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Cracking the EmergingMarkets Enigma
Andrew KarolyiProfessor of Finance & Alumni Professor of Asset Management, Cornell University
Third Luxembourg Asset Management Conference, November 17, 2014
I. The Phenomenon: EMs in 2013
2013: A Tough Year for EMs
MSCI World
MSCI Emerging Markets
Sliding BRICS in May & June
Bank for International Settlements Quarterly Review
What happened in May & June?
“Normalize”?
And the Taper Tantrums Began!
“We hope that the issuing country of the largest reserve currency in the world should be mindful of the spillover effects of its macroeconomic policies.” Zhu Guangyao, China’s Deputy Finance Minister
China Daily, September 6, 2013
EM outflows continue in 2014…
…and so do the Taper Tantrums
“… a lack of a coordinated exit from exceptionally loose monetary policies was done at the expense of emerging markets.” Alexandre Tombini, Governorof Central Bank of Brazil
“International monetary cooperationhas broken down…Industrial countries have to play a part in restoring that [co-operation], and they can’t at this point wash their hands off and say, we’ll do what we need to and you do the adjustment.” RBI Governor Raghu Rajan
Different countries hit differently?
?
So what do we have?
• Some Observations:– The tapering talk had a sharp negative impact
on emerging markets– It was surprisingly large– Different countries were affected differently
• Some Questions:– Which were hit hardest by Fed’s taper talk? – Why these and not others? – Is it related to “fundamentals”? Which ones?
II. A (biased) perspective on the EM Experience
in 2013
Forthcoming Oxford University Press, May 2015
What is the new book about?
• I develop a rigorous, comprehensive, and practical framework to measure the fundamental risks associated with investing in emerging markets:– Rigorous. Foundation of sound academic research at its core.– Comprehensive. Multiple dimensions of risks reflecting the
uneven quality of institutions that assure integrity of markets.– Practical. I devise a scoring system that ranks EMs on each
dimension of risk using principal component analysis (PCA).
• I build the indicators for 33 EMs plus 24 developed using publicly-available data sources and show they work very well in explaining foreign investor cross-country holdings
Why bother writing it?• To elevate the quality of the discourse in industry
circles about what an emerging market really is• Answer? Page 1, first sentence:
“Underfunded growth opportunities with problems”
• Why bother?– Refocus attention: NOT JUST the growth potential– Emphasize multiple dimensions of risk that can matter– Stop with the endless race to coin a new acronym!
(BRIC, BRICS, N-11, TIMPS, CIVETS, MINT, etc.)– Useful to explain how investors think based on actions?– Academics? A useful summary of our collective wisdom?
What are my risk indicators?
• Market Capacity Constraints
– Market cap to GDP– GDP per capita– Private/public bond market
capitalization– Turnover ratios– New issues to GDP• Operational
Inefficiencies– Brokerage commissions,
transfer taxes, market impact costs
– Illiquidity proxies– Short-sales constraints– Settlement cycles (T+N),
book-entry, delivery vs. payment (DVP)
• Foreign Investability Restrictions
– S&P/IFC accessibility– Registration rules,
ownership restrictions, FX convertibility limits
– Withholding taxes, double taxation treaties
• Corporate Opacity– Governance rankings– Accounting standards– Earnings management– Blockholder control– Closely-held shares
• Limits on Legal Protections– Anti-self-dealing– Anti-director rights– Creditor info, registry– Director liability, shareholder suits,
contract enforcement – Insider trading laws
• Political Instability– Political constraints (PolConV,
PolityIV, DPI) – Voice & Accountability, Govt.
Effectiveness, Rule of Law, Regulatory Burden
– Transparency International’s Corruption
– Heritage Foundation’s Freedom Index
How do I build them?
• Step 1: Harvest the wisdom of academic research– For example: Lots of research on market microstructure
around the world for “Operational inefficiencies”
• Step 2: Combine with other useful data
• Step 3: Synthesize into single risk index with PCA
How do I build them?
PCA for Operational Inefficiencies
???
How is the book organized?
• Part I. Setting the Stage:– Accepting the challenge– Defining my EM universe– A Primer on PCA methodology
• Part II. Building the EM Risk Indicators• Part III. Validating the EM Risk Indicators
– I conduct three experiments
• Part IV. Conclusions and Caveats
How do the indicators look?
Market Capacity Constraints
Operational Inefficiencies
Foreign Accessibility Restrictions
Corporate Opacity
Limits to Legal Protections
Political Instability
-1.0
0.0
1.0
Emerging Markets Developed Markets
How do the indicators look?
How do the EMs rank overall?
They can evolve over time
Validating EM Indicators: Part I
• In Part III of the book, I test whether the six risk indicators can “explain” foreign portfolio holdings in 2012:– FactSet (formerly Lionshares), global institutional;
over $23.6 trillion AUM, $6.3 trillion is foreign only– U.S. Treasury International Capital (TIC), U.S.
residents only, retail and institutional, $7.9 trillion
• Focus is on excess holdings relative to MSCI ACWI weights to capture potential “biases”
Biases in Foreign Holdings
China Russia
Taiwan
Israel
India
Indonesia
South Africa
Turkey
Argentina
Chile
ColombiaEgyp
tIndia
Israel
South Kore
a
Mexic
o
Nigeria Peru
Poland
Saudi A
rabia
Slove
nia
Sri La
nka
Thailand
Venezuela
-10%
-5%
0%
5%
10%
15%
BrazilChina
-18.72%Israel
Korea
South Africa
Taiwan
Actu
al F
racti
on o
f For
eign
Equ
ity H
oldi
ngs
Less
Fr
actio
n of
Wor
ld M
arke
t Cap
italiz
ation
in 2
012
U.S. residents invest $1.01 trillion in 2012
Regression Evidence
A 1σ increase in quality of corporate governance – from Philippines to South Africa – is associated with 0.98% increase (decrease) in over (under) weight
What about Luxembourg?
A Quasi-Natural Experiment?
• What about “taper talk” and EM portfolio flows in 2013?
• Are they linked empirically to the cross-country differences in fundamental risks?
• An out-of-sample experiment? (Chapter 11)
Validating EM Indicators Part II:2013 EM portfolio flows
Arge
ntina
Braz
ilCh
ileCh
ina
Colo
mbi
aCz
ech
Egyp
tH
unga
ryIn
dia
Indo
nesia
Isra
elKo
rea
Mal
aysia
Mex
ico
Mor
occo
Paki
stan
Peru
Phili
ppin
esPo
land
Russ
iaSo
uth
Afric
aTa
iwan
Thai
land
Turk
eyVe
nezu
ela
-40%
-30%
-20%
-10%
0%
10%
20%
30%
Net
Flo
ws o
f For
eign
Deb
t & E
quity
in 2
013
as %
of T
otal
For
eign
Hol
ding
s in
2012
Lots of cross-country variation!
U.S. Residents Only
What about 2013 EM flows?
A 1σ increase in limits to legal protections – from Argentina to Korea – is associated with 0.72% higher inflows (lower outflows) in
2013 as a % of 2012 holdings
III. Newer Evidence from EM Mutual Funds in 2013
A new study (in the works)
• “Racing to the Exit: Emerging Market Mutual Funds during the Fed Taper Talk of 2013” by Andrew Karolyi and Kirsty McLaren (PhD, Judge Business School, Cambridge University)
• Who? 312 active EM mutual funds with Morningstar individual holdings through 6/30/13, $318 billion AUM
• What? We compute their country-level active bets (Cremers-Petajisto, 2009) and flow-induced fund allocations (Jotikasthira, Lundblad, Ramadorai, 2012)
• Why? Which funds made big bets? Which direction? What fund attributes matter? What country attributes?
The GEM Fund Sample
Overall Small Adjustments…
…but lots of variation in active bets
-20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 200
10
20
30
40
50
60
70
80
90
Change in Country-level Active Share
Freq
uenc
y (o
ut o
f 312
GEM
Mut
ual F
unds
)
ΔActive Share
…And especially their timing bets
-50 -45 -40 -35 -30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35 40 45 50 >500
10
20
30
40
50
60
70
Country-level Market Timing
Freq
uenc
y (3
12 A
ctive
GEM
Mut
ual F
unds
)
Market Timing
Which EM funds are these?!?
Which funds timed their EM bets?Market Timing
Which GEM mutual funds strategically timed the markets?• Smaller funds in total net assets!• Funds that had stronger returns leading up to taper talk !!!!
Next question: Which EMs were focus of “market timers”?
FIFAs versus Risk Factors
-0.12% -0.10% -0.08% -0.06% -0.04% -0.02% 0.00% 0.02% 0.04% 0.06%
-0.03%
-0.02%
-0.01%
0.00%
0.01%
0.02%
0.03%
0.04%
0.05%
0.06%
Hungary
Mexico
Nigeria
f(x) = 0.335315949468257 x + 4.71053572292871E-05R² = 0.335315949468256
Actual FIFA (May-June 2013)
Expe
cted
FIF
A (b
ased
on
Risk
Fac
tors
)
Emerging Market Enigma Cracked?
• Hardly!
• And 2013 is a useful quasi-natural experiment to evaluate what institutional attributes of EMs really matter to global investors
• “Softer” constraints like corporate opacity, limits on legal protections, political instability seem to matter more than “basic” risks like operational costs, market capacity constraints, foreign restrictions
• Stay tuned – lots more to come
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