On the International Transmission of Shocks:
Micro-Evidence from Mutual Fund Portfolios
Claudio Raddatz
Sergio Schmukler
Central Bank of Chile
The World Bank
Debt and Credit, Growth and Crises
Banco de España-World Bank Conference
June 18 & 19, 2012
I. Motivation
 Volatile capital flows, intermediated by financial intermediaries (FI)
 Need to understand FI and the micro aspects of their behavior
 In particular, do FI make capital flows more volatile and pro-cyclical?
 Ex-ante risk taking behavior that generate crises
 Ex-post propagation of shocks across markets and countries (Q and P)
 Intermediaries face principal agent problems that affect allocations
 [Underlying Investors  FI Agents (Managers)]  Assets
 Limited evidence on inner-workings of FI at international level
 Aggregate investments x-countries, by foreign & domestic agents, and
certain intermediaries (mostly banks)
I. Motivation: This Paper
How do underlying investors and managers behave, react to
shocks, and contribute to transmit crises across countries?
 Focus on international mutual funds
 Increasingly important drivers of capital flows
 Detailed micro-level portfolio data
 More than 1,000 equity and bond funds, monthly, starting 1996
 Disentangle the behavior of
 Underlying investors (UI) by measuring injections/redemptions
 Managers (M) by changes in country-portfolio weights and cash
I. Motivation: This Paper
Allocations /
Net Inflows
Underlying
investors
Managers
Injections /
Redemptions
Country
1
Country
i
Country
N
Cash
I. Motivation: Specific questions
 What is the contribution of injections to changes in MF investment?
 Do managers significantly change country-portfolio weights over time?
 What are the determinants of investor’s injections and manager’s
portfolio allocations?
 How do injections and allocations respond to crises?
 At the country level, how much of the volatility of capital flows is
driven by fund managers versus investors?
 Are there differences between bond and equity funds?
Presentation
I.
Motivation
II.
Data and Summary Statistics
III.
Shocks to Managers and Portfolio Reallocations
IV.
Behavior of Investors and Managers
V.
Gross and Net Country Flows
VI.
Conclusions
II. Data: Micro-level Dataset on Mutual Funds: (EPFR )
 Data coverage (monthly frequency)
 1,076 funds: global and EM funds
 965 equity funds: Jan 1996-Nov 2010
 111 bond funds: Jul 2002-Nov 2010
 7,429,000 obs./weights across funds, 124 countries, and over time
 Equity funds: 6,867,500 obs.
 Bond funds: 561,500 obs.
 Variables





Total net assets (TNA)
% of the funds’ assets allocated to each country and held in cash
Investor type: active/passive
Investment scopes (geographical regions)
Others: fund domicile, family, main currency denomination
II. Data: Additional Data
 Fund prices (NAV)




255,510 obs., monthly basis
90% of matches with EPFR funds: 896 equity funds, 106 bond funds
Sources: Bloomberg and Datastream
Used to compute returns and injections to funds
 Country stock and bond market indexes (U.S. dollars)




23,272 obs., monthly basis
Equity markets: 86 countries, Jan 1999-Nov 2010
Bond markets: 78 countries, Jul 2002-Nov 2010
Sources: MSCI std. index, S&P BM index, local sources , JP Morgan
sovereign bond index
 Used to compute the flows to the countries
 Use country-level indexes to compute returns at country level
II. Data: Summary and Main Variables
fijt  Fijt / Ait 1
Country Level Injections/Redemptions
Bloomberg, Dstream,etc.

Ai , j ,t

R j ,t
Fi , j ,t  Ai , j ,t  Ai , j ,t 1 R jt
Country Assets
wi , j ,t
&
Allocations
EPFR
Ai ,t 
TNA
Ri ,t
DStream (match)

Fi ,t  Ai ,t  Ai ,t 1 Rit
Fund Level Injections/Redemptions
fit  Fit / Ait 1


II. Evolution of Total Assets in Equity Funds   Ai ,t 
 i

2001-2010
800,000
90,000
80,000
70,000
60,000
50,000
40,000
30,000
20,000
10,000
0
Millions of USD
700,000
600,000
500,000
400,000
300,000
200,000
100,000
• Assets fluctuate importantly in expected manner (pro-cyclically )
• Driven by prices (returns from previous allocations) or injections?
Jun. 10
Jun. 09
Jun. 08
Jun. 07
Jun. 06
Jun. 05
Jun. 04
Jun. 03
Jun. 02
Jun. 01
Jul. 00
Jan. 00
Jul. 99
Jan. 99
Jul. 98
Jan. 98
Jul. 97
Jan. 97
Jul. 96
0
Jan. 96
Millions of USD
1996-2000
II. Evolution of Portfolio Composition around the GFC
Global Equity Funds
Developed Europe
50%
Emerging Countries
15%
14%
49%
13%
48%
12%
47%
11%
46%
10%
45%
Northern
Rock
44%
43%
Bear
Stearns
9%
Lehman
Brothers
AIG
8%
North America
23%
22%
21%
20%
19%
18%
17%
16%
Average portfolio shares
Sep.09
May.09
Jan.09
Sep.08
May.08
Jan.08
Sep.07
May.07
Jan.07
15%
Sep.09
May.09
Jan.09
Sep.08
May.08
Jan.08
Sep.07
Jan.07
Sep.09
May.09
Jan.09
Sep.08
May.08
Jan.08
Sep.07
May.07
Jan.07
May.07
7%
42%
II. Evolution of Portfolio Composition around the GFC
Global Emerging Equity Funds
Latin America
25%
24%
23%
22%
21%
20%
19%
Average portfolio shares
Sep.09
May.09
Jan.09
Sep.08
May.08
Jan.08
Sep.07
May.07
Jan.07
18%
Sep.09
May.09
Jan.09
Sep.08
May.08
Jan.07
Sep.07
7%
May.07
40%
Sep.09
8%
May.09
9%
42%
Jan.09
10%
44%
Sep.08
11%
46%
May.08
12%
48%
Jan.08
13%
50%
Sep.07
14%
52%
May.07
54%
Jan.07
Emerging Europe
15%
Jan.08
Emerging Asia
56%
II. Evolution of Portfolio Composition around the GFC
Global Bond Funds
25%
20%
15%
10%
5%
Average portfolio shares
Sep.09
May.09
Jan.09
Sep.08
May.08
Jan.08
Sep.07
May.07
Jan.07
0%
Sep.09
May.09
Jan.09
Jan.07
North America
30%
Sep.08
0%
May.08
0%
Sep.07
5%
May.07
10%
Sep.09
10%
May.09
20%
Jan.09
15%
Sep.08
30%
May.08
20%
Jan.08
40%
Sep.07
25%
May.07
50%
Jan.07
Emerging Countries
30%
Jan.08
Developed Europe
60%
II. Evolution of Portfolio Composition around the GFC
Cash Weights – Global Funds
Average portfolio shares
Sep.09
May.09
Jan.09
Sep.09
May.09
Jan.09
Sep.08
May.08
Jan.08
Sep.07
May.07
0%
Sep.08
1%
May.08
2%
Sep.07
3%
May.07
4%
Jan.07
5%
Jan.07
Global Bond
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
Jan.08
Global Equity
6%
Presentation
I.
Motivation
II.
Data and Summary Statistics
III.
Shocks to Managers and Portfolio Reallocations
IV.
Behavior of Investors and Managers
V.
Gross and Net Country Flows
VI.
Conclusions
III. Variation in Assets: Decomposition of Asset Growth
Aˆit  rit  f it
Equity Funds
Mean
Growth Rate
Returns
of Assets
Standard Deviation
Variance Descomposition
Injections/
Initial Assets
Growth Rate of
Assets
Returns
Injections/
Initial Assets
All Equity Funds
2.20%
1.01%
1.15%
10.34%
47.24%
52.76%
Global
1.59%
0.71%
0.88%
6.96%
54.69%
45.31%
Global Emerging
2.85%
1.32%
1.46%
9.67%
49.57%
50.43%
Bond Funds
Mean
Growth Rate
Returns
of Assets
Standard Deviation
Variance Descomposition
Injections/
Initial Assets
Growth Rate of
Assets
Returns
Injections/
Initial Assets
All Bond Funds
3.94%
0.69%
3.19%
8.66%
11.37%
88.63%
Global
0.61%
0.31%
0.60%
7.39%
9.31%
90.69%
Global Emerging
1.31%
0.43%
0.92%
10.54%
9.74%
90.26%
Both injections and valuations matter
III. Variance Decomposition (Tranquil vs. Crisis Times)
Period
All Equity Funds
Global
Global Emerging
Period
All Bond Funds
All
Equity Funds
Global
Global Emerging
Equity Funds
Global Financial Crisis
Before Global Financial Crisis
Narrow Window
(Jan. 2003-Feb. 2007)
(Mar. 2008-Dec. 2009)
Injections/
Injections/
Returns
Returns
Initial Assets
Initial Assets
36.74%
63.26%
67.01%
32.99%
37.06%
62.94%
65.40%
34.60%
33.54%
66.46%
70.15%
29.85%
Global Financial Crisis
Wide Window
(Mar. 2007-Oct. 2010)
Injections/
Returns
Initial Assets
57.65%
42.35%
60.44%
39.56%
64.71%
35.29%
Bond Funds
Global Financial Crisis
Narrow Window
(Mar. 2008-Dec. 2009)
Injections/
Returns
Initial Assets
18.78%
81.22%
2.66%
97.34%
26.23%
73.77%
Global Financial Crisis
Wide Window
(Mar. 2007-Oct. 2010)
Injections/
Returns
Initial Assets
11.82%
88.18%
4.45%
95.55%
20.59%
79.41%
Before Global Financial Crisis
(Jan. 2003-Feb. 2007)
Injections/
Returns
Initial Assets
12.36%
87.64%
5.18%
94.82%
12.90%
87.10%
Not driven by a common time component
III. Significant Variation in Country Weights: Coefficients
of Variation
CV j 
 (w j )
wj
Equity Funds
Across Funds
Within
Target
Region
1.57
Within Funds
0.07
NonTarget
Region
0.66
0.61
0.05
0.41
0.72
Across Funds
0.66
0.04
1.56
0.85
Within Funds
0.53
0.03
0.68
0.93
Number of
Funds
Global
155
Global Emerging
187
Target
Region
Cash
1.15
Bond Funds
Global
30
Global Emerging
81
Across Funds
2.09
0.19
0.56
1.22
Within Funds
0.66
0.08
0.22
0.46
Across Funds
1.23
0.14
1.35
1.78
Within Funds
0.44
0.05
0.35
1.21
Manager’s decision on how to allocate flows may play an important role
Presentation
I.
Motivation
II.
Data and Summary Statistics
III.
Shocks to Managers and Portfolio Reallocations
IV.
Behavior of Investors and Managers
V.
Gross and Net Country Flows
VI.
Conclusions
IV. Behavior of Investors: Injections to Equity Funds
A. Equity Funds
Variables
Country Crisis
Injections/Average Assets
-0.048*
-0.003
-0.009
-0.013
(0.014)
(0.012)
(0.010)
(0.011)
Global Crisis
-0.018*
-0.008†
(0.001)
(0.004)
Lagged Fund Returns
0.161*
0.119*
(0.024)
Country of Origin Returns
(0.023)
0.261*
0.222*
0.171*
(0.033)
0.178*
(0.039)
0.135*
(0.024)
(0.023)
(0.028)
Time Fixed Effects
No
No
No
No
No
Yes
No
Country of Origin-Time Fixed Effects
No
No
No
No
No
No
Yes
41,232
41,232
40,492
39,479
38,764
38,764
40,492
0.035
0.016
0.036
0.017
0.047
0.028
0.050
0.031
0.065
0.046
0.114
0.092
0.174
0.090
No. of Observations
R-squared
Adj.R-sq
Pro-cyclical and subject to wealth effects
*=1%, †=5%, ~=10%
IV. Behavior of Investors: Injections to Bond Funds
B. Bond Funds
Variables
Country Crisis
Injections/Average Assets
-0.081*
-0.070*
-0.018
-0.031
(0.021)
(0.018)
(0.016)
(0.023)
Global Crisis
-0.038*
-0.028*
(0.006)
(0.008)
Lagged Fund Returns
0.229†
0.205†
(0.111)
Country of Origin Returns
(0.102)
0.464*
0.468*
0.126~
(0.070)
0.107
(0.067)
0.337*
Time Fixed Effects
No
No
No
(0.148)
No
Country of Origin-Month Fixed Effects
No
No
No
No
No
No
Yes
No. of Observations
3,520
3,520
3,445
3,261
3,196
3,196
3,445
R-squared
0.061
0.065
0.073
0.068
0.092
0.156
0.266
Adj. R-sq
0.038
0.041
0.051
0.044
0.069
0.107
0.087
Even more than equity funds
(0.127)
No
(0.121)
Yes
No
*=1%, †=5%, ~=10%
IV. Behavior of Managers: Framework
 Behavior of (log) weights
ijt    ijt 1     rjt  rit     Crisis jt   ij  it  ijt
 Comes from log-linearization of identity
wijt  wijt1 
( Rijt  f ijt )
( Rit  f it )
ijt  ijt 1  (rjt  rit )  ( fijt  fit )   it   ijt


buy and hold
 Plus an implicit flow equation
( fijt  fit )    ijt 1     rjt  rit     Crisis jt  ij  it  ijt
IV. Behavior of Managers: Framework
ijt    ijt 1     rjt  rit     Crisis jt   ij  it  ijt
 α and β = 1: buy-and-hold strategy
 α and β ≠ 1: cyclicality of flows from managers to countries
 β < 1 counter-cyclical relative flows
 ϒ response of flows to a crisis (on top of what is captured by β)
 Test for persistence of weights and response to returns and crises
 Similar results if reallocations (relative to buy-and-hold) studied
 Econometric considerations discussed in the paper
 Dynamic panel, UR, Endogeneity
IV. Behavior of Managers: Country Weights
A. Equity Funds
Log Lagged Weights
Relative Returns
Country Crisis
Log Country Weights
Monthly
0.986*
0.982*
0.983*
0.901*
0.901*
0.899 *
(0.001)
(0.001) (0.001)
(0.002) (0.002) (0.002)
0.622*
0.647*
0.993*
0.959*
0.956*
0.598 *
(0.051)
(0.057) (0.013)
(0.049) (0.013) (0.013)
-0.020*
(0.003)
No
Yes
No
No
No
No
No
Yes
No
No
No
No
Fund Fixed Effects
Date Fixed Effects
Fund-Date Fixed
No
No
Yes
Effects
Country of DestinyNo
No
No
Fund Fixed Effects
Log Lagged
Weights=Relative
Returns
0.000*
0.000*
0.446
No. of Observations 458,458 458,458 458,458
Semi Annual Annual
0.568*
0.307*
(0.012)
(0.026)
0.857*
0.567*
(0.032)
(0.035)
-0.069*
-0.118*
(0.017)
(0.026)
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
0.000*
0.000*
0.000*
458,458 458,458 458,458
0.000*
62,949
0.000*
26,018
*=1%, †=5%, ~=10%
IV. Behavior of Managers: Country Weights (Bonds)
B. Bond Funds
Log Country Weights
Monthly
Semi Annual Annual
Log Lagged Weights
0.974* 0.969* 0.970* 0.868* 0.866* 0.866*
0.448*
0.102~
(0.002) (0.003) (0.003) (0.008) (0.009) (0.009)
(0.037)
(0.059)
Relative Returns
0.237* 0.238* 0.638* 0.219* 0.608* 0.611*
0.296*
0.310*
(0.091) (0.091) (0.079) (0.084) (0.073) (0.073)
(0.101)
(0.100)
Country Crisis
-0.016
-0.017
-0.026
(0.011)
(0.050)
(0.084)
Fund Fixed Effects
No
Yes
No
No
No
No
No
No
Date Fixed Effects
No
Yes
No
No
No
No
No
No
Fund-Date Fixed Effects
No
No
Yes
No
Yes
Yes
Yes
Yes
Country of DestinyNo
No
No
Yes
Yes
Yes
Yes
Yes
Fund Fixed Effects
Log Lagged
Weights=Relative
Returns
0.000* 0.000* 0.000* 0.000* 0.000* 0.000*
0.127
0.023†
No. of Observations
39,183 39,183 39,183 39,183 39,183 39,183
5,035
1,959
*=1%, †=5%, ~=10%
Relative flows less pro-cyclical than in equity: contagion, precautionary savings?
IV. Behavior of Managers: Cash Weights
A. Equity Funds
Log Cash Weights
Variables
Log Lagged Weights
Monthly
0.587*
(0.006)
Relative Returns (-Fund return)
0.729*
(0.083)
0.389*
(0.008)
0.700*
(0.102)
0.360*
(0.008)
0.169~
(0.088)
Country Crisis
0.377*
(0.009)
0.494*
(0.099)
0.096~
(0.051)
Global Crisis
0.158*
Semi Annual
Annual
0.112*
-0.083
(0.024)
0.188*
(0.071)
0.116
(0.158)
0.116†
(0.050)
-0.181
(0.138)
0.498~
(0.284)
0.111
(0.018)
(0.049)
(0.101)
Origin Returns
-0.168
-0.437*
-0.034
Fund Fixed Effects
No
Yes
Yes
(0.116)
Yes
(0.097)
Yes
(0.119)
Yes
Time Fixed Effects
No
No
Yes
No
No
No
0.087~
0.002*
0.029†
0.237
0.288
0.479
Log Lagged Weights=Relative Returns
*=1%, †=5%, ~=10%
Counter-cyclical cash positions
IV. Behavior of Managers: Cash Weights (Bonds)
B. Bond Funds
Log Cash Weights
Variables
Log Lagged Weights
Relative Returns
Country Crisis
Global Crisis
Origin Returns
Fund Fixed Effects
Time Fixed Effects
Log Lagged Weights=Relative Returns
Monthly
0.654* 0.449* 0.446* 0.433*
(0.022) (0.029) (0.029) (0.030)
-0.459~ -0.422
-0.682
-0.381
(0.264) (0.303) (0.456) (0.298)
-0.537*
(0.172)
-0.028
(0.047)
0.261
(0.520)
No
Yes
Yes
Yes
No
No
Yes
No
0.000 * 0.004* 0.015 † 0.007*
Semi Annual
0.119
(0.078)
0.166
(0.257)
-1.175~
(0.670)
-0.039
(0.138)
0.991
(0.949)
Yes
No
0.867
Annual
-0.380†
(0.176)
0.510~
(0.295)
-1.923~
(1.057)
0.371~
(0.186)
-0.362
(0.930)
Yes
No
0.010 *
*=1%, †=5%, ~=10%
Pro-cyclical cash positions: precautionary savings? (levels also larger)
Presentation
I.
Motivation
II.
Data and Summary Statistics
III.
Shocks to Managers and Portfolio Reallocations
IV.
Behavior of Investors and Managers
V.
Gross and Net Country Flows
VI.
Conclusions
V. Gross and Net Country Capital Flows: Two Measures
 Gross Flows (includes valuation effects)
Aˆ jt   sijt1  wˆ ijt   sijt1  Aˆ it
i
i

 

Growth rate
of weights
Growth rate
of fund assets
 Net Flows
f jt   sijt1  wˆ ijt  rjt  rit    sijt1  f it
i
i



 

Return-adjusted
growth rate of weights
Injections
V. Net Flows
Shares
(% of Country Growth Rate)
Return-Adjusted
Growth Rate
Injections
of Weights
All
Countries
Type
Active
Passive
Frequency
Monthly
SemiAnnual
Annual
Variance Decomposition
(% of Variance of Country Growth Rate)
Return-Adjusted
Growth Rate
Injections
of Weights
88.4%
11.6%
84.8%
15.2%
87.4%
15.0%
12.6%
85.0%
86.8%
30.9%
13.2%
69.1%
88.4%
11.6%
84.8%
15.2%
83.3%
16.7%
78.9%
21.1%
80.6%
19.4%
73.0%
27.0%
Manager’s behavior explains most of MF net capital flows to countries
Larger for active funds
V. Gross and Net Country Flows: Quantitative Effects
 10% decline in lagged fund returns reduces injections in 1 pp
 If all funds investing in a country experience such decline, gross flows will
decline in 1 pp
 This is close to the median gross flow across countries (2%)
 10% decline in country of origin returns reduces injections in 2 pp
 10% decline in relative returns (holding fund returns constant)
induces a similar decline in gross flows
 A country crisis leads to a 2% decline in gross flows
 10% decline in relative returns yields a 1 pp decline in relative flows
 Similar to the unweighted average growth in net flows in the sample (-1.5%)
• If this is accompanied by a low fund performance or low returns in the
country of origin, that can induce large redemptions (4 pp decline)
V. Gross and Net Country Flows: Quantitative Effects
 For a shock to injections to have no effect on a country’s net flows
we need relative flows to compensate in the same amount
 Only countries that are doing relatively well, would not be seriously
affected by shocks to the injections by underlying investors
 Even in this case, contagion may be an important source of capital
flows
Presentation
I.
Motivation
II.
Data and Summary Statistics
III.
Shocks to Managers and Portfolio Reallocations
IV.
Behavior of Investors and Managers
V.
Gross and Net Country Flows
VI.
Conclusions
VI. Conclusions: Main Results
 MF assets fluctuate substantially over time, pro-cyclically
 Particularly pronounced effects during crises
 Large reallocations during global crisis, consistent with retrenchment
 Both investors and managers behind these movements,
changing their investments substantially over time
 … and shaping fluctuations in capital flows
 Neither managers nor investors exploit potential arbitrage
opportunities by being contrarian during crises
 No stabilizing role: amplify crises & transmit shocks x countries
 Important policy lesson: Runs even among equity-type
investors
VI. Conclusions: Main Results
 Not the case that bad shocks at home country propel more
investments abroad, to the contrary
 Underlying investors do not act either as deep-pocket
international investors buying assets abroad at fire sale prices
 Their behavior exerts pressure on managers, who need to
react to these shocks
 Evidence not consistent with constant country weights, which
change substantially over time
 Managers move away from countries experiencing crises
 Cash positions actively used, differently for equity and bonds
Thank you!