Institutional Investors: From Myth to Reality · Journal of International Economics. Opazo,...

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

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


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


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



Trading and herding



Diversification

Pro-cyclicality

Benchmark effect


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



Trading and herding



Diversification

Pro-cyclicality

Benchmark effect


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


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


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


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


(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


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


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


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


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


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


Direct Benchmark Effect: Israel’s Upgrade (5/2010)

Capital Flows in Levels: All Types of Funds


-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


-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


-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


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)


Announcement date



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)


First effective date

Second effective date

Third effective date


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!

Institutional Investors: From Myth to Reality · Journal of International Economics. Opazo,...

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