Global Asset Allocation 18 July 2014

Flows & Liquidity - Shorter Version How diversified are FX reserve managers? 

The slower reserve accumulation by China in Q2 is offset by faster accumulation by other EM countries.

Global Asset Allocation



Global FX reserves likely exceeded $12tr at the end of June, while SWF assets exceeded $6.6tr.

(44-20) 7134-7815 [email protected]



FX reserve managers stopped diversifying away from G4 currencies since Q1 2013.

Mika Inkinen



We calculate that the purchases of non-G4 currencies declined to almost zero in Q1 2014, the lowest since 2009.

J.P. Morgan Securities plc



Diversification is not only a function of the allocation to non-core currencies but also a function of volatilities and correlations.



Our measure of FX diversification, proxied by the ratio of the average variance of the individual currencies in the reserve portfolio divided by the overall portfolio variance, is close to historical averages currently.



The current currency composition of FX reserve managers’ appears misaligned both relative to an optimized portfolio allocation and relative to the share of various currencies in world payments.



FX reserve managers would be “better off” by raising their allocations to EUR, GBP and “Other” currencies such as SEK, NOK, NZD, CNY and EM currencies, at the expense of USD.



SWFs have boosted asset diversification by a lot more than FX reserve managers have diversified across currencies.



The cumulative inflow into EM bond ETFs surpasses its previous May 2013 peak.



The equity betas of HFs continue to climb reaching the previous highs seen at the beginning of 2011.

 China announced this week a $42bn increase in FX reserves in Q1, a third of its Q1 pace. The slowing in Chinese reserve accumulation shows that last February’s PBoC currency intervention did manage to eventually deter speculative inflows into Chinese renminbi in the second quarter. But the slower reserve accumulation by China in Q2 is offset by faster accumulation by other countries. From our sample of 22 EM countries which report their reserves weekly or monthly and which account for $7.8tr or two thirds of global FX reserves, we calculate that the reserves of 21 EM countries ex China went up by $67bn in Q2 following a decline of -$37bn in Q1. So the FX reserves of all these 22 EM countries including China rose by $20bn faster in Q2 (+$110bn) relative to Q1 (+$90bn).  In Q1, the quarterly flow, i.e. the accumulation adjusted for currency changes, of all FX reserves including countries outside the above 22 EM countries, is estimated to have been close to $160bn. Adding $20bn to this quarterly flow, we estimate the Q2 quarterly flow at $180bn implying that global FX reserves exceeded $12tr at the end of June.

See page 16 for analyst certification and important disclosures.

Nikolaos Panigirtzoglou

AC

J.P. Morgan Securities plc (44-20) 7742 6565 [email protected]

Matthew Lehmann (1-212) 834-8315 [email protected] J.P. Morgan Securities LLC

Nandini Srivastava (44-20) 7742-6183 [email protected] J.P. Morgan Securities plc

Jigar Vakharia (91-22) 6157-3281 [email protected] J.P. Morgan India Private Limited

Figure 1: Quarterly flow of global FX reserves FX reserve accumulation adjusted for currency changes in $bn per quarter 400

Quarterly flow of global FX reserves

300 200 100 0 -100 -200

99

02

05

08

11

14

Source: IMF. J.P. Morgan calculations

www.jpmorganmarkets.com

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

 That is, reserve accumulation is currently tracking an annual pace of close to $700bn. This is half the historical peak accumulation of $1.4tr per annum seen in 2007, but it is still robust by historical standards (Figure 1). In all, a temporary slowing in Chinese reserve diversification in Q2 does little to alter our projection that FX reserve managers and SWFs assets together will approach $20tr by year end. SWFs assets grew by $500bn in the first half of the year to $6.6tr, i.e. they track an annual growth pace of $1tr currently. SWFs assets are likely to exceed $7tr by year end.  But despite a robust pace of reserve accumulation over the past year, the performance of FX carry, i.e. G10 high yielders and EM currencies, had been rather weak, at least up until the beginning of this year. Is this because FX reserve managers stopped diversifying away from G4 currencies? One way of answering this question is to look at the currency composition of FX reserves using IMF’s COFER data. These data show that FX reserve diversification away from G4 currencies took off in the second half of 2009. Figure 2 shows that the share of non-G4 currencies started rising rapidly in Q3 2009, from just above 2%, and peaked at 7% in Q1 2013. But over the past year this share stopped increasing suggesting that there has been reduced appetite by FX reserve managers to accumulate non-G4 currencies i.e. currencies such as AUD, CAD, CHF, NOK, SEK, NZD and EM. By looking at flows, we calculate that the purchases of non-G4 currencies declined to only $2bn in Q1 2014, the lowest since 2009 (Figure 3). Given that these non-G4 currencies typically involve high yielders, the above evidence suggests that reduced buying by FX reserve managers might have been a reason behind the poor performance of FX carry strategies up until early this year. With the exception of New Zealand, the poor macro backdrop of most non-G4 economies over the past year, likely weighed on FX reserve managers’ appetite for G10 high yielders and EM currencies.  Diversification is not only a function of the allocation to non-core currencies but also a function of volatilities and correlations between the individual currencies. Portfolio variance can be reduced by increasing the number of currencies in the reserve portfolio or by a proper selection of currencies such that the average covariance and correlation among currencies in the portfolio is low. One measure of diversification is the ratio of the average variance of the individual currencies in the reserve portfolio divided by the overall portfolio variance. The ratio is constructed by looking at the average variance of eight currencies vs. the USD: USD, GBP, JPY, CHF, EUR, AUD, CAD and “Other”. “Other” is assumed to be an equally weighted average of five currencies: SEK, NOK, NZD, CNY and JPM EM currency index. The variance of the above eight currencies is multiplied by their respective weights according to COFER data currency composition to calculate the average currency variance. This average currency variance is then divided by the variance of the overall portfolio to arrive at the diversification index. Variances are calculated based on daily currency returns over one-year rolling periods. Our diversification index is shown in Figure 4. A higher ratio implies more diversified currency portfolios.  The current reading at 4.1x implies that the average currency variance is four times larger than the overall portfolio variance, so there is a decent degree of diversification. Our diversification index fell between 2009 and mid 2012 due to higher cross currency correlations, despite a higher allocation by FX reserve managers to non-G4 currencies. The diversification index rose significantly between mid 2012 and end 2013 helped by Abenomics and the change in yen correlations, but declined this year. Relative to historical standards, our diversification index currently stands at a rather average level. The index peaked in 2000 when the average pairwise correlation between various currency pairs was record low (Figure 5).  How misaligned is FX reserve managers’ currency composition currently 1) 2

Figure 2: Share of non-G4 currencies in stock of FX reserves 8%

Share of non-G4 currencies in stock of FX reserves

7% 6% 5% 4% 3% 2% 1%

99

02

05

08

11

14

Source: IMF COFER, J. P. Morgan

Figure 3: Purchases of non-G4 currencies by FX reserve managers $bn per quarter

80 Purchases of non-G4 currencies in $bn per quarter

70 60 50 40 30 20 10 0 -10 -20

99

02

05

08

11

14

Source: IMF COFER, J.P. Morgan calculations

Figure 4: FX reserve portfolio diversification index Variances are calculated based on daily currency returns over one-year rolling periods. See text for more details.

6.5

Average currency variance / Portfolio variance

6.0 5.5 5.0 4.5 4.0 3.5 3.0

99

02

05

08

Source: IMF COFER, J. P. Morgan calculations

11

14

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

relative to an optimal portfolio allocation or 2) relative to the share of various currencies in world payments? To answer the first question, we apply a BlackLitterman portfolio optimization exercise where the benchmark or starting point is the latest COFER currency composition and where we project carry like returns for the short term bonds of the above eight currencies over the next year. The variance covariance matrix is based on the monthly returns over the past five years. The optimal portfolio weights are shown in Figure 6 along with the latest COFER currency composition. The message from Figure 6 is that FX reserve managers would be better off in terms of their risk/return tradeoff by raising their allocations to EUR, JPY, GBP and “Other” currencies at the expense of the USD. As mentioned above “Other” includes currencies such as SEK, NOK, NZD, CNY and other EM. According to this Black-Litterman portfolio optimization exercise, the optimal USD allocation is less than half of the current USD allocation of 61%.  To answer the second question we use the latest May 2014 data by SWIFT on the share of various currencies in world payments. The Society for Worldwide Interbank Financial Telecommunication (SWIFT) records a vast amount of trade transactions and payments using its platform and thus provides a timely snapshot of the currency composition of global trade. The SWIFT currency shares are shown in Figure 7 along with the latest COFER currency composition. Similar to Figure 6 FX reserve managers should have a higher allocation to EUR, GBP and “Other” currencies. Different to Figure 6 though, Figure 7 points to a lower rather than higher weight on JPY vs. current FX reserve managers’ allocation.  Another way of looking at diversification is across asset classes rather than across currencies. FX reserves managers invest typically 80% of their assets in long term debt and 15% in short term debt. The rest is split between Bank Deposits and Equities. Within bonds they can invest in Treasuries, Agencies and Corporate bonds. US TIC data, released this week, provide a detailed picture of asset holdings of official institutions, i.e. FX Reserve Managers and Sovereign Wealth Funds. As of April 2014, these official institutions held 14% of their US portfolio in US Equities, 64% in UST bonds, 8% in Agency bonds, 3% in corporate bonds and the rest 11% in short term debt including bank deposits. To measure the degree of diversification of the US asset portfolio of these official institutions, we calculate the ratio of the average variance of the above five US asset classes over the variance of the overall US portfolio of these official institutions. Because these assets are confined to the US only, this portfolio diversification index is not affected by currency changes and only captures asset class diversification.

Average pairwise correlation of EURUSD, GBPUSD, JPYUSD, CHFUSD, AUDUSD and CADUSD. Correlations are calculated based on daily currency returns over one-year rolling periods.

70% 60% 50% 40% 30% 20%

Average pairwise correlation of EURUSD, GBPUSD, JPYUSD, CHFUSD, AUDUSD and CADUSD

10% 0%

99

02

05

08

11

14

Source: Bloomberg, J. P. Morgan calculations

Figure 6: Current currency composition of FX reserve managers vs. “optimal” “Optimal” weights are based on a Black-Litterman portfolio optimization exercise where the benchmark or starting point is the latest COFER currency composition and where we project carry like returns for the short term bonds of the above eight currencies over the next year. The variance covariance matrix is based on the monthly returns over the past five years.

0.7 0.6

FX reserve share (latest COFER data)

0.5 Optimized portfolio weights

0.4 0.3 0.2 0.1

Other

CAD

AUD

CHF

JPY

GBP

EUR

0

USD

 Figure 8 shows this US asset diversification index over time. Helped by a higher allocation to equities (from 8% in 2009 to 14% in 2014) and a negative correlation between bonds and equities, this US asset diversification index has risen steadily in recent years. It currently stands at the highest level ever. The caveat is that this asset diversification index includes the assets of both reserve managers and SWFs and that it is confined to holdings of US assets only. That is, the rise in the asset diversification index of Figure 8 is mostly driven by SWFs which are the official institutions mostly invested in equities. With this caveat in mind, the message from Figure 8 and Figure 4 is that SWFs have boosted asset diversification by a lot more than FX reserve managers have diversified across currencies.

Figure 5: Average pairwise currency correlation

Source: IMF COFER, Bloomberg, J. P. Morgan calculations

3

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

Figure 7: Current currency composition of FX reserve managers vs. currency shares in world payments SWIFT currency shares based on May 2014 data along with latest COFER currency composition.

0.7 0.6

FX reserve share (latest COFER data)

0.5 0.4 World payments share 0.3 0.2 0.1

Other

CAD

AUD

CHF

JPY

GBP

EUR

USD

0

Source: SWIFT, IMF COFER, J. P. Morgan calculations

Figure 8: US asset diversification index of official institutions Variances are calculated based on daily currency returns over one-year rolling periods. See text for more details

12

Average asset class variance / US portfolio variance

11 10 9 8 7 6 5 4 3 2

03

05

07

09

Source: US TIC, J. P. Morgan calculations

4

11

13

Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Table A1: Weekly flow monitor

Table A2: Weekly corporate flows

$bn, Includes US domiciled Mutual Fund flows from ICI with a one week lag and globally domiciled ETF flows from Bloomberg. Current week data only includes ETF flows.

$bn, Gross bond issuance includes all corporates incl. financials. United States issuance is all issuance globally by US companies and W. European issuance is all issuance globally by W. European companies. M&A is announced deal value and Buybacks are announced transactions. Y/Y change is change in YTD announcements over the same period last year. Equity supply and corporate announcements are based on announced deals, not completed.

MF & ETF Flows

16-Jul

4 wk avg

13 wk avg

2013 avg

All Equity

6.16

3.0

3.1

6.0

All Bond

1.62

2.7

3.4

-1.1

Equity Supply

18-Jul

4 wk avg

13 wk avg

y/y chng

US Equity

4.17

0.1

-0.5

2.6

Global IPOs

0.30

2.6

2.7

74%

Intl. Equity

1.99

3.2

3.4

3.6

Secondary Offerings

5.9

7.9

7.5

37%

Tax able Bonds

1.58

2.6

2.9

-0.1

Gross corporate bond issuance

Municipal Bonds

0.04

0.1

0.5

-1.1

United States

9.8

19.1

27.7

-4%

Western Europe (€bn)

2.8

14.3

20.1

23%

Japan

3.2

3.4

3.2

-12%

EM

5.3

16.3

24.1

-1%

Source: Bloomberg, ICI, J.P. Morgan

Chart A1: Fund flow indicator 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.

25

Last observation: 16-Jul-14

Corporate announcements M&A - Global

116.5

69.2

86.3

53%

- US Target

103.2

45.2

39.4

55%

- Non-US Target

13.3

24.0

46.9

52%

US buy backs

1.15

3.8

4.4

-33%

Non-US buy backs

0.06

0.6

2.6

-10%

20 Source: Bloomberg, Dealogic, Thomson Reuters, J.P. Morgan

15

Table A3: Trading turnover monitor

10 5 0 -5 -10 -15 -20 Feb-07 Feb-08 Feb-09 Feb-10 Feb-11 Feb-12 Feb-13 Feb-14 Source: Bloomberg, ICI, J.P. Morgan

Chart A2: Global equity & bond fund flows $bn per year. Flows include global MF and ETF flows. MF flows are from ICI (global flows up to Q4’13 is from ICI and data since then up to now is combination of EFAMA and ICI). 2014 YTD flows are estimated. ETF flows are from Bloomberg.

851

900

600

674

588 452 219

300 119

581

505 225

282 187 203222

100 1

0

82 YTD

-171 -210

-300 2006

2007

2008

2009

2010

Equity funds

Bond funds

2011

2013

2012

3 month avg. USTs are primary dealer transactions in all US government securities. JGBs are OTC volumes in all Japanese government securities. Bunds, Gold, Oil and Copper are futures. Gold includes Gold ETF’s. Min-Max chart is based on Turnover ratio i.e. the ratio of monthly trading volumes annualized divided by the outstanding amount. For Bunds and Commodities, futures trading volumes are used while the outstanding amount is proxied by open interest. The diamond reflects the latest turnover observation. The thin blue line marks the distance between the min and max for the complete time series since Jan-2005 onwards. Y/Y change is change in YTD deal values over the same period last year.

As on Jun-14 MIN Equities EM Equity DM Equity Govt Bonds USTs JGBs Bunds Credit US HG US HY US Convertibles Commodities Gold Oil Copper

MAX

Turnover ratio

Vol (tr)

y/y chng

1.61 0.90

$1.10 $3.56

-1% 10%

14.73 11.58 1.66

$10.05 ¥833 €2.33

-11% 14% -17%

0.69 1.08 2.05

$0.26 $0.15 $0.02

2% 15% -18%

31.99 63.71 5.22

$0.34 $1.97 $0.58

-37% -27% 23%

Source: Bloomberg, Federal Reserve, Trace, Japan Securities Dealer Association, WFE, J.P. Morgan. * Data with one month lag

2014

Source: Bloomberg, ICI, EFAMA, J.P. Morgan

5

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Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

ETF Flow Monitor (data as of Jul 16) Chart A3: Global Cross Asset ETF Flows

Chart A4: Bond ETF Flows

Cumulative flow into ETFs as a % of AUM.

Cumulative flow into bond ETFs as a % of AUM.

20%

10%

30%

EM

25%

Global HY

20%

Global HG ex-EM

15%

0%

10% -10%

5% 0%

-20%

-30%

-40% Jan-13

Equity

-5%

Bonds

-10%

Commodity

-15%

Apr-13

Jul-13

Oct-13

Jan-14

Apr-14

Jul-14

-20% Jan-13

Apr-13

Jul-13

Oct-13

Jan-14

Apr-14

Jul-14

Source: J.P. Morgan. Bloomberg

Source: J.P. Morgan. Bloomberg

Chart A5: Global Equity ETF Flows

Chart A6: US Equity Sectoral ETF Flows

Cumulative flow into global equity ETFs as a % of AUM.

Cumulative flow into US equity sectoral ETFs as a % of AUM.

50% 40%

EM

Industrial

US

Materials

WE 30%

Technology

Japan

Healthcare

20%

Energy

10%

Financial

0% Utilities

-10%

Cons. Staples

-20% -30% Jan-13

Telecom

Apr-13

Jul-13

Oct-13

Jan-14

Apr-14

Jul-14

Cons. Discretionary -50%

Source: J.P. Morgan. Bloomberg

6

Source: J.P. Morgan, Bloomberg

-30%

-10% 12M 3M

10%

30%

50%

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

Chart A7: Market health map

Conti… Explanation of indicators:

Each of the six axes corresponds to a key indicator for markets. The position of the blue line on each axis shows how far the current observation is from the extremes at either end of the scale. The dotted line shows the same but at the beginning of 2012 for comparison. For example, a reading at the centre for value would mean that risky assets are the most expensive they have ever been while a reading at the other end of the axis would mean they are the cheapest they have ever been. See explanation on the right for each indicator. Overall, the larger the blue area within the hexagon, the better for risky markets.

Positions: Difference between net spec positions on US equities and rates. See Chart A14. Flow momentum: The difference between flows into equity funds (incl. ETFs) and flows into bond funds. Chart A1. We then smooth this using a Hodrick-Prescott filter with a lambda parameter of 100. We then take the weekly change in this smoothed series as shown in Chart A1 Economic momentum: The 2-month change in the global manufacturing PMI. (See REVISITING: Using the Global PMI as trading signal, Nikolaos Panigirtzoglou, Jan 2012). Equity price momentum: The 6-month change in the S&P500 equity index.

Equity trading volumes

Chart A8: Option skew monitor Equity price momentum

Value

Economic momentum

Positions Inversed

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. It can therefore be seen as an indicator of risk perception in that a highly negative skew in equities is indicative of a bearish view. 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. A positive skew on iTraxx Main means investors favor buying protection, i.e. a short risk position. A positive skew for the Bund reflects a long duration view, also a short risk position. Crude Gold

Flows

Explanation of indicators:

German Bund

All variables are expressed as the percentile of the distribution that the observation falls into. I.e. a reading in the middle of the axis means that the observation falls exactly at the median of all historical observations.

iTraxx Main EURUSD

Equity trading volumes: The Y/Y change in the average daily trading volume of stocks on the NYSE. Value: The slope of the risk-return tradeoff line calculated across USTs, US HG and HY corporate bonds and US equities (see GMOS p. 6, Loeys et al, Jul 6 2011 for more details).

17-Jul-2014 11-Jul-2014

S&P500 -1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Source: Bloomberg, J.P. Morgan

Credit growth Chart A9: Credit creation in the G4

Chart A10: Credit creation in EM

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. Last obs is for Q1’14.

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. Last obs is for Q1’14.

25%

45%

G4 ex EU

20%

Euro area

35%

EM ex China China G4

15% 25%

10%

15%

5% 0%

5%

-5% -10% Mar-01

Mar-03

Mar-05

Mar-07

Mar-09

Mar-11

Mar-13

Source: Central bank, ICI, Barcap, Bloomberg, IMF and J.P. Morgan calculations

-5% Mar-01

Mar-03

Mar-05

Mar-07

Mar-09

Mar-11

Mar-13

Source: Central bank, ICI, Barcap, Bloomberg, IMF and J.P. Morgan calculations

7

Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Spec position monitors Chart A11: 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. We then scale the net positions by open interest. The chart shows the z-score of these net positions, i.e. the current net position divided by the open interest, 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 excluding the Eurodollar contract. The sample starts on the 13th of June 2006.

Last observation: 8-Jul-14

0.4 0.2 0.0 -0.2 -0.4 -0.6 07

08

09

10

11

12

13

14

Source: CFTC, J.P. Morgan

Chart A14: Spec position indicator on US equities vs. rates Difference between net spec positions on US equities & rates 01-Jul 14 08-Jul 14 0.0

1.0

2.0

3.0

Short interest as a % of shares outstanding based on z-scores. A strategy which overweight’s the S&P500 sectors with the highest short interest zscore (as % of shares o/s) vs. those with the lowest, produced an information ratio of 0.7 with a success rate of 56% (see F&L, Jun 28, 2013 for more details)

Telecom Utilities Energy Technology Health Care Industrials Discretionary Staples Financials Materials

Similar to Chart A12, this indicator is derived by the difference between total CFTC spec positions in US equity futures (in $bn) scaled by open interest (in $bn) minus a duration weighted composite of UST futures and scaled by open interest. The US equity is an aggregate of the S&P500, Dow Jones, NASDAQ and their Mini index. The US rates series is duration weighted aggregate of the UST2YR, UST5YR, UST10YR, UST long bond & the UST Ultra long bond futures. 20% Last observation: 8-Jul-14 15% 10% 5% 0% -5% -10% -15% -20%

-0.5

0.0 5/31/2014

Source: NYSE, J.P. Morgan

8

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.

0.6

Chart A13: S&P500 sector short interest

-1.0

Difference between net spec positions on risky & safe currencies

0.8

Standard devations from mean weekly position Copper Crude Oil Silver Nikkei US T-Bonds GBP Gold MXN AUD CAD NZD US Equities VIX RUB US Rates (ex. ED) Corn US 10YR US 2YR CHF USD US 5YR EUR BRL JPY Wheat 3M Eurodollars -3.0 -2.0 -1.0 Source: Bloomberg, CFTC, J.P. Morgan

Chart A12: Spec position indicator on Risky vs. Safe currencies

0.5

1.0 6/15/2014

1.5

2.0

2.5

93

96

99

02

Source: CFTC, Bloomberg and J.P. Morgan

05

08

11

14

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

Mutual fund and hedge fund betas Chart A15: Balanced fund equity exposure Rolling 21-day beta of balanced MF returns to returns on the S&P500. Balanced funds are top 20 US based funds by assets that have existed since 2006. It excludes tracker funds and funds with a low tracking error. The thin black line is the average during expansion since 2006.

0.80 0.75

Chart A16: Equity mutual fund beta to Euro vs. US and EM vs. US equities relative performance 41-business-day rolling beta of the average daily returns of 20 biggest USdomiciled active equity funds against the daily relative return of Euro area vs. US equities and emerging markets vs. US equities. The betas are based on multiple regressions of the relative performance of the Eurostoxx50 vs. the S&P500, MSCI EM vs. the S&P500 and the S&P500 outright performance.

0.35

0.70

Last observation:

16-Jul-14

0.30

0.65

0.25

0.60

EM

0.20

0.55

0.15

Last observation: 17-Jul-14

0.50

0.10 0.05

0.45 10

11

12

13

14

Euroarea

0.00

Source: Bloomberg J.P. Morgan

-0.05 Jan-11

Jan-12

Jan-13

Jan-14

Source: Bloomberg J.P. Morgan

Chart A17: Hedge fund monitor Rolling 21-day beta of macro and equity L/S hedge fund returns to returns on the S&P500. The beta represents the average exposure of macro hedge funds to equities over the previous 21-days.

0.8

Last observation: 16-Jul-14

Chart A18: Currency hedge fund USD exposure. The rolling 21-day beta of the Barclay Hedge FX index with the JPM USD tradable index vs. the net spec position in the USD as reported by the CFTC. Spec is the non-commercial category from the CFTC. 50

0.6

Equity L/S HF: beta to the S&P500

40

1.5

HF beta to the JPM USD tradable Index

30

0.4

1.0

20

0.2 0.0 -0.2 -0.4 Jan-10

2.0 Latest observation: 11-Jul-14

Macro HF: beta to the S&P500 Jan-11

Jan-12

Source: Datastream, Bloomberg, J.P. Morgan

Jan-13

Jan-14

10

0.5

0

0.0

-10

-0.5

-20

-1.0

-30

Net spec positions in the USD

-40

-1.5

-50

-2.0 07

08

09

10

11

12

13

14

Source: CFTC, Datastream, Barclay Group, Bloomberg J.P. Morgan

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Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Corporate activity Chart A19: G4 non-financial corporate capex and cash flow as % of GDP

Chart A20: G4 non-financial corporate sector net debt and equity issuance

% of GDP, G4 includes the US, the UK, the Euro area and Japan. Last observation as of Q4 2013.

$tr per quarter, G4 includes the US, the UK, the Euro area and Japan. Last observation as of Q4 2013.

11.0

G4 Capex

2.0

10.5 G4 net debt issuance

1.5

10.0 9.5

1.0

9.0 0.5

8.5 8.0

0.0

G4 Cash flow

7.5

-0.5

7.0 6.5 95

97

99

01

03

05

07

09

11

G4 net equity issuance

-1.0

13

98

Source: ECB, BOJ, BOE, Federal Reserve flow of funds

00

02

04

06

08

10

12

Source: ECB, BOJ, BOE, Federal Reserve flow of funds

Chart A21: Global M&A and LBO

Chart A22: US and non-US share buybacks

$tr. YTD 2014 as of Jul 18, 2014. M&A and LBO’s are announced.

4.5

0.8 M&A ex-LBO (lhs)

4.0

LBO (rhs)

3.5

0.5

2.5 YTD

2.0 1.5 1.0

05

06

07

08

09

Source: Reuters ThomsonOne, J.P. Morgan

10

11

12

13

14

0.7

0.5

0.3

0.4

0.2

0.3

0.0

Non-US buybacks US buybacks

0.6

0.4

0.1

0.5 0.0

0.7 0.6

3.0

$tr, YTD 2014 as of Jul 18, 2014. Buybacks are announced.

YTD

0.2 0.1 0.0

05

06

07

08

Source: Reuters ThomsonOne, J.P. Morgan

10

09

10

11

12

13

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Pension fund and insurance company flows Chart A23: G4 pension funds and insurance companies equity and bond flows

Chart A24: G4 pension funds and insurance companies equity and bond levels

Equity and bond buying in $bn per quarter. G4 includes the US, the UK, Euro area and Japan. Last observation is Q4 2013

Equity and bond as % of total assets per quarter. G4 includes the US, the UK, Euro area and Japan. Last observation is Q4 2013.

250

55% Bonds

200

Bonds

50%

150

45%

100

40%

50 35%

0

30%

-50 -100 -150 Mar-99

Equities Mar-02

Mar-05

Equities

25%

Mar-08

20% Mar-99

Mar-11

Mar-02

Mar-05

Mar-08

Mar-11

Source: ECB, BOJ, BOE, Federal Reserve flow of funds

Source: ECB, BOJ, BOE, Federal Reserve flow of funds

Chart A25: Pension fund deficits

Chart A26: G4 pension funds and insurance companies cash and alternatives levels

US$bn. For US, funded status of the 100 largest corporate defined benefit pension plans, from Milliman. For UK, funded status of the defined benefit schemes eligible for entry to the Pension Protection Fund, converted to US$ at current exchange rates. Last observation is June 2014.

100

Equity and bond as % of total assets per quarter. G4 includes the US, the UK, Euro area and Japan. Last observation is Q4 2013.

24%

0 20%

-100

16%

-200

12%

-300

US

-400

Cash

8%

-500 -600 Dec-09

Alternatives

UK

4%

Dec-10

Dec-11

Dec-12

Dec-13

0% Mar-99

Mar-02

Mar-05

Mar-08

Mar-11

Source: Milliman, UK Pension Protection Fund, J.P. Morgan Source: ECB, BOJ, BOE, Federal Reserve flow of funds

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Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

European Funding market monitor Table A4: Bank deposits and ECB reliance Deposits are non-seasonally adjusted Euro area non-bank, non-government deposits as of May 2014. We take total deposits (item 2.2.3. in MFI balance sheets minus “deposits from other financial institutions”, which includes deposits from securitized vehicles and financial holding corporations among others. We also subtract repos (item 2.2.3.4) from the total figures to give a cleaner picture of deposits outside interbank borrowing. ECB borrowing and Target 2 balances are latest available. ECB borrowing is gross borrowing from regular MROs and LTROs. The Chart shows the evolution of Target 2 balance for Spain and Italy along with government bond spreads. The shaded area denotes the period between May 2011 and Aug 2012 when convertibility risk premia were elevated due to Greece exit fears. Target 2 bal. Target 6m chng ECB borrowing Depo 3m chng Depo 12m chng

€bn Austria

-39

2

8

0.8%

-0.6%

Belgium

-21

-6

15

1.4%

4.9%

Cyprus

100

1.4 1.9

0 10y Spanish and Italian govt spread vs Bunds

2.4

2

-2.6%

-17.0%

-100

-12

0

7.5%

-14.0%

-200

2.9

19

56

0.1%

4.2%

3.4

462

-48

60

0.1%

1.9%

-300

-30

21

45

-0.2%

-1.5%

-400

3.9 4.4

-6

2

Finland

14

France

-49

Germany Greece Ireland

-47

24

23

0.2%

0.4%

-500

Italy

-149

80

210

-6.5%

-38.4%

-600

4.9

Luxembourg

105

2

3

7.9%

2.0%

Netherlands

30

-30

7

3.5%

-3.1%

-700

Portugal

-57

4

42

1.6%

2.3%

Spanish and Italian 5.4 Target2 5.9 Apr-13 Jan-14

Spain

-209

21

188

0.0%

2.6%

Source: Bloomberg, ECB, National Central Banks, J.P. Morgan

-800 Jan-11

Oct-11

Jul-12

Source: Bloomberg, National Central Banks, J.P. Morgan

Chart A27: Euro area gross bank debt issuance

Chart A28: Excess cash in the Euro area banking system

Includes secured, unsecured and securitized issuance in any currency. Excludes short-term debt (maturity less than 1-year) and self funded issuance (where the issuing bank is the only book runner).

€bn, Measured as the difference between the amount in the ECB deposit facility minus that in the lending facility, plus the difference between the current account reserves that banks hold with the ECB minus required reserves.

€bn 30

25

Periphery

Last observation: 18-Jul-14

Core

900

Last observation:

16-Jul-14

800

EMU bank unsecured gross issuance

700 600

20

500 15

400 300

10

200 5

Oct-12

100

Jan-13

Apr-13

Source: Dealogic, J.P. Morgan

12

Jul-13

Oct-13

Jan-14

Apr-14

Jul-14

0 Jan 11 Source: ECB, J.P. Morgan

Jan 12

Jan 13

Jan 14

Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Japanese flows and positions Chart A29: Tokyo Stock Exchange Margin trading: total buys minus total sells In bn of shares. Topix on right axis.

6.0

3500 Last observation: 11-Jul-14

5.0

3000

Chart A30: Domestic retail flows In JPY tr. Retail flows are from Tokyo stock exchange and FX margin trader positions are JPM calculation. FX margin trader positions are in reverse order. A higher number means a larger short and vice versa.

0.5

Last observation: 8-Jul-14

-2

Japanese retail flow (4 wk avg.)

0.4

0

0.3

buys minus sells 4.0

2500

0.2

2

0.1 3.0

2000

2.0

1500

4

0.0 -0.1

6

-0.2 1.0 0.0

1000

Topix 89

92

95

98

01

04

07

8

-0.3 -0.4

10

13

Source: Tokyo Stock Exchange, J.P. Morgan

500

10

-0.5

Domestic FX margin traders

-0.6 Jan-11 Jul-11

Jan-12 Jul-12

Jan-13 Jul-13

12 Jan-14 Jul-14

Source: TSE, J.P. Morgan calculations

Chart A31: Japanese equity buying by foreign investors. Japanese investors' buying of foreign bonds

Chart A32: Overseas CFTC spec positions

$bn, 4 week moving average.

CFTC positions are in $bn.

20

Last observation: 11-Jul-14

20

Foreign investors' buying of Japanese equities

15

15

Last observation: 8-Jul-14 Nikkei Spec position

100

10 5

0 -50

-5

-100

-10

-5

-15

-10

50

0

0

09

Japanese investors' buying of foreign bonds 10 11 12 13

Source: Japan MoF, J.P. Morgan

14

200 150

10

5

250

-150 CFTC JPY/USD net spec positions

-200

-20 -250 Jan-11 Jul-11 Jan-12 Jul-12 Jan-13 Jul-13 Jan-14 Jul-14 Source: Bloomberg, CFTC, J.P. Morgan calculations.

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Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

Nikolaos Panigirtzoglou (44-20) 7134-7815 [email protected]

Gold flows and positions Chart A33: Spec positions

Chart A34: Gold ETFs

$bn. CFTC net long minus short position in futures for the Managed Money Category.

Mn troy oz. Physical gold held by all gold ETFs globally.

90

40

80

Last observation: 8-Jul-14

35

Last observation: 16-Jul-14

70 30

60

25

50

20

40

15

30

10

20

5

10

0 Jun-06 Jun-07 Jun-08 Jun-09 Jun-10 Jun-11 Jun-12 Jun-13 Jun-14

0 Oct-03

Apr-05

Oct-06

Apr-08

Oct-09

Apr-11

Oct-12

Apr-14

Source: Bloomberg, J.P. Morgan

Source: CFTC, Bloomberg, J.P. Morgan

Chart A36: Shanghai exchange gold volumes

Chart A35: Gold coin sales Thousand troy ounces 350

Thousand troy ounces.

Last observation: Jun-14

2000

300

1800 250

Last observation: 16-Jul-14

1600 1400

200

1200

150

1000 100

800

50

600 400 87

92

97

Source: US Mint, Bloomberg, J.P. Morgan

02

07

12

200 0 Nov-03 May-05 Nov-06 May-08 Nov-09 May-11 Nov-12 May-14 Source: Shanghai Gold Exchange, Bloomberg, J.P. Morgan.

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Global Asset Allocation Flows & Liquidity - Shorter Version 18 July 2014

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