Global Asset Allocation 05 September 2014

Flows & Liquidity The ECB's liquidity boost 











The ECB’s prospective quantitative expansion is hitting the global financial system at a time when liquidity is already very high. And this is true for both “narrow” or “banking sector liquidity” and “broad” or “non-bank sector” liquidity.

Global Asset Allocation

The G4 banking system is already flooded with excess reserves of around $4.5tr. Narrow or banking sector liquidity should exceed $5tr as a result of ECB’s actions, exerting even more downward pressure on 2-5 year government bond yields of core countries, the preferred habitat of banks.

J.P. Morgan Securities plc

In our models, global money supply, which stood at $68tr at the end of August, is $5tr above an estimated medium-tem money demand target. Prospective ECB actions are likely to widen this $5tr gap especially if ECB actions improve euro area credit creation.

(1-212) 834-8315 [email protected]

Nikolaos Panigirtzoglou

AC

(44-20) 7134-7815 [email protected]

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

Matthew Lehmann

J.P. Morgan Securities LLC

Nandini Srivastava

Of the ECB’s eligible universe of corporate bonds, bank bonds and ABS, around €3.4tr is potentially within the range of likely “acceptable” liquidity/price/credit risks, i.e. subjected to a 0-10% haircut. Out of this €3.4tr universe, there are roughly €1.1tr of covered bonds and €550bn of ABS.

(44-20) 7742-6183 [email protected]

While there is around €100bn per month capacity across all liquid euro credit markets, comprised of €50bn of primary issuance and €50bn of secondary trading volume, only a fraction of this can be used by the ECB without distorting private markets too much. The ECB would need to expand the range of private sector assets beyond ABS and covered bonds to achieve its quantitative objectives more quickly.

J.P. Morgan India Private Limited

 The ECB President stated in this week’s press conference that the ECB’s forthcoming programs, i.e. TLTROs coupled with ABS and covered bond purchases, could take the ECB’s balance sheet back to early 2012 levels, i.e. to €3tr from €2tr currently. These remarks, not only suggest that the ECB might have a target in mind regarding the size of its balance sheet, but raise questions about the boost to global liquidity from prospective ECB actions.  In aggregate, G4 central balance sheets started rising rapidly from the end of 2010 driven by the Fed’s QE2 followed by the BoE’s QE, ECB’s LTROs, Fed’s QE3 and BoJ’s QE. As a result of these central bank actions, G4 central bank balance sheets expanded by almost $4tr over 4 years i.e. by $1tr per year since the end of 2010 (Figure 1). With the ECB aiming at a €1tr expansion of its balance sheet, this $1tr per year pace in G4 central bank balance sheet expansion is likely to increase rather than decrease from here, despite the Fed’s tapering. The BoJ is already expanding its balance by close to $650bn per year, so adding a similar pace of increase for the ECB’s balance sheet (€500bn or $650bn per year) should result in an annual pace of G4 central bank balance sheet expansion of $1.3tr, even as the Fed ceases bonds purchases.

See page 17 for analyst certification and important disclosures.

J.P. Morgan Securities plc

Jigar Vakharia (91-22) 6157-3281 [email protected]

Figure 1: G4 Central bank balance sheets Total assets in $bn for the Fed, €bn for the ECB, ¥100bn for the BoJ and £100m for the BoE Last observation is Aug 29th 2014

5000 BoE

4000

Fed

3000 ECB

2000

BoJ

1000 0 08 11000

09

10

11

12

13

14

$bn at current exchange rates

10000 9000 8000 7000 6000

Fed+ECB+BoJ+BoE assets

5000 4000 08

09

10

11

12

13

14

Source: National central bank sources

www.jpmorganmarkets.com

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

Global Asset Allocation Flows & Liquidity 05 September 2014

 This ECB-driven quantitative expansion is hitting the global financial system at a time when liquidity is already very high. And this is true for both “narrow” or “banking sector liquidity” and “broad” or “non-bank sector” liquidity.  Narrow or banking sector liquidity is created by the injection of excess reserves into the banking system. Broad or non-bank liquidity reflects money supply i.e. the amount of cash held by the non-bank sectors of the economy such as households, non-financial corporations and financial intermediaries such as asset managers, pension funds and insurance companies. These two components of liquidity are interrelated but are not necessarily mechanically linked and are thus distinct. QE bond purchases, by injecting reserves into the banking system, increase narrow liquidity, but they do not necessarily increase broad money supply. Bond purchases can result in an increase in money supply either directly, e.g. if the central bank buys bonds from a non-bank entity such as a pension fund, this automatically expands the assets (reserves) & liabilities (deposits) of the banking system; or indirectly, when central banks’ quantitative measures induce higher bank lending in the economy.  The G4 banking system is already flooded with excess reserves of around $4.5tr i.e. reserves commercial banks have with central banks in excess of what they need to meet usual liquidity needs. Given that the banking system cannot get rid of reserves in aggregate, these zero yielding reserves become the “hot potato” that banks try to pass to other each until the relative pricing is adjusted enough to remove the incentive for banks to get rid of these reserves. With the ECB aiming at increasing the amount of excess reserves even further via its TLTRO/bond purchase programs, G4 narrow or banking sector liquidity should exceed $5tr, exerting even more downward pressure on 2-5 year government bond yields of core countries, the preferred habitat of banks.  Broad liquidity is also likely to be boosted by ECB’s quantitative actions, especially if these actions improve credit creation. Broad liquidity is a more important component of overall liquidity as it can impact other asset classes beyond government bonds, such as corporate bonds, equities, real estate, etc. We measure broad liquidity via a model-driven estimate of excess money supply rather than by using money supply aggregates themselves. Money supply aggregates measure the amount of cash, mostly bank deposits and money market funds, held by households, non-financial corporations and nonbank financial intermediaries such as asset managers, pension funds and insurance companies. Money supply aggregates thus measure gross rather than excess money supply. Money demand matters along with money supply and one needs to look at the balance between the two in order to assess the potential impact of broad liquidity on asset prices and inflation.  To assess excess money supply, we update the model we previously published in Flows & Liquidity, Apr 26th 2013. Beyond nominal GDP and financial wealth, i.e. the stock of tradable bonds and equities in the world, the model includes an uncertainty variable. Uncertainty is important as it makes agents hold more cash during periods of elevated risk perception, for precautionary reasons. We proxy uncertainty via the US monthly index constructed by Baker, Bloom and Davis. To measure policy-related economic uncertainty, they construct an index from three types of underlying components. One component quantifies newspaper coverage of policy-related economic uncertainty. A second component reflects the number of federal tax code provisions set to expire in future years. The third component uses disagreement among economic forecasters as a proxy for uncertainty. This uncertainty proxy is shown in Figure 2 along with its smoothed version. This uncertainty proxy declined sharply over the past two years and has completely 2

Figure 2: Economic policy uncertainty proxy US monthly index 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. 300 250 200 150 100 50 0 89 92 95 98 01 04 Source: www.policyuncertainty.com

07

10

13

Figure 3: Real money supply (actual) vs. demand (fitted) Dependent Variable: M2/CPI Method: Least Squares Sample (adjusted): 1990M01 2014M08 Included observations: 296 after adjustments Variable

t-stat

Prob.

constant

Coefficient Std. Error -0.09

0.02

-5.69

0.00

Nominal GDP over CPI

0.57

0.06

8.81

0.00

Bonds/Equities market cap over CPI

0.25

0.02

13.90

0.00

Uncertainty

3.80

1.14

3.33

0.00

R-squared

0.97

0.60

Actual

0.55 0.50 0.45 0.40 0.35 0.30 0.25

Fitted

0.20 90

93

96

99

02

05

08

11

14

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

Global Asset Allocation Flows & Liquidity 05 September 2014

unwound the post Lehman increase.  To estimate the gap between money supply and a medium-term demand target, we regress real money balances, global M2 deflated by global CPI, against 1) real GDP (i.e. the level of nominal GDP deflated by global CPI), 2) real financial wealth (i.e. the total capitalization of global bonds and equities deflated by global CPI), and 3) the uncertainty proxy described above. To remove the impact of FX changes from our global money stock measure, we aggregate the M2 stocks of various countries at constant (today’s) exchange rates. The regression results are shown in Figure 3. All three variables are statistically significant with a positive sign as predicted by theory.  Excess (i.e. the residual in our model) money supply is currently in record high positive territory. The current residual suggests that global money supply which stood at $68tr at the end of August is $5tr above our estimated medium-tem money demand target. The residual of the regression turned positive in May 2012 and has risen steadily since then. This is both because of real money supply increasing and money demand decreasing due to lower uncertainty (Figure 2: Global M2 reached $68tr in August this year and is up by $15tr or 29% since the end of 2010 when G4 central bank balance sheets started rising rapidly. The capitalization of both bonds and equities in the world had risen by a similar 31% over the same period and the current pace of M2 growth suggests that global equities and bonds should continue to grow by at least 6% per annum.  Of this $15tr increase in global M2 since end 2010, $5tr was due to G4 and the rest $10tr was due to the rest of the world, mostly EM. Strong credit growth in EM economies has boosted our measure of excess liquidity in recent years and this force led by China continues unabated. It is often mentioned that this Chinese or EM liquidity is trapped within EM. We disagree. It is true that domestic economic agents in China and other EM economies face restrictions in deploying their capital abroad. But domestic liquidity in China and EM is channeled to the rest of the world via reserve accumulation, i.e. via the official sector, as capital restrictions put upward pressure on EM currencies.  Prospective ECB actions are likely to widen the above $5tr estimated gap between global money supply and demand. That is, the ECB's quantitative expansion is hitting the financial system at a time when broad liquidity is also very high. The rise in excess liquidity, i.e. the residual in the model of Figure 3, is supportive of all assets outside cash, i.e. bonds, equities and real estate. The current episode of excess liquidity, which began in May 2012, appears to have been the most extreme ever in terms of its magnitude and the ECB actions have the potential to make it even more extreme, in our view. Before then, there were three major episodes of excess liquidity (i.e. positive residual) in our model: 1993-1995, 2001-2006 and Oct 2008-Sep 2010. These were periods of strong asset price inflation suggesting that excess liquidity could have been a factor supporting markets at the time.  It is also important to note that liquidity is not constrained by borders. For example, foreign institutions could also sell ABS or covered bonds to the ECB, so the prospective injection of liquidity by the ECB could reach foreign as well as domestic institutions. Anecdotally, both the Fed and the BoE have bought significant amount of bonds from foreign institutions during their QE operations. In addition, in a global and interlinked financial system, via arbitrage, the ECB operations can end up suppressing yields of higher yielding bond universes outside the euro area by more than domestic bonds.

M2 /CPI Residual: Actual minus Fitted

0.05 0.04 0.03 0.02 0.01 0.00 -0.01 -0.02 -0.03 -0.04 -0.05 -0.06 90

94

98

02

06

10

14

Source: J.P. Morgan

Figure 4: Nominal asset yields In %. US cash is proxied by the yield on JPM Global 1m Cash index. The Global Bond yield is proxied by the yield on JPM GABI index. The Global equity yield is proxied by the dividend yield of the DataStream global equity index augmented by 5y rolling global CPI inflation to make it nominal. Similarly the property yield is proxied by the dividend yield on the US commercial property (NCREIF) augmented by 5y rolling US CPI inflation to make it nominal. 14

%

12

Enter Textreal estate US commercial

10 8 Equities

6

Bonds

4 Cash

2 0 89

92

95

98

01

04

07

10

13

Source: DataStream, NCREIF, Bloomberg, J.P. Morgan

 These liquidity boosts are not without risks. We note that they risk creating asset bubbles which when they burst can destroy wealth leading to adverse 3

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Global Asset Allocation Flows & Liquidity 05 September 2014

economic outcomes. Asset yields are mean reverting over long periods of time and thus historically low levels of yields in bonds, equities and real estate (Figure 4) are unlikely to be sustained forever.

ECB’s QE: capacity constraints

 In the light of ECB’s announcements we update our discussion from Flows and Liquidity of May 30th “Liquidity constraints”:  1) How big is the universe of marketable private sector credit instruments in the Euro area?

2.0 1.5 1.0 0.5 asset backed securities

Source: ECB

Figure 6: Haircut distribution of ECB eligible collateral ECB haircut in x axis, haircut distribution for ECB eligible collateral issued by Euro area private sector entities on which the ECB provides haircut information.

40% 35% 30% 25%

 2) What is the current capacity of the primary and secondary markets of these bonds?

20%

 We had argued before that the nature of corporate bond trading has changed since the Lehman crisis and has become more order and customer driven. Consistent with a desire to hold a leaner inventory, broker/dealers redirected their trading business towards more of an order-driven model where they are getting orders from big institutional investors and try to work these orders without having to hold a large inventory in the meantime. This is a change from previous practices of positioning taking, i.e. holding enough inventories across bond issues they wanted to make markets on. Big institutional investors on the buy side have thus become instrumental in driving liquidity in the corporate bond market by using banks as intermediaries to receive flow and price information, and negotiate and execute trades. And this is one of the reasons why liquidity has become more bifurcated, being healthy for the

10%

4

other marketable assets

0.0

corporate bonds

 The €1.7tr of securities subjected to 0-5% haircut band represent assets with relatively low liquidity/price/credit risks. The €1.7tr of securities subjected to 5-10% haircut represents assets with medium liquidity/price/credit risks. So around €3.4tr of the ECB’s eligible universe of corporate bonds, bank bond and ABS, is potentially within the range of likely “acceptable” liquidity/price/credit risks. Out of this €3.4tr universe, there are roughly €1.1tr of covered bonds and €550bn of ABS.

2.5

covered bank bonds

 Given the liquidity/price discovery/credit risks, we note the universe in Figure 5 is not a good reflection of what the ECB could practically buy. One way of adjusting the universe of assets for these risks is by looking at ECB haircuts. The haircuts the ECB imposes on the market value of the collateral it accepts depend to large extent on liquidity/price/credit risks. The higher these risks the higher the haircut the ECB imposes. Figure 6 shows the distribution by haircut of a €4.8tr universe of ECB-eligible collateral issued by Euro area private sector entities on which the ECB provides haircut information. Around 35% or €1.7tr of this is subjected to a haircut of between 0-5% and another 35% or €1.7tr to a haircut of 5-10%. The latter haircut band includes all of ABS securities, while covered bonds are mostly subjected to 0-5% haircut band.

€tr as of Q2 2014, notional amounts, private (i.e. nongovernment) marketable debt eligible as collateral for ECB credit operations

uncovered bank bonds

 We have now Q2 data from the latest ECB collateral report where the universe of private (non-government) debt eligible as collateral for ECB credit operations was around €7tn in notional amounts. This universe represents debt issued by the private sector subjected to minimum credit quality criteria to prevent the ECB from taking too much credit risk. The composition of this universe remains largely unchanged from Q1 other than small decreases in notional amounts of covered bonds and ABS. The majority of this universe consists of uncovered bank bonds (€2.2tr), followed by covered bank bonds (€1.5tr), corporate bonds (€1.4tr), ABS or Asset Backed Securities (€680bn) and “other marketable assets” (€1.2tr) which include agency and supranational debt among others (Figure 5). Out of this €7tr, around €880bn appears to have been issued by non- Euro area entities and around €1.7tr (assuming a 10% haircut) of private sector assets are already posted as collateral.

Figure 5: ECB-eligible non-govt marketable collateral

15%

5% 0% Source: ECB

0-5

5-10

10-15

15-20

20+

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Global Asset Allocation Flows & Liquidity 05 September 2014

largest, most recently issued and frequently traded corporate bonds, in which large institutional investors are mostly interested, but having dried up for smaller, off-the-run issues.  And this what we believe the ECB could end up becoming as it introduces large scale asset purchases across Euro corporate bond markets: a big investor driving the order flow and liquidity in both primary and secondary euro corporate bond markets, financial and non-financial, secured and unsecured.  We had argued before that in total there is roughly €100bn per month of total capacity in liquid euro credit markets, €50bn in the primary market and €50bn in the secondary market. Corporate bond issuance is running at around €50bn per month currently (average of past 12 months) in the Euro area alone on a gross basis, including both financials and non-financials, unsecured and secured bonds. Secondary trading volumes are estimated at close to €40bn€50bn per month, and this excludes covered bonds, ABS, agency and supranational debt. Assuming a 20%-30% threshold beyond which the ECB risks distorting primary and secondary markets for euro area private sector debt by becoming too dominant, we arrived at a €20bn-€30bn per month estimate of ECB’s potential feasible buying capacity.  But if the ECB ends up buying only ABS and covered bonds, a buying pace of between €7-€14bn is feasible based on estimates by our colleague Gareth Davies and his team. In other words, the ECB would need to expand the range of private sector assets beyond ABS and covered bonds to achieve its quantitative objectives more quickly.  In our Flows and Liquidity of May 30th “Liquidity constraints” we had also looked at two additional questions which we reproduce below as they help putting the new ECB initiatives into historical perspective:  3) How did the previous ECB covered bond purchase programs fare?  The ECB’s Covered Bond Purchase Programme (CBPP1) was announced on May 7 2009, and was in operation between July 2009 and June 2010, during which time the ECB outright purchased €60bn of covered bonds. On October 6 2011, the ECB announced it would reactivate the programme (CBPP2) and purchased less than €20bn between November 2011 and early 2012. An ECB study found that over the 12-month period of the CBPP1 programme, 148 new eligible covered bonds as well as 47 taps of existing covered bonds were issued for an overall amount of €148 billion. The ECB used both primary and secondary markets during the program and at the time the ECB's mere announcement boosted issuance creating the capacity that the ECB needed to implement its bond purchase program. The CBPP1 program helped to deepen and broaden the covered bond market as well as to narrow bid-offer spreads. CBPP2 stopped before its original planned €40bn target because its credit easing objective was already fulfilled. And this an important distinction: the objective of ECB's covered bond programs was credit easing and not quantitative easing and this is why size targets were secondary objectives at the time.  4) How credit market capacity responded to previous QE programs?  There is little doubt that credit market liquidity and capacity is not static, but rather dynamic responding to demand conditions. We had explained before (Flows & Liquidity May 20th 2011) that QE works through both price and quantity channels. By buying bonds, central banks not only lower bond yields, but also expand the capacity of debt capital markets by boosting demand. This is shown in Figure 7 which shows that net covered bond issuance (including both secured and unsecured debt) was higher during QE periods, QE1, QE2 5

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

Global Asset Allocation Flows & Liquidity 05 September 2014

and QE3, as the Fed's purchases boosted bond demand in both the US and Europe. And net corporate bond issuance responded by more during QE3 relative to QE1 or QE2 given the higher pace and the open ended nature of the former. It is also interesting that the improvement in corporate bond issuance was actually more striking in Europe during these Fed QE episodes, where demand in debt capital markets was perhaps more constrained. 

As mentioned above corporate bond issuance is running at around €50bn per month currently (average of past 12 months) in the Euro area alone on a gross basis, including both, financials and non-financials, unsecured and secured bonds. The evidence from Figure 7 suggests that corporate bond issuance, and thus the capacity of Euro area bond markets, could increase in response to potential QE by the ECB. The caveat with this argument is that demand conditions in credit markets are now much stronger than they were during QE1 or QE2 so the incremental response of corporate bond issuance to potential QE by the ECB will likely be smaller.

80

QE1

QE2

75

QE3

70 65 60 55 50 45 Sep 12-Aug14

Jul11-Aug12

Apr10-Oct10

40

Dec08-Mar10

 While EUR CFTC spec positions had reached extreme levels on Tue 26th August (the blue line in Figure 8 declined to -$25bn on Aug 26th the lowest since July 2012), more timely data suggest that currency HFs had largely covered their EUR shorts ahead of this week’s ECB meeting. The rolling beta of currency HF returns to the returns of the JPM EUR tradable index suggest that these currency HFs had covered most of their EUR shorts ahead of the ECB meeting. The black line in Figure 8 jumped sharply during August with 80% of previous shorts having been covered during the month. With the caveat that the Barclay Hedge FX index only captures a small number of currency HFs, Figure 8 suggests that EUR positioning by HFs might have been cleaner than that based on CFTC data.

Average monthly net bond issuance by US and W. European financials and non-financials. Includes secured, unsecured and securitized issuance but excludes short term and self funded debt.

Nov10-Jun11

Currency HF’s appear to have covered EUR shorts ahead of this week’s ECB meeting

Figure 7: Net corporate bond issuance during QE

Source: Dealogic

Figure 8: Currency hedge fund EUR exposure The rolling 21-day beta of the Barclay Hedge FX index with the JPM EUR tradable index vs. the net spec position in the EUR as reported by the CFTC in $bn. Spec is the non-commercial category from the CFTC. 35 25

2.0

Currency HF beta to the JPM EUR tradable index

1.5 1.0

15

0.5

5

0.0

-5

-0.5 -1.0

-15 Net spec positions in the EUR

-25 -35 Jan-11

Jan-12

Jan-13

-1.5 -2.0 -2.5

Jan-14

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

6

Global Asset Allocation Flows & Liquidity 05 September 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

3-Sep

4 wk avg

13 wk avg

2013 avg

All Equity

3.63

6.8

3.6

6.0

All Bond

-1.61

3.5

2.2

-1.1

Equity Supply

5-Sep

4 wk avg

13 wk avg

y/y chng

US Equity

4.59

4.6

0.3

2.6

Global IPOs

1.0

2.8

2.3

70%

Intl. Equity

-0.97

2.5

3.4

3.6

Secondary Offerings

9.7

8.2

6.9

34%

Tax able Bonds

-1.67

2.8

1.7

-0.1

Gross corporate bond issuance

Municipal Bonds

0.06

0.7

0.5

-1.1

United States

36.1

19.5

23.3

-6%

Western Europe (€bn)

16.0

8.1

12.5

16%

Japan

11.1

4.9

3.4

-10%

EM

8.0

15.5

20.3

6%

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: 3-Sep-14

Corporate announcements M&A - Global

28.3

53.4

69.0

53%

- US Target

13.2

30.0

35.3

62%

- Non-US Target

15.1

23.4

33.7

46%

US buy backs

0.7

2.0

4.7

-26%

Non-US buy backs

0.4

0.7

1.8

-5%

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 Q1’14 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

100 1

0

82

187 202250

YTD -171 -210

-300 2006

2007

2008

Equity funds

2009

2010

2011

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 Aug-14 MI N 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

1.9 0.9

$1.3 $3.6

0% 10%

10.8 13.2 1.2

$7.5 ¥937 €1.93

-12% 15% -14%

0.5 0.9 1.5

$0.2 $0.1 $0.0

2% 21% -18%

32.1 77.7 5.2

$0.3 $1.9 $0.5

-34% -21% 15%

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

Bond funds

2013

2014

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

7

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

Global Asset Allocation Flows & Liquidity 05 September 2014

ETF Flow Monitor (data as of Sep 03) 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

Materials

US

Industrial

WE 30%

Healthcare

Japan

Technology

20%

Cons. Staples

10%

Energy

0% Financial

-10%

Telecom

-20% -30% Jan-13

Utilities

Apr-13

Jul-13

Oct-13

Jan-14

Apr-14

Jul-14

Cons. Discretionary -30%

Source: J.P. Morgan. Bloomberg

8

-20%

Source: J.P. Morgan, Bloomberg

-10% 0% 12M 3M

10%

20%

30%

40%

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

Global Asset Allocation Flows & Liquidity 05 September 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. iTraxx Main Gold

Flows

Explanation of indicators:

EURUSD

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.

29-Aug-2014

Crude

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).

04-Sep-2014

German Bund

S&P500 -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

9

Global Asset Allocation Flows & Liquidity 05 September 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. Standard devations from mean weekly position USD US T-Bonds Nikkei Copper Crude Oil VIX US Rates (ex. ED) AUD NZD GBP US Equities US 10YR US 2YR CAD US 5YR MXN Gold CHF Corn Silver BRL RUB JPY EUR Wheat 3M Eurodollars -3.0 -2.0 Source: Bloomberg, CFTC, J.P. Morgan

0% -5% -10% -15% -20%

93

96

99

02

05

08

11

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 19-Aug 14 26-Aug 14

-1.0

0.0

1.0

2.0

Utilities Telecom Energy Health Care Staples Technology Industrials Discretionary Materials Financials

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. 0.8 Last observation: 26-Aug-14 0.6 0.4 0.2 0.0 -0.2 -0.4 -0.6 07

0.0

1.0 7/15/2014

10

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. 20% Last observation: 26-Aug-14 15%

5%

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)

Source: NYSE, J.P. Morgan

Difference between net spec positions on risky & safe currencies

10%

Chart A13: S&P500 sector short interest

-1.0

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

2.0 7/31/2014

3.0

4.0

08

09

10

Source: CFTC, Bloomberg and J.P. Morgan

11

12

13

14

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

Global Asset Allocation Flows & Liquidity 05 September 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:

3-Sep-14

0.30

0.65

0.25 0.60

EM

0.20

0.55

0.15 0.10

Last observation: 03-Sep-14

0.50

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: 2-Sep-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

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

0.6

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: 29-Aug-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

11

Global Asset Allocation Flows & Liquidity 05 September 2014

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 Q1 2014.

$tr per quarter, G4 includes the US, the UK, the Euro area and Japan. Last observation as of Q1 2014.

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

-1.0

13

98

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

00

02

04

08

10

12

14

Chart A22: US and non-US share buybacks

$tr. YTD 2014 as of Sep 05, 2014. M&A and LBO’s are announced.

4.5

0.8 M&A ex-LBO (lhs)

4.0

LBO (rhs)

3.5 3.0

YTD

2.5

$tr, YTD 2014 as of Sep 05, 2014. Buybacks are announced.

0.7

0.7

0.6

0.6

0.5

0.5

0.4

2.0

Non-US buybacks US buybacks

0.4

0.3

1.5

0.3

YTD

0.2

1.0

0.1

0.5 05

06

07

08

09

Source: Reuters ThomsonOne, J.P. Morgan

10

11

12

13

14

0.0

0.2 0.1 0.0

05

06

07

08

Source: Reuters ThomsonOne, J.P. Morgan

12

06

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

Chart A21: Global M&A and LBO

0.0

G4 net equity issuance

09

10

11

12

13

14

Global Asset Allocation Flows & Liquidity 05 September 2014

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

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 Q1 2014

Equity and bond as % of total assets per quarter. G4 includes the US, the UK, Euro area and Japan. Last observation is Q1 2014. 55%

250 Bonds

200

50%

150

Bonds

45%

100 40%

50

35%

0 -50 -100 -150 Mar-99

Equities

30%

Equities

25%

Mar-02

Mar-05

Mar-08

Mar-11

Mar-14

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

20% Mar-99

Mar-02

Mar-05

Mar-08

Mar-11

Mar-14

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

Chart A25: Pension fund deficits 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 Jul 2014.

Chart A26: G4 pension funds and insurance companies cash and alternatives levels Equity and bond as % of total assets per quarter. G4 includes the US, the UK, Euro area and Japan. Last observation is Q1 2014.

100 0

25%

-100

UK

20%

Alternatives

-200

15%

-300

US

-400

Cash

10%

-500 -600 Dec-09

5% Dec-10

Dec-11

Source: Milliman, UK Pension Protection Fund, J.P. Morgan

Dec-12

Dec-13

0% Mar-99

Mar-02

Mar-05

Mar-08

Mar-11

Mar-14

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

13

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

Global Asset Allocation Flows & Liquidity 05 September 2014

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 July 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. €bn

Target 2 bal. Target 6m chng ECB borrowing Depo 3m chng Depo 12m chng

Austria

-39

-1

8

0.1%

0.1%

Belgium

-21

-5

14

0.6%

7.9%

Cyprus

-5

2

100

1.8

0

2

3.4%

12.1%

-100

1.3 10y Spanish and Italian govt spread vs Bunds

2.3

Finland

13

-2

0

4.8%

8.0%

-200

2.8

France

-31

17

54

4.1%

6.1%

444

-57

18

1.5%

2.4%

-300

3.3

Germany Greece

-32

20

45

-1.8%

-12.3%

-400

3.8

Ireland

-46

24

22

-6.4%

-10.5%

-500

4.3

Italy

-130

69

165

1.7%

0.3%

-600

4.8

Luxembourg

103

-2

1

-1.7%

-6.4%

Netherlands

2

-43

6

-1.1%

2.4%

-700

Portugal

-60

-1

38

2.0%

5.6%

Spain

-213

19

173

1.7%

2.7%

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

-800 Jan-11 Oct-11

Jul-12

Spanish and Italian 5.3 Target2 5.8 Apr-13 Jan-14

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: 5-Sep-14

Core

900

Last observation:

3-Sep-14

800

EMU bank unsecured gross issuance

700 600

20

500 15

400 300

10

200 5

Oct-12 Jan-13 Apr-13 Source: Dealogic, J.P. Morgan

14

100

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 05 September 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: 29-Aug-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 0.4

Last observation: 19-Aug-14

-2

Japanese retail flow (4 wk avg.) 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

1000

Topix

8

-0.3 -0.4

0.0

89

92

95

98

01

04

07

10

13

Source: Tokyo Stock Exchange, J.P. Morgan

500

-0.5

10 Domestic FX margin traders

-0.6 12 Jan-11 Jul-11 Jan-12 Jul-12 Jan-13 Jul-13 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: 29-Aug-14

20

Foreign investors' buying of Japanese equities 15

15

Last observation: 19-Aug-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.

15

Global Asset Allocation Flows & Liquidity 05 September 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: 26-Aug-14

35

Last observation: 3-Sep-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: Aug-14

2000

300

1800

250

Last observation: 3-Sep-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.

16

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Global Asset Allocation Flows & Liquidity 05 September 2014

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Global Asset Allocation Flows & Liquidity 05 September 2014

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