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Flows & Assets Report The Big Emerging Markets Short First Quarter 2016
BBVA Research
Gonzalo De Cadenas & Alvaro Ortiz (Cross EM Unit)
Julián Cubero & Sara Baliña (Economic Scenarios)
Sonsoles Castillo & Cristina Varela (Financial Scenarios)
Flows and Assets Report: Q1 2016
1. Key Messages
2. Portfolio Flows & Asset Prices: stylized facts, drivers and now-casts
3. Scenarios: Macroeconomic and Monetary Policy and Flows Scenarios
4. Hot Topic: Liquidity Risk & FX
5. Useful Information: Methodological Appendix
Index
2
Flows and Assets Report: Q1 2016
Summary
3
Main drivers
• Global growth concerns led by China’s policy
shifts and inability to sooth investor concerns
heightened risk off-mood particularly by year-
end.
• Global monetary policy easing bias that
initially prevented further deterioration lost
effect. The short recess in financial volatility
was followed by a relapse. Unlike previous
episodes, the trigger was not in the Fed
policy but China, EM vulnerabilities and
potential impact of EM & DM.
(Review of previous quarter events & insight into 2016 on behalf of the information collected
as of January 30th 2016)
Portfolio Flows
• EM Portfolio flows in Q4-15 were similar to
Tantrum times (~ $ -65 Bn.). Since the Taper
it was ~ $ -350 Bn. Very much the Lehman
times alike. This happens in a context of
much lower weight of EM assets in global
portfolios.
• Selective and strong flow reallocation away
from EMs remains with little discrimination.
Increased active portfolio management and
retail investor base warrant higher flow
volatility and sensitivity to global financial
conditions.
Flows and Assets Report: Q1 2016
Summary
4
Asset prices
• Financial tensions: EM financial tensions failed
to recede. China’s contagiousness unveils
EM’s cyclical fragility. Divergent monetary
paths in DM are also a source for volatility.
• Risk premia: the stint of financial tensions and
worrying outlook brought a moderate risk re-
pricing that derailed some EM from
Investment Grade (Brazil)
• FX: currencies best gauge the negative
sentiment towards EM financial assets. Global
factors weighted in all currencies depreciation,
intensity will vary on vulnerabilities and
funding structure (more on bonds).
(Review of previous quarter events & insight into 2016 on behalf of the information collected
as of January 30th 2016)
Forecasts & Analysis
• Baseline scenario is for EM flows steadily to
run below long term trend reallocating from
EMs to DMs.
• Our forecasts carry a strong tilt to the
downside for EM capital flows and assets
valuations amid the array of risk factors
ahead (doubts about China growth, spillovers
RMB devaluation, corporate debt overhang in
some key EM, geopolitical tensions) and the
lack of policy room to maneuver. In a risk
scenario it shouldn't be discarded an
enhanced activism from EM Central Banks to
avoid domestic balance sheet mismatches.
Capital flows Quarterly assessment
Flows and Assets Report: Q1 2016
Cumulated Portfolio Flows to Emerging Markets
using High Frequency Data
(Flow in US$ Tn)
Source: BBVA Research & FMI
Events unfolded as envisaged in our negative scenario
(bringing flows below the previous base scenario)
6
The China triggered sell off continues generalized by private balance sheet vulnerabilities in a context of uneven global monetary policy (in line with negative scenario)
A sell-off episode that reminds early Lehman times
In both cases flows went down -50% from equilibrium
levels and along the same period
EM Portfolio flows in Q4-15 were similar to Tantrum
times (~ $ -65 Bn.)
Since Taper it was ~ $ -350 Bn.
-600
-400
-200
0
200
2013 2014 2015 2016
0.0
0.5
1.0
2006 2008 2010 2012 2014 2016
High Frequency
Imbalance
Assessment (Deviations from
Long Term Trend in
%. Portfolio Flow
Excess in % )
Flows and Assets Report: Q1 2016
BBVA High Frequency Portfolio Flows Map (% monthly change in net liabilities measured as net flows to total assets under management)
Source: BBVA Research 7
Countries orbiting the oil setback and those caught in geopolitical conflicts and strongest macro vulnerabilities register the largest net portfolio outflows
USA # # # # # # # # # # # # #
Japan # # # # # # # # # # # # #
Canada # # # # # # # # # # # # #
UK # # # # # # # # # # # # #
Sweeden # # # # # # # # # # # # #
Norway # # # # # # # # # # # # #
Denmark # # # # # # # # # # # # #
Finland # # # # # # # # # # # # #
Germany # # # # # # # # # # # # #
Austria # # # # # # # # # # # # #
Netherlands # # # # # # # # # # # # #
France # # # # # # # # # # # # #
Belgium # # # # # # # # # # # # #
Italy # # # # # # # # # # # # #
Spain # # # # # # # # # # # # #
Ireland # # # # # # # # # # # # #
Portugal # # # # # # # # # # # # #
Greece # # # # # # # # # # # # #
Poland # # # # # # # # # # # # #
Czech Rep # # # # # # # # # # # # #
Hungary # # # # # # # # # # # # #
Turkey # # # # # # # # # # # # #
Russia # # # # # # # # # # # # #
Mexico # # # # # # # # # # # # #
Brazil # # # # # # # # # # # # #
Chile # # # # # # # # # # # # #
Colombia # # # # # # # # # # # # #
PeruPeru # # # # # # # # # # # # #
Argentina # # # # # # # # # # # # #
China # # # # # # # # # # # # #
IndiaIndia # # # # # # # # # # # # #
Korea # # # # # # # # # # # # #
Thailand # # # # # # # # # # # # #
Indonesia # # # # # # # # # # # # #
Philippines # # # # # # # # # # # # #
Hong Kong # # # # # # # # # # # # #
Singapore # # # # # # # # # # # # #
2016
Asi
a
2014 2015
G4
Wes
tern
Eu
rop
eEM
Eu
rLA
TAM
2011 2012 2013
<-2% +2%> 0%
*BBVA Research Portfolio Flows Map: The Flows Map show the monthly evolution of net inflows with
Darker blue colors representing sharp net outflows and lighter colors standing for net Inflows
• Reallocation and flight to quality supported DMs (mainly, Japan). Oil concerns also strike Norway
• Discrimination in the Eurozone valuations and real interest rate conditional
• EM Europe caught in the weakening cycle and the geopolitical blockade Russia/Turkey
• Commodity prices correction and the scarce monetary room to maneuver had a stake in Latam
• Very scarce discrimination (Thailand and India) possible in Asia, caught in the weakening cycle despite of the non commodity exporting condition
Flows 4Q15 vs. 3Q15 (% quarterly change in flows,
shades are previous values)
-6.0 -1.0 4.0
USACanada
SweedenDenmarkGermany
NetherlandsBelgium
SpainPortugal
PolandHungary
RussiaBrazil
ColombiaArgentina
IndiaThailand
PhilippinesSingapore
Flows and Assets Report: Q1 2016
Source: BBVA Research 8
Relentless flight to quality and persistent and broad based volatility across risk assets May anticipate this turning into an EM crisis episode with global reach
BBVA Research Safe Haven Indicator (Median Safe Haven Factor from flows and asset prices data using the BBVA DFM/FAVAR Model)
BBVA Safe Haven Indicator Represents the median of the selected Safe Haven
Components in Portfolio Flows, Risk Premia and FX data
-2
-1
0
1
2
3
4
5
6
7
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
Le
hm
So
v. F
in. C
risis
UE
Ta
pe
ring
EM
Cris
is W
oe
s:
fina
ncia
l insta
bility
(eq
uity
se
ll off &
RM
B d
eva
lua
tion
)
Performance Financial Assets (Base year 2013) EMBI: EM sovereign bond index, CEMBI: EM corporate bond index, MSCI World: world equity index, DXY index
70
90
110
130
150
170
190
210
02-J
an-1
3
02-J
ul-1
3
02-J
an
-14
02-J
ul-1
4
02-J
an
-15
02-J
ul-1
5
02-J
an
-16
EMBI G (spread) CEMBI Broad (Spread)
MSCI World DXY
Extreme High Normal Below Normal
Source: BBVA Research and Bloomberg
Flows and Assets Report: Q1 2016
-5.0-2.50.02.55.0
Source: BBVA Research 9
Bonds
Equity
Net Flows Q4 2015 by Asset Class (% quarterly change in Country Flows over Total Assets. Shades are previous quarterly changes)
Net Flows Q4 2015 by Investor Type (% quarterly change Country Flows over Total Assets. Shades are previous quarterly changes)
Institutional
Retail
Increased active portfolio management (open end mutual funds*) and retail investor base warrant higher flow volatility and sensitivity to global financial conditions
Usa
Japan
Canada
UK
Sw
eeden
Norw
ay
Denm
ark
Fin
land
Germ
any
Austr
ia
Neth
erlands
Fra
nce
Belg
ium
Italy
Spain
Irela
nd
Port
ugal
Gre
ece
Pola
nd
Czech R
ep
Hungary
Turk
ey
Russia
Mexic
o
Bra
zil
Chile
Colo
mbia
Peru
Arg
entina
Chin
a
India
Kore
a
Thaila
nd
Indonesia
Phili
ppin
es
Hong K
ong
Sin
gapore
-5.0-2.50.02.55.0
-5.0-2.50.02.55.0
-5.0-2.50.02.55.0
Flows and Assets Report: Q1 2016
Source: BBVA Research 10
Estimated Net Equity Flows Q4 2015 (Dark blue are Net Outflows, Light Blue are Net Inflows in Q415)
Capital flows by region: 4-week moving average (country flows as % of AUM)
Bonds
Initial rotation from Bonds (Fed lift-off) to Equity (attractive valuations) and preference for safe assets (reallocation) soon followed by simple flight to quality (January equity global sell-off and increase in gold prices)
Source: BBVA Research
US Peripheral Europe Core Europe EM
Equity
-1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60 0.80 1.00
M-13 J-13 N-13 M-14 J-14 N-14 M-15 J-15 N-15
Taper tantrum
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
M-13 J-13 N-13 M-14 J-14 N-14 M-15 J-15 N-15
Ro
tati
on
Reallocation
Outflows Size Inflows Size
-7% 7%
Flows and Assets Report: Q1 2016
Source: BBVA Research 11 Source: BBVA Research
-4
-2
0
2
4
Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16
Global
Local
EM
Emerging Markets Flows (Median Emerging Market Portfolio Flow Decomposition,
monthly change in %)
30%
70%
Global factors relentlessly dominate net outflows away from EMs* yet the idiosyncratic cycle still plays a very relevant role.
BBVA Global Factor of Portfolio Flows Decomposition (First Factor from Flows using BBVA’s DFM/FAVAR Model
represents the main driver of flows)
(*) Increased redeemable funds acting at shorter horizons exacerbate the movement as
less pension and insurance long term funds give leeway to more Open End MFs and ETFs
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
Dec-12 Jun-13 Dec-13 Jun-14 Dec-14 Jun-15 Dec-15
Activity in DMs Activity in EMs Interest rates US (10Y) Interest rates EZ (10Y) Risk in Global (VIX) Risk in EM (Embi)
Flows and Assets Report: Q1 2016
12 Source: BBVA Research
BBVA Global Factor of Portfolio Flows Decomposition (First Factor from Flows using BBVA’s DFM/FAVAR Model
represents the main driver of flows)
EM risk perception loops back and forth into global risk aversion in a context of Fed’s new stance
Materializing US monetary policy shift (Dec. hike) and
undershooting expectations on ECB additional measures
Worryingly worsening of EM growth supplements tepid
recovery in DMs
Portfolio flows impaired on global risk aversion amid
Chinese uncertainty (economic cycle) and EM idiosyncratic
factors
Heightened global risk aversion bundled to monetary policy
dynamics. Global liquidity concerns in the context of
increased cost of capital (USD appreciation and expected
US rate path)
Factors in Q4 2015
Factors expected in Q1 2016
Financial Variables Quarterly assessment
Flows and Assets Report: Q1 2016
Source: BBVA Research 14 Source: BBVA Research based on Bloomberg data
BBVA Research Financial Stress Index regional map Standard deviation ≈ (-1, 1)
BBVA Financial Tensions Index MAP
This indicator measures financial tensions from different
indicators across DM and EM Countries
These indicators are: sovereign risk measures, stock market
volatility, bank credit risk (CDS 5yr), corporate credit risk,
interest rate volatility, currency volatility and liquidity tensions.
EM Financial Tensions stuck at summer levels China’s contagiousness unveils EM cyclical fragility. Divergent monetary paths in DM are also a volatility source
Jan-1
6
# # # # # # # #
EMU # # # # # # # #
# # # # # # # #
Brazil # # # # # # # #
Chile # # # # # # # #
Colombia # # # # # # # #
Mexico # # # # # # # #
Peru # # # # # # # #
# # # # # # # #
Czech Republic # # # # # # # #
Hungary # # # # # # # #
Poland # # # # # # # #
Russia # # # # # # # #
Turkey # # # # # # # #
# # # # # # # #
China # # # # # # # #
India # # # # # # # #
Indonesia # # # # # # # #
Korea # # # # # # # #
Malaysia # # # # # # # #
Philippines # # # # # # # #
Taiwan # # # # # # # #
Thailand # # # # # # # #
US
Latam
EMEA
Asia
Dec-1
5
Oct-
15
Jul-15
Aug-1
5
Jun-1
5
Nov-1
5
Jan-1
5
Sep-1
5
Dec-1
4
May-1
5
Apr-
15
Mar-
15
Feb-1
5
-1.5
0.0
1.5
3.0
4.5
Jan-0
8
Jan-0
9
Jan-1
0
Jan-1
1
Jan-1
2
Jan-1
3
Jan-1
4
Jan-1
5
Jan-1
6
Developed Emerging
BBVA Research Financial Stress Index for Developed and Emerging markets (normalized Index)
Very High Very Low
Flows and Assets Report: Q1 2016
Source: BBVA Research, Haver 15
EM monetary policy trilemma remains: countercyclical role vs. inflation anchoring balance sheet stabilization
Real Interest Rates map Level up to Nov-15
>4.0 2.0-4.0 0.-2.0 -3.0-0 <-3.0
Flows and Assets Report: Q1 2016
Source: BBVA Research 16 Source: BBVA Research
20% 80%
Risk Premium Change in Turkey and Factors
Risk Premium Change in Brazil and Factors
EM risk premia evenly affected by a mix of global and local factors Yet a vast degree of dispersion is found among EMS
52%
48%
EMs change in risk premia (Median EM 5Y CDS in bps change)
85%
15%
-20
-15
-10
-5
0
5
10
15
20
25
30
Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16
Local
Global/Regional
EM TOTAL
50% 50%
-40
-20
0
20
40
60
Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16
Local
Global/Regional
Brazil
-30
-20
-10
0
10
20
30
41275 41456 41640 41821 42005 42186 42370
Local
Global/Regional -80 bps
Graft
Probe
Fed
Wording Elections QE3 &
Draghi Tapering & Taksim
Flows and Assets Report: Q1 2016
Source: BBVA Research 17 Source: BBVA Research
Exchange Rate: currencies best gauge the negative sentiment towards EM financial assets Sudden RMB shifts triggered strong financial volatility changes
FX 4Q15 vs 3Q2015 change in % (shades are last quarter’s cum FX change vs USD)
-35.0 -30.0 -25.0 -20.0 -15.0 -10.0 -5.0 0.0 5.0 10.0
Switzerland Japan
Canada UK
Sweeden Norway
Denmark EuroZone
Poland Czech Rep
Hungary Turkey Russia Mexico
Brazil Chile
Colombia Peru
Argentina China India
Korea Thailand
Indonesia Philippines Hong Kong Singapore
FX Change Decomposition in Emerging Markets * (in % MoM change, negative are depreciations vs USD)
(*) Measured as median % MoM change from the following Emerging Economies;
Turkey, Poland Czech. Rep., Hungary, Russia, South Africa, Mexico, Brazil, Chile,
Colombia, Argentina, Peru, China, Korea, Thailand, India, Indonesia, Philippines,
Hong Kong, Singapore
-8
-6
-4
-2
0
2
4
Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16
Global
Regional/Local
Emerging FX
65% 35%
(*) Argentinas case Comes after the new government decission to free the exchange rate controls.
Flows and Assets Report: Q1 2016
Source: BBVA Research 18
-15
-10
-5
0
5
10
Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16
Global
Local
Brazil FX
FX Change Decomposition in Emerging Markets (in % MoM change, negative are depreciations)
Brazil (Real) Turkey (Lira)
-10
-8
-6
-4
-2
0
2
4
Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16
Local/Regional
GLOBAL
Turey
The effect of global factors is greater where funding remains coupled to bond inflows
Flows and Assets Report: Q1 2016
Source: BBVA Research 19
Q4 2015 Equity price
Changes (% QoQ) (shades are last
quarters QoQ change)
### Sharp Equity Price Contraction (below -6 %)
### Strong Equity Price Contraction (between -3 % and -6 %)
### Moderate Equity Price Contraction (between 0 and -3 %)
0,50 Moderate Equity Price Expansion (between 0 and 3 %)
1,20 Strong Equity Price Expansion (between 3 % and 6 %)
3,00 Booming Equity Price Expansion (greater than 6 %)
BBVA Equity Price Map (Monthly Variation of Equity Price Indexes in %)
USA # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Japan # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Canada # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
UK # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Sweeden # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Norway # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Denmark # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Finland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Germany # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Austria # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Netherlands # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
France # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Belgium # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Italy # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Spain # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Ireland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Portugal # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Greece # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Poland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Czech Rep # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hungary # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Turkey # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Russia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Mexico # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Brazil # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Chile # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Colombia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
PeruPeru # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Argentina # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
China # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
IndiaIndia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Korea # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Thailand # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Indonesia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Philippines # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hong Kong # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Singapore # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
2014
G4
West
ern
Eu
rop
eEM
Eu
r
20152011 2012 2013
LA
TA
MA
sia
-40.0 -20.0 0.0 20.0
USA
Canada
Sweeden
Denmark
Germany
Netherlands
Belgium
Spain
Portugal
Poland
Hungary
Russia
Brazil
Colombia
Argentina
India
Thailand
Philippines
Singapore
Equity prices dropped across the board in a global sell off As anticipated FX risk re-pricing, higher cost of capital & faltering growth slashed earnings expectations
Flows and Assets Report: Q1 2016
20
Recent sell-off improved equity markets valuations Though short stints of reversion cannot be discarded, uncertainties about the profit cycle prevent a sustainable price recovery
BBVA Assessing Equity Market Misalignment Composite Indicator (Weighted average, of PER 12months Forward, PER12months Trailing and P/B Ratios) updated Jan 20th
Source: BBVA Research
Country
US # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Japan # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Canada # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
UK # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Europe # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
EMU # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Denmark # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Netherlands # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Germany # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
France # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Italy # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Belgium # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Greece # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Spain # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Ireland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Portugal # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Turkey # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Poland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Czech Rep # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hungary # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Romania # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Russia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Mexico # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Brazil # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Chile # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Colombia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Argentina # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Peru # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
China # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Korea # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Thailand # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
India # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Indonesia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Malaysia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Philippines
Hong Kong # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Singapore # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
2016
Asi
a
2011 2012
G4
Wes
tern
Eu
rop
e
2006 2007 2008 2009 20102001 2002 2003 2004
Euro
pe
EMLA
TAM
2005 20152013 2014
Most DM returned to levels close to fair value, after equity markets
plunge early in 2016. Yet, there are some core EZ stocks that remain
overvalued
Equity valuations mixed in EM. In Latam, Chile and Colombia are
undervalued in historical terms, while Mexico moderated its
overvaluation
In EM Europe, liquid markets such as Turkey, Poland and Russia
remained undervalued, but the uncertainty about the oil prices and
idiosyncratic factors limited the gains in the short-term
In Asian markets, India and Indonesia remain overvalued, while
China is undervalued, although uncertainties about the policy
management makes difficult a sustainable recovery of prices
zscore Highly overvalued 1.5
Overvalued 1.0-1.5
Slightly overvalued 0.5-1.0 Fair Value -0.5- -0.5
Slightly undervalued -1.0--0.5
Undervalued -1.5--1.0
Highly undervalued -1.5
Flows and Assets Report: Q1 2016
Source: JP Morgan, BBVA Research 21
Could financial markets be pricing a 2nd. round of tail risks on corporates, sovereign & quasi-sovereign?
EM Corporate debt index (spread bp)
0,0
200,0
400,0
600,0
800,0
1.000,0
1.200,0
Jan-07 Jan-09 Jan-11 Jan-13 Jan-15
CEMBI Mexico CEMBI Brazil CEMBI Colombia
CEMBI Chile CEMBI Peru
0
200
400
600
800
1.000
1.200
1.400
1.600
1.800
2.000
May-07 May-09 May-11 May-13 May-15
CEMBI Asia CEMBI Latam CEMBI EM Europe
EM Corporate bond index (spread bp)
Source: JP Morgan, BBVA Research
Flows and Assets Report: Q1 2016
Source: JP Morgan, BBVA Research 22 Source: JP Morgan, BBVA Research
(**) Other funds: they could include loans in FX
Source: BBVA Research, BIS
Corporate Debt, structure up to Q115 (% total)
Corporate debt overhang in key EMs could exacerbate the loop between cyclical adjustment And higher financial costs bringing further FX depreciation & higher rates
EM: Corporate debt (as % of GDP)
0
20
40
60
80
100
120
140
160
180
Arg
en
tin
a
Me
xic
o
Ind
on
esia
Pe
ru
Co
lom
bia
Po
lan
d
Bra
zil
Ind
ia
Tu
rke
y
Ru
ssia
Ch
ile
Ch
ina
External Debt Domestic Capital Market Debt
Other funds (loans) Sample average
Scenarios Simulation analysis
Flows and Assets Report: Q1 2016
Source: BBVA Research 24
Shocks
Vast array of shocks with global scope Some Known unknowns such as a sharp RMB depreciation or a credit crunch in big EM could amplify the impact
EM Debt Overhang
(Corporate leverage)
Economic downturn and credit
crunch in big EM: negative feedback
loop between lower corporate
profitability and financial constrains.
Higher impact on those corporates
with more exposure to indebtedness
denominated in FX
Vulnerable EM with high private
indebtedness (China, Brazil, Turkey)
Cycle of defaults in corporates with
high indebtedness. Spillovers on
banking sector (rebound of NPL) and
domestic activity
Shocks Shock definition Contagion Channels Global impact: greatest impact on…
China's shock
Financial disruption -equity bubble
burst and sharp RMB devaluation-
with significant impact on domestic
demand. Failure of economic policies
to avoid a hard landing
Spike of volatility, in particular, sharp
rebound in EM risk premia& FX
depreciations
EM commodity exporters (LatAm),
China's trade partners (other Asian
countries and USA) and EM countries
with a vulnerable external position
(Turkey, Brazil)
Intense commodity prices fall (oil
below 20$/b in 2016-17) & global
trade downturn
Commodity prices relapse (oil close to
30$/b in 2016-17) & global trade
slowdown
Geopolitics: complex
and interconnected
events
Rebound of financial tensions in
neighbors. Potential increase of oil
prices if conflict impacts on its supply
Higher risk premia (structural reforms
halt) + economic slowdown through
lower confidence & credit restrictions
Failed recovery in EMU
and Japan and/or US
cyclical relapse
Stagnation in EMU and Japan and/or
technical recession in US.
Ineffectiveness of monetary policy
(deleveraging process & capital
investment constrains)
Increase of global risk aversion
smoothed by additional QE stimulus Countries with close trade links with
EMU (EM Europe), Japan (EM Asia)
and/or US (Mexico)
Increase of global risk aversion &
funding constrains across the board.
Huge EM capital outflowsEM with a more vulnerable external
position (FX debt & current account
deficit) as, for example, Turkey and
Colombia Synchronized activity adjustment,
more intense in those sectors
dependent on debt funding
EM Europe
EMU Peripheral countries
Upsurge in geopolitical tensions in
Middle East: new wave of refugees
crisis, social unrest and spiral of
terrorist attacks
In Europe, populism gains ground
and puts at risk the political stability
Risk of Brexit (UK in/out EU)
increases
Fed tightening path
Higher/sharper than expected
interest rate hikes, not supported by
domestic demand improvement,
provokes US recession
Severity degree
Probability
Flows and Assets Report: Q1 2016
Source: BBVA Research–FAVAR Model 25
Scenarios
All carry a tilt to the downside for EMs
• Global monetary policy
Long end rates anchored at
low levels. Divergences remain
after Fed lift-off
(BCE further easing vs smooth
yet steady FED hikes)
• Global growth
Gradual yet subpar global
recovery supported overly by
DMs
• Global risk aversion
Resilient at the current levels
EM high risk premia resiliently
elevated
Baseline Scenario
• Global monetary policy
Reinforced easing in DM but
limited room to maneuver. EM
Policy support the cycle (and
prevent outflows) conditional on
exchange rate and policy room
• Global growth
China triggered correction of
EM growth continues, reinforced
by anemic growth in DM
• Global risk aversion
Heightened risk aversion
globally (in particular in EM)
surging financial tensions
across the board
Mild Global Risk
• Global monetary policy
Reinforced easing in DM and
flight to quality anchors long
rates at low levels. Tightened
funding conditions in EM
• Global growth
EM meltdown; DM stagnation
• Global risk aversion
Despite policy support tries to
sooth financial volatility,
relentless surge in EM risk
premia
Heightened Global Risk on China Woes
Flows and Assets Report: Q1 2016
Source: BBVA Research 26
Baseline Scenario
Selective reallocation continues from EM to DMs EM flows steadily below long term trend
Baseline Market & Macro Scenario
<-2% +2%> 0%
Outflows Inflows BBVA Research Portfolio Flows Map*
The Flows Map show the monthly evolution of net
inflows withDarker blue colors representing sharp net
outflows and lighter colors standing for net Inflows
BBVA Baseline Scenario of Portfolio Flows (% monthly change in net liabilities measured as net flows to
total assets under management)
USA # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Japan # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Canada # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
UK # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Sweeden # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Norway # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Denmark # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Finland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Germany # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Austria # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Netherlands # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
France # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Belgium # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Italy # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Spain # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Ireland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Portugal # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Greece # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Poland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Czech Rep # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hungary # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Turkey # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Russia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Mexico # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Brazil # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Chile # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Colombia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
PeruPeru # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Argentina # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
China # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
IndiaIndia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Korea # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Thailand # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Indonesia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Philippines # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hong Kong # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Singapore # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
EM
Eu
r
20162012 2013 2014 2015
LA
TA
MA
sia
G4
West
ern
Eu
rop
e
Global Growth (risk to the downside)
+3.6 pp in 2016-17 avg.
+2.3 pp DM
+4.8 pp EM
Global Monetary Policy
2.3 pp & 2.9 pp 10y T-note in 2016 & 2017 EoP
0.60 pp & 0.9 pp10y Bund in 2016 & 2017 EoP
Global Risk Aversion
Stable VIX relaxes back to 20 points until 2017 EoP
EMBI resiliently elevated at 4.4 pp 2017 EoP
Flows and Assets Report: Q1 2016
Source: BBVA Research 27
Baseline Scenario
Selective reallocation continues from EM to DMs EM flows steadily below long term trend
Baseline Market & Macro Scenario
<-2% +2%> 0%
Outflows Inflows BBVA Research Portfolio Flows Map*
The Flows Map show the monthly evolution of net
inflows withDarker blue colors representing sharp net
outflows and lighter colors standing for net Inflows
BBVA Baseline Scenario of Portfolio Flows (% monthly change in net liabilities measured as net flows to
total assets under management) Global Growth (risk to the downside)
-1.0 pp below baseline in 2016-17 avg.
DM -1.0 pp below baseline
EM -1.5 pp below baseline
Global Monetary Policy
10y T-note -70 pbs below baseline on average in 2016
& 2017
Bund -60bps below baseline on average in 2016 & 2017
Global Risk Aversion
VIX remains at 24 points in 2016, 20 points end 2017 EoP
EMBI increases to 5.5 pp in 2017 EoP
USA # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Japan # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Canada # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
UK # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Sweeden # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Norway # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Denmark # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Finland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Germany # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Austria # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Netherlands # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
France # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Belgium # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Italy # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Spain # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Ireland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Portugal # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Greece # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Poland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Czech Rep # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hungary # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Turkey # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Russia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Mexico # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Brazil # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Chile # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Colombia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
PeruPeru # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Argentina # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
China # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
IndiaIndia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Korea # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Thailand # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Indonesia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Philippines # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hong Kong # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Singapore # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
LA
TA
MA
sia
G4
West
ern
Eu
rop
eEM
Eu
r
20162012 2013 2014 2015
Flows and Assets Report: Q1 2016
USA # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Japan # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Canada # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
UK # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Sweeden # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Norway # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Denmark # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Finland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Germany # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Austria # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Netherlands # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
France # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Belgium # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Italy # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Spain # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Ireland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Portugal # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Greece # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Poland # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Czech Rep # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hungary # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Turkey # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Russia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Mexico # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Brazil # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Chile # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Colombia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
PeruPeru # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Argentina # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
China # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
IndiaIndia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Korea # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Thailand # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Indonesia # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Philippines # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Hong Kong # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Singapore # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
LA
TA
MA
sia
G4
West
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Eu
rop
eEM
Eu
r
20162012 2013 2014 2015
Source: BBVA Research 28
Baseline Scenario
Selective reallocation continues from EM to DMs EM flows steadily below long term trend
Baseline Market & Macro Scenario
<-2% +2%> 0%
Outflows Inflows BBVA Research Portfolio Flows Map*
The Flows Map show the monthly evolution of net
inflows withDarker blue colors representing sharp net
outflows and lighter colors standing for net Inflows
BBVA Baseline Scenario of Portfolio Flows (% monthly change in net liabilities measured as net flows to
total assets under management) Global Growth (risk to the downside)
2.1 pp below baseline in 2016-17 avg.
DM -2.2 pp below baseline
EM -3.1 pp below baseline
Global Monetary Policy
10y T-note -140 pbs below baseline on average in 2016
& 2017
Bund -90 bps below baseline on average in 2016 & 2017
Global Risk Aversion
VIX Increases and stabilizes by 30 until 2017 & 25 in
2017 EoP
EMBI surges to 6.5 pp in 2017 EoP
Flows and Assets Report: Q1 2016
Source: BBVA Research
Scenario Conditional Flow Paths for EMs (Cumulated Baseline and alternative scenarios. Cumulative % variation of portfolio Flows, forecast as of December 2015)
Summary of Scenarios
All carry a tilt to the downside for EMs
(**)
Basline Scenario
Negative Scenario
Heightened Risk Scenario
0
100
200
300
400
500
600
700
800
900
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
(**) Original forecast intervals for the simulations made at the beginning of 2015 to compare to the current situation
Hot Topics Liquidity & Exchange Rates
Flows and Assets Report: Q1 2016
Source: BBVA Research 31
Currency dynamics are deeply linked to liquidity
position of a country. A tighter situation -be that due to
less commodity revenues or due to increased financial
severance- feeds into the expectation of reserve
depletion.
Ultimately this is predicted to trigger a depreciation of
the exchange rate as stabilization mechanism. Over the
last two years increased global financial costs (Fed
normalization, risk premia etc.) and eroding export
revenues due to commodity price cuts and weaker
global demand have stressed EMs liquidity positions.
As a result, free-floating currencies (in commodity and
non commodity exporting countries) steadily
depreciated during the same period. Though the
depreciation started before the oil price slump, financial
volatility and the commodity price cycle have
exacerbated this process
Liquidity & Exchange Rates
Emerging Markets: Liquidity Position & Exchange
Rates
We asses the risk of running short of liquidity by computing the Liquidity Risk Indicator as the share of Reserves and Trade & Capital Income relative to the amount of market liabilities (ex FDI) and short-term banking debt. A Positive value implies a margin to repay the amount of outstanding short term debt by that amount, negative value imply a shortfall of funds to repay short term debt. The chart to the right displays each country's’ liquidity position (LRI) vs. the exchange rate (FX - RHA in inverse order, right hand axis). Depreciations go along tighter liquidity historically. This process started already in 2013 before commodity prices started to decline.
Start of the Oil price Slump Q3-2014 Start of the FX depreciation (Q2-2013 or before)
2.5
3
3.5
40
10
20
30
40
50
60
Mar-
06
Mar-
07
Mar-
08
Mar-
09
Mar-
10
Mar-
11
Mar-
12
Mar-
13
Mar-
14
Mar-
15
Peru
LRI FX
1
2
3
4
5
6
720
30
40
50
60
Mar-
06
Dec-0
6S
ep
-07
Ju
n-0
8M
ar-
09
Dec-0
9S
ep
-10
Ju
n-1
1M
ar-
12
Dec-1
2S
ep
-13
Ju
n-1
4M
ar-
15
Chile
LRI FX
11.21.41.61.822.22.42.62.80
10
20
30
40
50
60
Mar-
06
Mar-
07
Mar-
08
Mar-
09
Mar-
10
Mar-
11
Mar-
12
Mar-
13
Mar-
14
Mar-
15
Colombia
LRI FX
11.522.533.5-35
-30-25-20-15-10
-50
Mar-
06
Mar-
07
Mar-
08
Mar-
09
Mar-
10
Mar-
11
Mar-
12
Mar-
13
Mar-
14
Mar-
15
Turkey
LRI FX
10
12
14
1620253035404550
Mar-
06
Mar-
07
Mar-
08
Mar-
09
Mar-
10
Mar-
11
Mar-
12
Mar-
13
Mar-
14
Mar-
15
Mexico
LRI FX
1
3
5
7
9
11-400
-300
-200
-100
0
Mar-
06
Mar-
07
Mar-
08
Mar-
09
Mar-
10
Mar-
11
Mar-
12
Mar-
13
Mar-
14
Mar-
15
Argentina
LRI FX
Useful Information
Flows and Assets Report: Q1 2016
33
Our framework is based on the belief that there are unobservable factors or channels that act at the global (GLOBAL), regional (Developed (DM), Emerging (EM) and Safe Havens (SH) and idiosyncratic (I) transmitting from the global macro economy to flows or asset prices. The origin of these shocks can be created due to monetary policy in DMs, expected growth differentials between DMs and EMs and the differential risk aversion levels arising between the latter two.
To model the behavior between flows and asset prices and these global shocks via the described channels we use a two step approach based on a Dynamic Factor Model (DFM) and its interaction to a Factor Augmented Vector Autorregresion (FAVAR)
In the first part of the model, the “Dynamic Factor Model of Portfolio Flows and Asset Prices”, we use a version of a Dynamic Factor Model. Our set-up comprises a measurement equation block (1) and a state equation block (2). Both blocks together build the so called State Space Model. In this, the measurement equation block relates each observable portfolio flow in the (Y) matrix to several unobservable “states” or latent factors (F) with varying intensities according to the estimated parameters of each flow.
Methodology and Interpreting the Results A Dynamic Factor Model / Factor Augmented VAR to analyze and forecast flows and asset prices. Reference Paper: “Monetary Policy in the North and Portfolio Flows in the South”
In the second part of the model the “Factor Augmented VAR (FAVAR) model“ we state the relation of the extracted factors with a set of macroeconomic variables in the form of a VAR structure allowing time dynamics between the three elements of the analysis: factors, macro and flows/assets.
We have chosen a set of macro variables so that the extracted factors carry strong statistical relations to the global financial cycle represented here with the EUR and US long-term rates that proxy the term premium. Also, factors and these latter variables carry strong links to the Global Risk Aversion and the Differential Risk Aversion to Emerging Markets (here gathered with the VIX and the EMBI respectively as in Rey 2012). Lastly we have analysed the relation of these variables and variables that proxy growth and growth differentials between developed and emerging markets (here as the G7 and great -EM median GDP Q/Q growth rates).
The model is estimated by means of maximum likelihood with Bayesian techniques and a prior that leverages more in the recent past in order to gauge the recent events.
Factors are forecasted conditional to the evolution of macro economic variables following the scenarios described bellow and flows are recovered back from the forecasted factors by means of the estimated measurement equation block (1) described above.
Flows and Assets Report: Q1 2016
34
The BBVA_PM: a two step DFM/FAVAR model Reference Paper: “Monetary Policy in the North and Portfolio Flows in the South”
* See Doz, Giannone, Reichlin (2006), Watson, Reis (2010), Agrippino and Rey, H.
(2013) Fratzscher 2013, Rey (2012), Puy (2013) among others
(2) Factor Augmented Model (FAVAR) to combine Macroeconomic variables and factors and Variables
(1) The Dynamic Factor Model (DFM) to extract flows (and asset prices) factors
Global & Regional Macro Shocks
Transmission Channels
(Macro & Factors)
From Factors To Fin. Variables
…… Flows assumed to conceal a structure of latent factors (L) (Global, Regional and Idiosyncratic), Each factor is orthogonal and follows an AR(p) process (f(L)). PF(t)i=b1i*Global(t)+b2i*EME(t) +bi*IDIO(t)i+U(t) (emerging) PF(t)j=b1j*Global(t)+b4i*DME(t) +bi*IDIO(t)i+U(t) (developed) PF(t)j=b1j*Global(t)+ b4i*DME(t) ++b5i*SH(t) + bi*IDIO(t)i+U(t) (SH)
1 Measurement Block Relates Factors (Ft) and Flows (Xt)
2) Transition Block allows for flows (Ft) dynamics as AR
The Noise to Signal Ratio is maximized, errors are iid.
The process is estimated using a Kalman Filter
Exploiting time relations between the extracted latent factors and a set of selected global macro variables (2) and recovering flows by means of the measurement equation block in the DFM.
SHOCK • Risk Aversion ( VIX
/EMBI) • Monetary Policy (Fed,
ECB rates) • Growth differentials
TRANSMISSION • To Global the Global
factor • To Specific Markets
(DM,EM, SH)
REACTION • Retrenchment • Reallocation • Flight to
Quality • etc.
Flows and Assets Report: Q1 2016
35
This document, prepared by BBVA Research Department, is provided for information purposes only and expresses data, opinions or estimates pertinent on the date of issue of the report, prepared by BBVA or obtained from or based on sources we consider to be reliable, which have not been independently verified by BBVA. Therefore, BBVA offers no warranty, either express or implicit, regarding its accuracy, integrity or correctness.
Estimates this document may contain have been undertaken according to generally accepted methodologies and should be considered as forecasts or projections. Results obtained in the past, either positive or negative, are no guarantee of future performance.
This document and its contents are subject to changes without prior notice depending on variables such as the economic context or market fluctuations. BBVA is not responsible for updating these contents or for giving notice of such changes.
BBVA accepts no liability for any loss, direct or indirect, that may result from the use of this document or its contents.
Disclamer
This document and its contents do not constitute an offer, invitation or solicitation to purchase, divest or enter into any interest in financial assets or instruments. Neither shall this document nor its contents form the basis of any contract, commitment or decision of any kind.
With particular regard to investment in financial assets having a relation with the economic variables this document may cover, readers should be aware that under no circumstances should they base their investment decisions on the information contained in this document. Persons or entities offering investment products to these potential investors are legally required to provide the information needed for them to take an appropriate investment decision.
The content of this document is protected by intellectual property laws. Its reproduction, transformation, distribution, public communication, making available, extraction, reuse, forwarding or use of any nature, by any means or process, are not permitted except in cases where it is legally permitted or expressly authorised by BBVA.
Flows and Assets Report: Q1 2016
BBVA Research Group Chief Economist Jorge Sicilia
Cross Ciuntry Emerging Economies Cross-Country Emerging Markets Analysis
Álvaro Ortiz Vidal-Abarca [email protected]
Asia Stephen Schwartz [email protected]
Mexico Carlos Serrano
Latam Coordination Juan Ruiz
Argentina Gloria Sorensen [email protected]
Chile Jorge Selaive [email protected]
Colombia Juana Téllez [email protected]
Peru Hugo Perea [email protected]
Venezuela Oswaldo López [email protected]
Developed Economies: Rafael Doménech [email protected]
Spain Miguel Cardoso [email protected]
Europe Miguel Jiménez [email protected]
US Nathaniel Karp [email protected]
Global Areas:
Financial Scenarios Sonsoles Castillo [email protected]
Economic Scenarios Julián Cubero [email protected]
Innovation & Processes Oscar de las Peñas [email protected]
Financial Systems & Regulation: Santiago Fernández de Lis [email protected]
Financial Systems Ana Rubio [email protected]
Financial Inclusion David Tuesta [email protected]
Regulation and Public Policies María Abascal [email protected]
Recovery and Resolution Policy José Carlos Pardo [email protected]
Contact details: BBVA Research Paseo Castellana, 81 – 7th floor 28046 Madrid (Spain) Tel. + 34 91 374 60 00 and + 34 91 537 70 00 Fax. +34 91 374 30 25 [email protected] www.bbvaresearch.com
BBVA Research Asia 43/F Two International Finance Centre 8 Finance Street Central Hong Kong Tel: +852 2582 3111 E-mail: [email protected]