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Global Markets and Flows: How is China changing the investment landscape? October 2015
Nikolaos Panigirtzoglou
Global Asset Allocation
Nikolaos Panigirtzoglou is a Managing Director. He works from London as Global Market
Strategist. He edits the weekly publication Flows & Liquidity and contributes to
JPMorgan's The JPMorgan View and Global Markets Outlook and Strategy.
He joined JPMorgan in 2004. Prior to his arrival, he worked as Financial Economist at
the Bank of England. Mr. Panigirtzoglou received a PhD from Queen Mary University of
London, an MSc in Economics from London School of Economics and MSc in Economics
and Finance from Warwick Business School. His work has been published in top
academic journals such as The Journal of Finance and Management Science.
Tactical trading themes Bonds
FX reserve depletion poses little
threat to core bond markets.
China to export deflation faster via
currency deprecation. Inflation
breakevens to stay low.
Long bias in Antipodeans.
There is juice in peripheral carry
trades.
There is more juice in EM local
bonds with GBI-EM yield at 6.8%
but this requires taking fx risk. We
instead prefer EM sovereign
external debt.
Credit
Is the credit cycle turning?
Structural credit overweights to
keep credit volatility more
elevated than in previous cycles.
Favour financials over non-
financials. Continued bank
deleveraging contrasts with non-
financial corporate shareholder
friendly activity.
ECB’s QE to benefit European
bank credit by more than other
regions. OW European credit
outright and vs. the US. .
Commodities
Little evidence of improvement in
physical oil demand/supply. Specs
have been driving recent swings.
Gold ETF flows on a downtrend.
Base metals hostage to China’s
continued downshifting.
EM
Further CNH downside. 12m fwd
CNH mispriced.
EM asset performance tied to
China and commodities.
Equities
Equities hostage to persistent
uncertainty from China.
EM equities offer highest value and look
oversold but there is little flow impetus.
Investors seek refuge to US and
European equities.
Japanese equities benefit from
continued buying by Japanese state
pension funds but proximity to China
offsets this benefit.
Financials suffer from Fed’s capitulation.
Currencies
Beyond the Fed, dollar funding
shortage creates a favourable
backdrop for the dollar.
Short EUR or JPY trade to
resume later in the year on more
ECB/BoJ activism into 2016.
EM currencies offer decent carry
and are oversold but are
hostage to CNH depreciation
expectations.
2
3
China’s capitulation(1)
China’s capital flow $bn per quarter, proxied by the change in FX reserves minus the current account balance. Last observation in red is for
July only (one month). Both July and Q2 are our estimates as balance of payments data are only available up until Q1’15.
Source: SAFE, J.P. Morgan calculations
Real effective exchange rates
(CPI based)
Source: J.P. Morgan calculations
-250
-200
-150
-100
-50
0
50
100
150
06 08 10 12 14
Deviation from
vs 10Y avg
Australia (AUD) -9.8% -9.4%
Brazil (BRL) -29.9% -33.5%
Canada (CAD) -9% -14.1%
China (CNY) 6.3% 22.4%
Euro (EUR) -3.5% -9.5%
India (INR) 6.8% 12.9%
Indonesia (IDR) 3.1% -3.1%
Japan (JPY) -3% -20%
Korea (KRW) 0.7% 2.7%
Malaysia (MYR) -14.9% -12.8%
Mexico (MXN) -14% -13.5%
Russia (RUB) -16.9% -20.5%
Singapore (SGD) -2.3% 6%
Switzerland (CHF) 6.7% 9.4%
Taiwan (TWD) -0.3% -2.7%
Thailand (THB) -2.7% -0.7%
Turkey (TRY) -13.2% -14.6%
United Kingdom (GBP) 5.1% 5.7%
United States (USD) 9.9% 8.5%
Country 12-mo Change
4
China’s capitulation(2)
Source: IMF
5
China’s capitulation(3)
Source: Bloomberg, National statistics sources in China, Alibaba
China flow indicator The flow indicator includes: Rail freight volumes, cement production, steel production, auto production,
housing starts and total loans. It is constructed by taking YoY changes in calendar quarter monthly averages
for each variable. Z-scores are then calculated for each of these variables by taking the current observation,
subtracting the average since 2006 and dividing by the standard deviation over the same historical period.
The aggregate indicator is constructed by taking an average of these z-scores.
4
5
6
7
8
9
10
11
12
13
-2,5
-2,0
-1,5
-1,0
-0,5
0,0
0,5
1,0
1,5
2,0
pro.08 lip.10 pro.11 lip.13 pro.14
China flow indicator
China YoY real GDP growth
z-score %
0,0
0,2
0,4
0,6
0,8
1,0
1,2
1,4
1,6
1,8
2,0
03 05 07 09 11 13 15
Mill
ion
s
China vehicle sales (mn, 12m average)
180
280
380
480
580
680
780
880
Q2 '12 Q4 '12 Q2 '13 Q4 '13 Q2 '14 Q4 '14 Q2 '15
Alibaba gross merchandise value (bn yuan)
-5
0
5
10
15
20
25
30
35
40
45
09 10 11 12 13 14 15
China electricity consumption yoy in %
6
China’s capitulation(4)
Source: Bloomberg, National statistics sources in China
0%
5%
10%
15%
20%
25%
98 01 05 08 12 15
China nominal GDP yoy
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
05 07 09 11 13 15
China nominal GDP change/divided by the change
in total social financing
120%
140%
160%
180%
200%
220%
01 02 03 04 05 06 07 08 09 10 11 12 13 14US Japan UK Euro area
7
Who is deleveraging?
Credit creation to the real economy across the G4 Rolling sum of 4 quarter credit creation as % of GDP. Credit creation includes both bank
loans as well as net debt issuance by non financial corporations and households.
Credit creation in major DM and EM Economies
Rolling sum of 4 quarter credit creation as % of GDP. Credit creation includes both
bank loans as well as net debt issuance by non financial corporations and HHs
Stock of household and non financial corporate
sector debt as % of GDP in G4 economies
Stock of household and non financial corporate sector
debt as % of GDP in major DM and EM economies
Source: Central bank, BIS, ICI, Barcap, Bloomberg, IMF and J.P. Morgan calculations. Last observation as of Q1’15.
50%
100%
150%
200%
250%
01 02 03 04 05 06 07 08 09 10 11 12 13 14G4 EM ex China G5 China
-10%
0%
10%
20%
30%
40%
50%
01 03 05 07 09 11 13 15
Hu
nd
red
s G4 G5 China EM ex China
-10%
-5%
0%
5%
10%
15%
20%
02 05 08 11 14
US
Japan Euro area
8
How much more capital could flee China?
• “Loans” in “foreign liabilities”: stock of $434bn
as of Q2 more than a third below its Q2 2014 peak
• “Currency and deposits” in foreign assets: $313bn
as of Q2 offsetting 70% of outstanding foreign
debt
• “Currency and deposits” in “foreign liabilities:
stock of $461bn as of Q2, 8% below its Q4 2014
peak
• “Trade credits” in “foreign assets” stood at
$455bn as of Q2 2015 rising at an annual pace of
close to 20% per year or $15bn per quarter
9
The $1.7tr oil income shift
Oil producers
-$400bn : Oil exporters cut in spending on goods and services
-$370bn : SWF/FX reserve accumulation (from +$270bn in 2014 to -$100bn in 2015)
-$200bn : Oil companies capex
+$17bn : Oil companies buybacks Oil consumers
+$150bn : Asian oil importers CA surplus increase (improved SWF/FX
reserve accumulation)
+$420bn : Residential sector income windfall
+$510bn : Industrial sector income windfall
+$510bn : Transportation sector income windfall
+$85bn : Industrial/transportation companies share buybacks
Net balance
Spending: Assuming the residential sector spends 80% of its $420bn income windfall, the industrial and
transportation sectors will need to spend at least $260bn this year to offset the $600bn spending cuts of oil
producers. This seems unlikely given weak capex trends by industrial companies YTD.
Bonds: SWF/FX reserve accumulation changes are neutral for bonds. A big portion of industrial and
transportation sector $1020bn income windfall is likely saved via bank deposits. This boosts bond demand.
Equities: SWF/FX reserve accumulation changes are negative -$170bn for equities. But $100bn of this
impact is offset by increased share buybacks. So overall flow change for equities is -$170bn.
Weaker demand and inflation globally
Source: Manufacturing PMIs from Markit
10
40
42
44
46
48
50
52
54
56
58
60
07 08 09 10 11 12 13 14 15
Global manufacturing PMI - output prices
40
42
44
46
48
50
52
54
56
58
60
03 04 05 06 07 08 09 10 11 12 13 14 15
EM PMI
DM PMI
11
The commodity downfall
Commodity prices GSCI Reduced Energy spot index (around 50% weight on Energy)
Source: Bloomberg
Commodity equity sectors Relative price index
100
200
300
400
500
600
700
800
00 02 04 06 08 10 12 14
GSCI Reduced Energy spot index
(around 50% weight on Energy)
50
100
150
200
250
300
00 02 04 06 08 10 12 14
Energy vs.
MSCI World
Materials vs.
MSCI World
12
Oil specs behind recent swings
Net spec positions on Brent and WTI futures contracts Net spec positions divided by open interest. CFTC futures positions for WTI and Brent are net long
minus short for the Managed Money category.
WTI oil skew Skew is the difference between the implied volatility of out-of-the-money
(OTM) call options and put options. A positive skew implies more demand for
calls than puts and a negative skew, higher demand for puts than calls. The
chart shows z-score of the skew, i.e. the skew minus a rolling 2-year avg skew
divided by a rolling two-year standard deviation of the skew.
Source: CFTC, Bloomberg Source: J.P. Morgan
0%
5%
10%
15%
20%
25%
12 13 14 15
Brent WTI
Last observation: 13-Oct-15
-8
-6
-4
-2
0
2
4
6
08 09 10 11 12 13 14 15
13
Which oil metrics to watch?
All prices are in $
Spot=Forward Dated Brent/BFOE which reflects the price of North
Sea Crude cargoes loading in 10-25 days from today and represents a
notional cash contract
Source: Bloomberg, J.P. Morgan
40
50
60
70
80
90
100
110
120
-5
-3
-1
1
3
5
Jan-14 May-14 Sep-14 Jan-15 May-15 Sep-15
Brent 1st contract
Spot-Brent 1st contract
-3
-2
-1
0
1
2
3
4
5
Jan-14 May-14 Sep-14 Jan-15 May-15 Sep-15
Saudi Aramco export price
discount to Asia destination
vs. Oman/Dubai average
35
45
55
65
75
85
95
105
115
Jan-14 May-14 Sep-14 Jan-15 May-15 Sep-15
WTI 1st contract
WTI 18th contract
14
How oversold is EM?
Spec position indicator of risky vs. safe
currencies as a contrarian Rule 2
Excess return indices
EM share in equity ETFs over EM share in the
MSCI AC World index
EM share in bond ETFs over EM share in JPM’s GABI
(global bond) index
Share of EM in US investors’ foreign equity holdings
minus the equivalent share within global equity
indices
%
Source: Bloomberg, CFTC, Datastream, US TIC, J.P. Morgan.
-8,0%
-7,5%
-7,0%
-6,5%
-6,0%
-5,5%
12 13 14 15
80
100
120
140
160
180
200
220
kol.06 vlj.08 kol.09 vlj.11 kol.12 vlj.14 kol.15
MSCI EM vs World
ELMI
30%
40%
50%
60%
70%
80%
90%
100%
06 07 08 09 10 11 12 13 14 15
EM bond ETF share over EM bond index
share in the world
60%
80%
100%
120%
140%
160%
180%
05 06 07 08 09 10 11 12 13 14 15
EM equity ETF share over EM equity index
share in the world
China’s margin debt still unwinding
Outstanding balance of margin
transactions as % of the free float of
Shanghai Stock Exchange
China-HK North South Flows, $bn
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
ruj.12 svi.13 sij.14 ruj.14 svi.150
5
10
15
20
25
30
stu 14 sij 15 ožu 15 svi 15 srp 15 ruj 15
Southbound Northbound
16
EM and commodity currencies still oversold vs. safe currencies Weekly Spec Position Monitor Net spec positions are the number of long contracts minus the number of short using CFTC
futures only data. This net position is then converted to a USD amount by multiplying by the
contract size and then the corresponding futures price. To proxy for speculative investors,
commodity positions use the managed money category, while the other assets use the non-
commercial category. The chart shows the z-score of these net positions, i.e. the current
net position minus the average over the whole sample divided by the standard deviation of
the weekly positions over the whole sample. US rates is a duration weighted composite of
the individual UST series plus the Eurodollar contract. The sample starts on the 13th of June
2006.
Difference between net spec. position indicator
in Risky vs. Safe currencies Difference between net spec positions on risky & safe currencies : Net spec position is
calculated in USD across 5 "risky" and 3 "safe“ currencies (safe currencies also include
Gold). These positions are then scaled by open interest and we take an average of "risky"
and "safe" assets to create two series. The chart is then simply the difference between the
"risky" and "safe" series. The final series shown in the chart below is demeaned using data
since 2006. The risky currencies are: AUD, NZD, CAD, RUB, MXN and BRL. The safe
currencies are: JPY, CHF and Gold.
Source: Bloomberg, CFTC, J.P. Morgan
Source: Bloomberg, CFTC, J.P. Morgan
17
Fed capitulation(1)
Source: Fed, Bloomberg, J.P. Morgan
1-month OIS rates vs. FOMC projections
FOMC projections are truncated by removing the top three of individual FOMC
projections
Forward 1-month USD OIS rates
FOMC projections are truncated by removing the bottom three and top three of
individual FOMC projections
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Dec-12 Jun-13 Dec-13 Jun-14 Dec-14 Jun-15
Dec-15, Dec-16 and Dec-17FOMC forecasts after truncating the top three dots
OIS rate Dec-16
OIS rate Dec-15
OIS rate Dec-17
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Dec-15 Dec-17 Dec-19 Dec-21 Dec-23
1 May 2013
5-Sep-2013
19 Oct 2015
18
Fed capitulation(2)
Source: Fed
The Fed dots FOMC projections of the unemployment rate
Average of central tendency forecasts
5.0
5.2
5.4
5.6
5.8
6.0
6.2
6.4
6.6
Sep12 Mar13 Sep13 Mar14 Sep14 Mar15 Sep15
Long run unemployement rate
2015 unemployement rate
19
Is inflation rising?
Source: Bloomberg
-40
-30
-20
-10
0
10
20
30
40
50
08 10 12 14
G10 inflation surprise index
EM inflation surprise index
1,3
1,5
1,7
1,9
2,1
2,3
2,5
2,7
2,9
04 05 06 07 08 09 10 11 12 13 14 15
Euro Inflation swap 5y5y
1,0
1,5
2,0
2,5
3,0
3,5
4,0
01 03 05 07 09 11 13 15
US ECI wage private industry workers YoY
0,0
1,0
2,0
3,0
4,0
5,0
6,0
01 03 05 07 09 11 13 15
UK regular pay whole economy 3m avg YoY
20
2015 bond supply vs. demand
Global bond demand Annual flow in $bn by investor type.
Bond buying by G4 commercial banks
3-month rolling sum in $bn, last obs is Jul 2015.
Global bond supply
$bn p.a. 2015 denotes JPM forecast. Only external debt is used for EM bond supply.
Annual change in excess bond supply (i.e. gap
between supply and demand)
Excess bond supply in $bn p.a. in the left axis calculated by the difference
between the demand estimates of Figure 1 and the supply estimates of Figure 3.
Right axis shows the annual change of the yield on the Barcap Global Agg index in %
Source: Central bank sources, ICI, Barcap, Bloomberg, IMF and J.P. Morgan calculations
-1000
0
1000
2000
3000
4000
5000
06 07 08 09 10 11 12 13 14 15
G4 central banks Foreign officialG4 commercial banks Bond funds/RetailPension/Insurance Total
-1000
0
1000
2000
3000
4000
06 07 08 09 10 11 12 13 14 15
DM Govt Spread product
-0,9
-0,6
-0,3
0,0
0,3
0,6
0,9
-800
-400
0
400
800
07 08 09 10 11 12 13 14 15
Excess supply changeYield change
-300
-200
-100
0
100
200
300
400
500
600
11 12 13 14 15
21
4 reasons EM FX reserve depletion poses little risk to overall bond demand
1) The capital flows out of EM could find their way into DM bonds. In
particular, the accumulation of dollar deposits, which is by now a
widespread phenomenon across EM economies, is likely to find its way
into USD dominated bonds via the banking system.
2) The uncertainty that China induces to global growth and inflation outlook
is likely to influence G4 central bank policy. Potentially more QE from
the ECB or the BoJ could eventually boost bond demand.
3) The recent market correction and the rise in volatility and uncertainty is
creating a natural support for bonds by asset allocators who had
previously accumulated too much of equity risk.
4) The rise in volatility and uncertainty is already hurting bond supply. Up
until August, USD issuance is only 3% higher from last year’s pace. As a
result USD issuance is no longer able to offset the 20% YoY decline in non-
USD denominated issuance.
22
Correlations matter
Source: 3-month correlation of daily
returns, J.P. Morgan, Bloomberg
-90%
-70%
-50%
-30%
-10%
10%
30%
50%
70%
90%
srp.93 srp.96 srp.99 srp.02 srp.05 srp.08 srp.11 srp.14
Govt. bond-equity correlation
MSCI World Local vs. GBI Global hedged into USD
40%
50%
60%
70%
80%
90%
100%
srp.07 srp.08 srp.09 srp.10 srp.11 srp.12 srp.13 srp.14 srp.15
Credit-equity correlation
CDX.IG 5y vs. MSCI World Local
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
srp.93 srp.96 srp.99 srp.02 srp.05 srp.08 srp.11 srp.14
Commodity-equity correlation
MSCI World local vs GSCI spot index
-100%
-80%
-60%
-40%
-20%
0%
20%
40%
60%
80%
srp.93 srp.96 srp.99 srp.02 srp.05 srp.08 srp.11 srp.14
Dollar-equity correlation
DXY vs. MSCI World Local
Volatility has bottomed out
23
Implied vol across 5 asset classes
Weighted average of 12 implied vols across 5 asset classes. We
apply a 20% weight on each of the five asset classes. The 11 implied
vols used were: V2X Index, VIX Index, VNKY Index, JPMVXYG7 Index,
Cl1 Comdty, HG1 Comdty, GC1 Comdty, C 1 Comdty, iTraxx,
CDX.IG, Euro 10y swap rate, US 10y swap rate
Source: Bloomberg, J.P. Morgan
10
15
20
25
30
35
40
45
50
55
07 08 09 10 11 12 13 14 15
24
Who has de-risked?
CTAs’ beta to bonds and equities
21-day rolling betas based on a bivariate regression of the daily returns of the
HFRXSDV index to the daily returns of the MSCI AC World and Barcap Global Agg $
indices
Risk parity funds’ beta to bonds and equities
21-day rolling betas based on a bivariate regression of the daily returns of our risk
parity fund return index to the daily returns of the MSCI AC World and Barcap Global
Agg $ indices.
Equity beta of Balanced mutual funds
21-day rolling betas based on a bivariate regression of the daily returns of our
risk parity fund return index to the daily returns of the MSCI AC World and
Barcap Global Agg $ indices
Source: Bloomberg, J.P. Morgan.
Equity beta of Discretionary Macro HFs
21-day rolling betas based on a bivariate regression of the daily returns of our
risk parity fund return index to the daily returns of the MSCI AC World and
Barcap Global Agg $ indices
-0,5
0,0
0,5
1,0
1,5
ožu tra svi lip srp kol ruj lis
Beta to bonds
Beta to equities
-1,5
-1,0
-0,5
0,0
0,5
1,0
1,5
2,0
0,0
0,2
0,4
0,6
ožu tra svi lip srp kol ruj lis
Beta to bonds
Beta to equities
-0,2
0,0
0,2
0,4
0,6
ožu tra svi lip srp kol ruj lis
Macro Discretionary
0,50
0,55
0,60
0,65
0,70
0,75
0,80
Jan-14 May-14 Sep-14 Jan-15 May-15 Sep-15
25
How low is market depth?
Average trade size in US off-exchange
trading venues 000s of US$. Average trade size is equal to trading volume in $ divided
by the number of trades. Last observation is Sep’15.
Source: World Federation of Exchanges, J.P. Morgan
Market depth in 10y US Treasuries 5-day average of tightest three bids and asks each day, measured in
$mn for 10y US Treasuries.
Average trade size in equity exchanges 000s of US$. Average trade size is equal to trading volume in $ divided by
the number of trades. Last observation is Sep‘15.
Average trade size in US corporate bond trading 000s of US$. Average trade size is equal to trading volume in $ divided by the
number of trades. Last observation is Jun’15
Source: FINRA Trace, J.P. Morgan.
Source: BATS Global Markets, J.P. Morgan calculations. Source: J.P. Morgan.
7
8
9
10
11
12
13
14
09 10 11 12 13 14 15
Th
ou
sa
nd
s
0
100
200
300
400
500
600
07 08 09 10 11 12 13 14 15
300
400
500
600
700
800
900
06 08 10 12 14
Tho
usa
nd
s
IG HY
0
5
10
15
20
04 06 08 10 12 14
Tho
usa
nd
s DM
China/HK
EM ex-China
26
Has global liquidity peaked?
Real global money supply (actual) vs. demand
(fitted)
Real money supply (actual) vs. demand (fitted) Dependent Variable: M2/CPI, Method: Least Squares, Sample (adjusted):
1990M01 2014M10, Included observations: 296 after adjustments
Economic policy uncertainty proxy
Global monthly index based on US, Europe, Japan and China proxies as
constructed by Baker, Bloom and Davis www.policyuncertainty.com. We smooth
the series by applying a Hodrick Prescott filter with a lambda parameter of 100.
Source: Policyuncertainty.com, J. P. Morgan
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
90 93 96 99 02 05 08 11 14
Actual
Fitted
Variable Coeff Std Error t-stat Prob
constant -0.18 0.02 -11.20 0.00
Nominal GDP
ov er CPI0.81 0.07 12.20 0.00
Bonds/Equities
market cap
ov er CPI
0.15 0.03 5.10 0.00
Uncertainty 5.38 0.74 7.25 0.00
0
50
100
150
200
250
sij.90 sij.95 sij.00 sij.05 sij.10 sij.15
-0,06
-0,04
-0,02
0,00
0,02
0,04
0,06
90 94 98 02 06 10 14
M2 /CPI Residual: Actual minus Fitted
27
Asset reflation
Source: Bloomberg, ICI, J.P. Morgan
Difference between flows into Equity and Bond
funds
$bn per week. Flow includes US domiciled Mutual Fund and globally domiciled ETF
flows. Current week data only includes ETF flows. The thin blue line shows the 4-
week average of this difference. The thick black line shows a smoothed version of
the same series. The smoothing is done using a Hodrick-Prescott filter with a
Lambda parameter of 100.
Source: ICI, EFAMA, Bloomberg, J.P. Morgan
Global equity & bond fund flows
$bn per year. Flows include global MF and ETF flows. MF flows are from ICI
(global flows up to Q2’15 is from ICI and data since then up to now is
combination of EFAMA and ICI). ETF flows are from Bloomberg.
28
Investors are overweight equities vs. bonds
Source: US Flow of Funds, J.P. Morgan
Equity allocations of US households %, sum of equities held directly or via mutual fund shares or via Defined
Contribution plans divided by total financial assets. Latest obs. is for Q2’15.
Source: ICI, Bloomberg, J.P. Morgan
Equity fund AUM share as % of AUM of all fund
assets (mutual funds and ETFs), worldwide and
US domiciled
% , last obs. is for Q2’ 2015
10%
15%
20%
25%
30%
35%
40%
45%
52 62 72 82 92 02 1220%
25%
30%
35%
40%
45%
50%
55%
60%
65%
90 93 96 99 02 05 08 11 14
US
Worldwide
29
Are equities expensive?
Equity allocation of US households S&P500 real EPS growth
S&P500 ERP (in %) = Equity Discount Rate-Real 10y UST yield S&P500 fair value value
Source: Fed, J.P. Morgan
0
400
800
1200
1600
2000
2400
90 92 94 96 98 00 02 04 06 08 10 12 14
S&P500 actual
S&P500 fair value
-0.10
-0.05
0.00
0.05
0.10
0.15
56 60 64 68 72 76 80 84 88 92 96 00 04 08 12
delivered growth expected growth over next 5 years
-2
0
2
4
6
8
56 61 66 71 76 81 86 91 96 01 06 11
S&P500 ERP
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
52 57 62 67 72 77 82 87 92 97 02 07 12
actual
fitted
When to hedge equity risk (1)?
Equity Valuation: Hedge when the deviation from fair
value is greater than half a standard deviation and
stop hedging when prices fall below their fair value.
This signal was successful (i.e. equity returns were
negative when the model signaled expensive
valuations) during 10 out of 18 times since 1960s for
the S&P500 index.
Credit Signal: the 4 quarter change in US interest
expense to corporate profits is greater than one
percentage point and the 4 quarter change in US HG
credit spreads is greater than 20bps. Exit equity hedge
when the above condition no longer holds.
Credit signals were able to successfully time (i.e.
equity returns were negative when the credit metrics
recommended hedging) only three declines in the S&P
500 since 1970s. Over the recent history, we can see
that the credit signal was successful in timing the two
major cycles of the equity markets.
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
58 63 68 73 78 83 88 93 98 03 08 13
Periods of hedging as indicated by the S&P500 valuation
signal
**Shaded regions are periods of hedging as indicated by the signals.
The blue line depicts the S&P 500 on log scale.
Periods of hedging as indicated by credit signals
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
70 75 80 85 90 95 00 05 10 15
When to hedge equity risk (2)
Combined signal recommends hedging when both
our equity valuation signal and credit signals are
turned on and stops when both are turned off.
This combined signal was successful (i.e. equity
returns were negative when the model
recommended hedging) during 4 out of 7 episodes
since 1974 for the S&P500 index.
Performance of the combination of the equity valuation and credit
signals
Enter hedge when both credit signal is on and deviation fromFV>0.5sigma
and exit when both credit off and valuation goes below FV
Returns during this period
Start date End Date S&P500
MSCI AC
World VIX level
Jan-75 Jul-76 33%
Jul-80 Sep-81 -2%
Oct-82 Mar-84 25%
Mar-87 Apr-87 -3%
Feb-91 Jul-93 28% 18% 22
Jun-98 Jul-02 -22% -22% 20
Oct-07 Jan-09 -44% -46% 18
Periods of hedging as indicated by our combination of the equity
valuation and credit signals
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
58 63 68 73 78 83 88 93 98 03 08 13
**Shaded regions are periods of hedging as indicated by our combination of the
equity valuation and credit signals. The blue line depicts the S&P 500 on log scale:
32
EPS growth and PE multiples across regions
12m forward EPS growth (% yoy in local terms,
EM is in $)
12 month forward PE multiple trend
Source: Datastream, J.P. Morgan. Last obs. Sep 15
-30%
-20%
-10%
0%
10%
20%
30%
srp 11 tra 12 sij 13 lis 13 srp 14 tra 15
US
Euro
Japan
EM
5
10
15
20
06 08 10 12 14
US Euro
Japan EM
33
Source: Bloomberg, Datastream, J.P. Morgan. Last obs. Sep 2015
Japan US, Europe and EM
US and Japanese profit margin at historical highs. European profit margins fail to expand. Profit margins: 12-month trailing EPS divided by Sales-per Share
0,01
0,03
0,05
0,07
0,09
0,11
0,13
06 07 08 09 10 11 12 13 14 15
S&P500
MSCI Europe
MSCI EM
-0,02
-0,01
0
0,01
0,02
0,03
0,04
0,05
0,06
95 97 99 01 03 05 07 09 11 13 15
MSCI Japan
Is the credit cycle turning?
US High Grade Credit US High Yield Credit and default rates
34
Source: J.P. Morgan, Barclays
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
200
400
600
800
1000
1200
1400
1600
1800
2000
87 91 95 99 03 07 11 15
bp
Last observation: 20-Oct-15
0
50
100
150
200
250
300
350
400
450
500
550
600
73 77 81 85 89 93 97 01 05 09 13
bp
Last observation: 20-Oct-15
35
How overweight credit are investors?
Share of the global bond universe owned by banks,
i.e. central and commercial banks
Global bond universe is proxied by the $50tr market value of Barcap’s Multiverse
Bond Index augmented by Munis and Inflation linked bonds. Central banks include G4
central banks and FX reserve managers. Commercial banks include G4 commercial
banks only
Share of bonds owned by non-bank entities globally
As % their combined bond and equity holdings. Non bank entities exclude G4 central
banks, FX reserve managers and G4 commercial banks.
Credit overweight of non-bank entities globally
Percentage of non-government related bonds in non-bank investors’ bond
portfolios minus percentage of non-government related bonds in the tradable
bond universe of the Barcap Multiverse index augmented by Munis and Inflation
linked bonds.
Source: Fed, BoJ, BoE, ECB, IMF, Barcap, Datastream, Bloomberg, J.P. Morgan
-5%
0%
5%
10%
15%
20%
25%
06 08 10 12 14 16
Projection
0%
10%
20%
30%
40%
50%
60%
02 04 07 10 13 15
central banks + commercial banks
central banks
20%
25%
30%
35%
40%
45%
02 04 06 08 10 12 14
Interest expense to cash flows for G4 non-financial
corporates
G4 includes US, Euro area, UK and Japan. G4 starts in 1999. Last Obs. is Q2’15
5%
10%
15%
20%
25%
30%
35%
40%
90 94 98 02 06 10 14
G4
US
36
Euro area’s inflation challenge
Harmonised competitiveness indicator
based on unit labour costs indices for the total economy. The purpose of HCIs is
to provide consistent and comparable measures of euro area countries' price and
cost competitiveness that are also consistent with the real effective exchange
rates (EERs) of the euro. The HCI of a specific country takes into account both
intra and extra-euro area trade.
Source: ECB Source: IMF Fiscal Monitor April 2015
Germany
Greece
Spain
Ireland
France
ItalyPortugal
80
90
100
110
120
130
140
99 01 03 05 07 09 11 13-2.6
-2.1
-1.6
-1.1
-0.6
-0.1
0.4
0.9
1.4
1.9
2006 2008 2010 2012 2014 2016 2018
Euro area: cyclical adjusted primary balance as % GDP
37
Does Euro area look like Japan?
Credit growth
Oya change of the stock of total credit extended to the real economy, i.e.
households and non-financial corporations, either via bank loans or via debt
issuance in debt capital markets. Quarterly data. Last obs. is for Q1’15.
65+ dependency ratios
Elderly population (age 65 and over) as percent of total population
Non- financial corporate surplus as % of GDP
Surplus is defined by the difference between cash flows and capex. Last obs. is
for Q1’15
Bond allocation of pension funds and insurance
companies
Percentage of assets. It includes both public and private defined benefit and defined
contribution plans as well as insurance companies.
Source: SWF Institute, IMF, BIS, OECD, J.P. Morgan
30%
40%
50%
60%
70%
80%
99 01 04 07 10 12
Japan
Euro area
US
10
15
20
25
30
35
40
1980 1990 2000 2010 2020 2030 2040 2050
Japan
US
Euro area
-9,0%
-4,0%
1,0%
6,0%
80 86 92 98 05 11
Euro area
Japan
US
-10%
-5%
0%
5%
10%
15%
20%
81 84 87 90 93 96 99 02 05 08 11 14
US Japan Euroarea
38
Shortage in dollar funding
Source: Central banks, Bloomberg, J.P. Morgan
50
60
70
80
90
100
110
120
130
70 74 78 82 86 90 94 98 02 06 10 14
Yen
60
80
100
120
140
160
180
70 74 78 82 86 90 94 98 02 06 10 14
Latam
EM Asia-ex China
EM Europe
90
100
110
120
130
140
70 74 78 82 86 90 94 98 02 06 10 14
G6
Dollar FX basis In bps. Weighted average of the 5y basis of 8 USD pairs: EUR, JPY, GBP, CAD,
AUD, CHF, KRW, MXN. The weights are based on the Bloomberg BBDXY Index.
-60
-50
-40
-30
-20
-10
0
10
04 06 08 10 12 14
Long-term (2-year) opportunities
Bonds
Long US high yield bonds
Hold 5s/30s US Treasury curve
flattener.
Long in 4Y Cypriot government bonds.
Long 8Y Italy vs. Germany.
Long 5Yx5Y US breakevens.
Receive 1Yx2Y NZD swaps vs. USD
swaps.
Credit
Enter DI Jan19/Jan23 DI steepeners
in Brazil.
UW CLP rates within GBI-EM.
Buy European Corporate Hybrids.
Long AAA CLOs.
Buy protection on Crossover S22 20-
35% tranche as a cheap market
hedge.
Long risk iTraxx Main S21 Jun-17 0-
3%.
Long risk 35-100% Crossover vs 35-
100% CDX.HY Dec-19.
Long Brazilian breakeven position.
Mexico: Hold 7Y breakevens in
UDI/TIIE swaps.
Currencies
Short in AUD vs USD.
Shorts in NZD vs. SEK and GBP.
Long INR vs SGD.
Short in AUD/MXN.
Equities
OW Eurozone vs. US equities, FX
hedged.
OW Eurozone vs. UK equities.
OW Topix vs. MSCI World.
OW banks within Euro area equities i.e.
long SX7E vs. SX5E.
Styles: OW High Quality/Low Volatility
within US.
Long US Housing Recovery
(JPAMHOUS) vs S&P 500.
Prefer Large-cap over Small-cap in US.
Buy SMid vs. Large caps in the
Eurozone.
Long Semiconductor sector in US vs.
S&P500.
OW MSCI EMU Small Cap vs the FTSE
250.
OW European SMid vs. US SMid.
Long in MSCI EAFE 2Y volatility vs.
short in S&P 500.
Take advantage of high funding spreads
for Euro STOXX 50 long-dated TRS.
Long Euro STOXX 50 3Y ATMF calls.
39 For more details see “Trade opportunities for long-term investors”, Nikolaos Panigirtzoglou, Oct 2015.
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