Incentives
Patterns not exclusive of developing countries
Unexpected patterns even in U.S. and develop countries
Invest in few stocks
Do not share information within companies
Are pro-cyclical even when investing in equities and even when shocks have already hit them
Are subject to significant redemptions from investors
Follow benchmarks and behave passively, which can add to pro-cyclicality through coordination effects
Organizational factors seem key to understand behavior
However and unfortunately, not clear alternative model
Features Not Country Specific
Benchmarks
What determines the intensive and extensive margins?
Effects on cost of capital to corporations and corporate financing
Effects on domestic institutional investors
Active management
What determines deviations from the benchmarks?
Are there arbitrage/investment opportunities?
Asset managers and financial stability (BIS, FSB, IMF)
How do funds manage their liquidity?
To what extent do asset managers generate pro-cyclicality in capital
flows and investments?
Directions for Future Work
Prospects for financial development
Experiences with long-term and illiquid financing
Infrastructure finance and SME finance by institutional investors?
Different models of institutional investors?
Different results?
Domestic investors vs. foreign investors in long-term finance
Others institutional investors (SWF, PE, VC, HF)
Government role
Role of public sector in managing/regulating retirement savings
Scope for new regulation and tradeoffs
Institutional investors and big data
Directions for Future Work
Thank you!