China Equity Strategy - jrj.com.cnpg.jrj.com.cn/acc/Res/CN_RES/INVEST/2016/7/13/4c0502e2-2f83-4974-9afd-afe5b0ec2b92.pdfJul 13, 2016 · China Equity Strategy Page 2 Deutsche Bank

Deutsche Bank Markets Research

Asia

China

Strategy

China Equity Strategy

Date

13 July 2016

Strategy Update

Industrial reflation amid weak CPI to expand equity valuations

________________________________________________________________________________________________________________

Deutsche Bank AG/Hong Kong

Deutsche Bank does and seeks to do business with companies covered in its research reports. Thus, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in making their investment decision. DISCLOSURES AND ANALYST CERTIFICATIONS ARE LOCATED IN APPENDIX 1. MCI (P) 057/04/2016.

Yuliang Chang, CFA

Strategist

(+852 ) 2203 6195

[email protected]

Joseph Huo

Strategist

(+852 ) 2203 6251

[email protected]

PPI may rise further, following M1/M2 spread

-2.8

10.2

-15

-10

-5

0

5

10

15

-15

-10

-5

0

5

10

15

Jan

-04

Au

g-0

4

Mar-

05

Oct-

05

May-

06

Dec-0

6

Ju

l-07

Feb

-08

Sep

-08

Ap

r-09

Nov-

09

Ju

n-1

0

Jan

-11

Au

g-1

1

Mar-

12

Oct-

12

May-

13

Dec-1

3

Ju

l-14

Feb

-15

Sep

-15

Ap

r-16

pptyoy % PPI (lag 6m)

M1 minus M2 (3m MA; RHS)

M1-M2 vs. PPI (lag 6m)

Correlation = 75%

Source: Bloomberg Finance LP, Deutsche Bank Strategy Research

Domestic rates remain low and supportive

2.8%2.5%

4.0%

3.2%

1%

2%

3%

4%

5%

6%

7%

8%

Ju

l-14

Sep

-14

Nov-1

4

Jan

-15

Mar-

15

May-1

5

Ju

l-15

Sep

-15

Nov-1

5

Jan

-16

Mar-

16

May-1

6

Ju

l-16

10y China gov't bond 7d repo (20D MA)

3m wealth mgmt product 6m bill discount rate

Market rates stay low, suggesting accommodative financial conditions

Source: Wind, Deutsche Bank Strategy Research

Short-sell ratio stays at a high level of 11%

7.2%6.7%

13.4%

12.0%

14.7%

7.3%

13.4%13.8%

16.4%

11.1%

4%

6%

8%

10%

12%

14%

16%

18%

7,000

8,000

9,000

10,000

11,000

12,000

13,000

14,000

15,000

16,000

Jan

-12

Mar-

12

May-1

2Ju

l-12

Sep

-12

Nov-1

2Jan

-13

Mar-

13

May-1

3Ju

l-13

Sep

-13

Nov-1

3Jan

-14

Mar-

14

May-1

4Ju

l-14

Sep

-14

Nov-1

4Jan

-15

Mar-

15

May-1

5Ju

l-15

Sep

-15

Nov-1

5Jan

-16

Mar-

16

May-1

6Ju

l-16

HSCEI Short sell turnover as % of total (5-day MA, RHS)


Both growth and rates outlook seem favorable for re-rating of Chinese equities With heightened uncertainty post-Brexit, global investors are weighing up the tug of war between softening growth and falling rates. Judging which side will dominate global asset pricing may prove difficult at the current juncture, given significant uncertainty regarding how and when Brexit might progress. For Chinese equities, we believe both the growth and the rates outlook seem favorable for valuation expansion from current discounted levels, considering that 1) strengthening industrial pricing (PPI) may further revive corporate growth and profitability, while 2) weak consumer pricing (CPI) and more DM monetary easing may keep domestic market rates subdued.

Chinese equities have outperformed EU/JP but lagged EMs since 19 May. We believe our expected industrial reflation amid weak CPI presents a Goldilocks macro backdrop in the near term. Also considering the depressed valuations, stretched underweight/shorted investor positioning, and visible fund inflows from Chinese investors, we reiterate our positive market view and target HSCEI/MSCI China at 10,000/64 by end-2016. By sector, we prefer domestic demand and continue to suggest overweight financials, IT, and industrials; we recently also upgraded energy and downgraded utilities.

Why PPI may pick up further and how that could help corporate fundamentals We think China’s PPI is likely to pick up further in the coming months, thanks to 1) rising industrial demand on the lagged effect of supportive policies, 2) low industrial inventory after lengthened and sizable destocking, and 3) an easier comparison base. The potential acceleration of supply-side reform (capacity cuts) could be a plus. Recently, domestic commodity prices grinded higher again, reversing the downward pressure seen in May.

As activity stabilizes and PPI expands, nominal growth has rebounded notably YTD. Looking ahead, we see an extended nominal growth acceleration amid a rising PPI, further reviving corporate fundamentals, especially profit margin/ ROE. Specifically, many up-/mid-stream sectors have seen ASP and/or volume pick up in 2Q16 (including steel, coal, cement, etc), reinforcing our earlier expectation of strengthening earnings momentum; we continue to expect more consensus earnings upgrades as interim results loom.

Why CPI may stay weak and how that may weigh on domestic market rates While recent floods may raise short-term food prices, we believe China’s CPI is likely to stay weak in the coming months, given 1) sluggish consumption demand, with the earlier industrial slowdown putting pressure on employment and household income; 2) rising food supply, which may drag consumer prices, and 3) a tougher comparison base. As global uncertainty intensifies, major central banks are readying additional easing. The resulting ultra-low interest rates in DM fixed income markets have widened the EM vs. DM yield spread, possibly luring yield-hungry institutions back to EMs, China included.

China’s market rates are hovering at low levels and credit spreads remain tight, thanks to the PBoC’s easing bias. If CPI stays weak and DMs provide more loosening, domestic market rates may remain subdued, boding well for corporate fundamentals, commodity prices, and equity valuations.

Distributed on: 07/12/2016 17:13:33GMT

13 July 2016


Page 2 Deutsche Bank AG/Hong Kong

Both growth and rates outlook seem favorable for re-rating of Chinese equities

With uncertainty heightened post-Brexit, global investors are gauging the tug

of war between softening growth and falling rates: on the one hand, possible

delays and/or cancelations of business (capex/hiring) plans may hurt the

already-fragile global economy, especially in the UK/EU; on the other hand,

major central banks may launch additional policy loosening, pushing global

rates even lower.

Judging which side will dominate global asset pricing may prove difficult at the

current juncture, given the significant uncertainty over how and when Brexit

might progress. For Chinese equities, we believe both the growth and the

rates outlook seem favorable for valuation expansion from current low levels

in the coming months, considering that

1) strengthening industrial pricing (PPI) may further revive corporate

growth and profitability, while

2) weak consumer pricing (CPI) and more DM monetary easing may

keep domestic market rates subdued.

Since 19 May, A-shares (CSI300) have returned 2% and H-shares (MSCI China)

have risen 6% in USD terms, outperforming Japan and Europe, while

underperforming other EMs, including Brazil, Indonesia, Taiwan, etc (Figure 1).

We believe our expected industrial reflation amid weak consumer inflation

presents a Goldilocks macro backdrop. Also taking into account the

depressed valuations (Figure 2), stretched underweight/shorted investor

positioning (Figure 3~Figure 4; see Is H-share shorts the next pain trade? 31

May), and visible fund inflows from Chinese investors (Figure 5~Figure 6; see

Elevated A/H premium to strengthen SB inflow; overseas funds may follow, 7

Apr), we reiterate our positive market view and target HSCEI/MSCI China at

10,000/64 by end-2016.

By sector, we prefer domestic demand and continue to suggest overweight

financials, IT and industrials; we recently also upgraded energy and

downgraded utilities. See Figure 7 for our sector preferences and Figure 8 for

our top-10 picks from a top-down strategist’s perspective. See more analysis in

our latest monthly strategy series, China Strategy Spotlight - Post-Brexit: focus

on domestic demand and SB inflow, 30 Jun.

13 July 2016


Deutsche Bank AG/Hong Kong Page 3

Figure 1: Chinese equities have outperformed EU/JP

while lagging other EMs since 19 May

Figure 2: MSCI China (ex. ADRs) trades at 9.6x 12m

forward P/E, a 16% discount to the 10-year average

-1%0%

2%

2%

4%

4%

4%

5%

6%

6%

6%

7%

7%

8%

8%

8%

8%

10%

12%13%

14%

18%

Europe

Japan

H-shr S.cap

A-share

China ADRs

Russia

SHCOMP

US

Hong Kong

H-share

ChiNext

S.E. Asia

Singapore

Asia x. JP

S. Korea

India

EM

SZCOMP

S. America

Taiwan

Indonesia

Brazil

Global equities return since May 19 (in USD)

9.6x

13.8x13.1x

5x

10x

15x

20x

25x

30x

35x

Jan

-05

Ju

n-0

5

Nov-0

5

Ap

r-06

Sep

-06

Feb

-07

Ju

l-0

7

Dec-0

7

May-0

8

Oct-

08

Mar-

09

Au

g-0

9

Jan

-10

Ju

n-1

0

Nov-1

0

Ap

r-11

Sep

-11

Feb

-12

Ju

l-1

2

Dec-1

2

May-1

3

Oct-

13

Mar-

14

Au

g-1

4

Jan

-15

Ju

n-1

5

Nov-1

5

Ap

r-16

12m fwd P/E (X)ex. ADRs

MSCI China

MSCI China ex. financials

MSCI China ex. financials & energy

+1 SD= 14.7x

-1 SD= 8.3x

10-yr avg.= 11.5x

now 10-yr avg. premium

9.6x 11.5x -16%

13.8x 12.6x 10%

13.1x 13.5x -3%

Source: Bloomberg Finance LP, MSCI, Deutsche Bank Strategy Research


Figure 3: China-dedicated institutional investors

overweight discretionary and healthcare, while

underweight financials, telcos and IT

Figure 4: Short sell ratio has come down in the past few

weeks from an all-time-high of 16.4% in mid-May; the

current 11% still looks high in a historical context

-7.2-5.9

-2.8

-0.8 -0.7

2.23.0 3.3

8.6

-7.1

-4.6

-1.2 -1.0 -0.7

2.5

0.8

2.9

8.2

-10

-5

0

5

10

15AUM weighted Simple average10 largest China funds'

sector allocation vs. MSCI China (in ppt)as of May-2016

Underweight

Overweight

7.2%6.7%

13.4%

12.0%

14.7%

7.3%

13.4%13.8%

16.4%

11.1%

4%

6%

8%

10%

12%

14%

16%

18%

7,000

8,000

9,000

10,000

11,000

12,000

13,000

14,000

15,000

16,000 Jan

-12

Mar-

12

May-1

2

Ju

l-1

2

Sep

-12

Nov-1

2

Jan

-13

Mar-

13

May-1

3

Ju

l-1

3

Sep

-13

Nov-1

3

Jan

-14

Mar-

14

May-1

4

Ju

l-1

4

Sep

-14

Nov-1

4

Jan

-15

Mar-

15

May-1

5

Ju

l-1

5

Sep

-15

Nov-1

5

Jan

-16

Mar-

16

May-1

6

Ju

l-1

6

HSCEI Short sell turnover as % of total (5-day MA, RHS)

Source: Fund report, MSCI, Deutsche Bank Strategy Research


Figure 5: Southbound inflows to HK stocks have surged

significantly since May this year

Figure 6: Southbound investors have been focusing on

large H-share banks since mid-May

199

120

136

121

149

121

149

121

147 146

129

139134

131

105

115

125

135

145

155

165

175

0

40

80

120

160

200

240

Jan

-15

Feb

-15

Mar-

15

Ap

r-1

5

May-1

5

Ju

n-1

5

Ju

l-15

Au

g-1

5

Sep

-15

Oct-

15

Nov-1

5

Dec-1

5

Jan

-16

Feb

-16

Mar-

16

Ap

r-16

May-1

6

Ju

n-1

6

Ju

l-16

Rmb bn SHSC southbound flow (lag 20-day) A/H premium (HSAHP; RHS)

SB flow trails A/H premium

A leads H

A leads H

A lags H

9%

41%

21%

40% 40%

4%

24%

9%

33%

23%

0%

10%

20%

30%

40%

50%

60%

70%

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

May-1

9

May-2

0

May-2

3

May-2

4

May-2

5

May-2

6

May-2

7

May-3

0

May-3

1

Ju

n-0

1

Ju

n-0

2

Ju

n-0

3

Ju

n-0

6

Ju

n-1

3

Ju

n-1

4

Ju

n-1

5

Ju

n-1

6

Ju

n-1

7

Ju

n-2

0

Ju

n-2

1

Ju

n-2

2

Ju

n-2

3

Ju

n-2

4

Ju

n-2

7

Ju

n-2

8

Ju

n-2

9

Ju

n-3

0

Ju

l-04

Ju

l-05

Ju

l-06

Ju

l-07

Daily SHSCsouthbound net inflows (RMB bn)

Big-4 Chinese banks

Others

Big-4 banks as % of SB net flows (RHS)

SB net inflows as % of Big-4 banks' daily turnover (RHS)


Source: Bloomberg Finance LP, CCASS, Deutsche Bank Strategy Research

13 July 2016



Figure 7: We suggest overweighting financials, info tech and industrials, while underweighting telecom, utilities and

staples; we are market-weight on discretionary, energy, health care, materials and utilities

Index

weight

Advised

weightDiff.

12m fwd

P/E (X)

12m fwd

P/B (X)

10-yr val.

z-scoreOverweight Market-weight Underweight

Banks

Insurance

Diversified Financials

Real Estate

Info. Tech. 31% 34% 3% 24.3 4.7 -0.0 Internet & Software Hardware & Semicon

Industrials 6% 8% 2% 9.3 0.9 -0.9 Capital Goods Transportation

Automobiles

Retailing & Others

Oil, Gas & Services

Coal

Health Care 2% 2% 0% 16.8 2.5 -0.7 Health Care

Materials 1% 1% 0% 14.0 0.8 0.6 Construction Materials Other Basic Materials

Telecom 9% 4% -5% 13.6 1.3 0.1 Telecom

Utilities 3% 1% -2% 9.2 1.2 -1.7 Water/Gas/Renew. IPPs

Cons. Stap. 2% 0% -2% 18.9 2.5 0.2 Household Products Food & Beverage

Market-

weight

(MW)

Under-

weight

(UW)

1.0

Energy 7% 7% 0% 20.9 0.8 2.8

6.0 0.7 -1.1

Cons. Disc. 8% 8% 0% 16.6 2.0

MSCI China

GICS Sector

Financials 30% 34% 4%Over-

weight

(OW)

Source: Bloomberg Finance LP, MSCI, Deutsche Bank Strategy Research Note: 5-year valuation z-score refers to the standard deviation from past 5-year historical average in terms 12-month forward P/E, except for financials, which are based on 12-month trailing P/B

Figure 8: Deutsche Bank China Strategy’s 2016 China top-10 picks from a top-down strategist’s perspective

Ticker Company Name

GICS

Sector

Price

Jul 11

(LOC)

Return

YTD

Shr-class

Mkt Cap

(USDm)

3M ADT

(USDm)

5-yr

Beta

MXCN

16E

P/E

16E

P/B

16E

ROAE

16E

Div.

Yield

16E

EPS

Gwth

17E

EPS

Gwth

DB

Rating

Target

Price

2318 HK Ping An Financials 33.80 -20% 33,165 131 1.2 10.3 1.4 15% 1.7% -3% 9% Buy 51.9

3968 HK China Merchants Bank Financials 17.02 -3% 10,178 51 1.2 6.3 0.9 15% 4.7% 3% 6% Buy 20.1

6886 HK Huatai Securities Financials 16.72 -4% 3,829 11 1.4 12.6 1.2 10% 2.5% -31% 17% Buy 19.0

388 HK HKEx Financials 185.10 -5% 29,326 135 1.0 34.9 7.4 22% 2.6% -20% 10% Hold 155.0

3311 HK CSCI Industrials 10.44 -21% 6,062 12 1.1 8.6 1.6 20% 3.5% 18% 18% Buy 15.1

914 HK Anhui Conch Cement Materials 18.84 -7% 3,350 25 1.2 12.3 1.2 10% 2.4% 32% 15% Buy 24.4

2357 HK AviChina Industrials 5.72 -6% 1,768 5 1.2 25.0 2.1 9% 0.6% 27% 19% Buy 8.4

BABA US Alibaba Info. Tech. 81.46 0% 203,265 1,200 0.7 28.2 5.2 23% 0.0% 15% 21% Buy 110.0

NTES US NetEase Info. Tech. 196.62 9% 25,851 223 0.7 17.4 4.6 29% 1.3% 39% 13% Buy 207.0

EDU US New Oriental Cons. Disc. 41.84 33% 6,566 67 0.6 22.4 4.2 19% 0.4% 27% 20% Buy 47.0

Equal weight 32,336 186 1.0 17.8 3.0 17% 2.0% 11% 15%

DB 2016 China Top-10 Picks Consensus Estimates (calendarized) DB Rating


13 July 2016



Why PPI may pick up further and how that could help corporate fundamentals

We think China’s PPI is likely to pick up further in the coming months, thanks

to 1) rising industrial demand stemming from the lagged effect of both credit

creation and fiscal expansion, 2) low industrial inventory after lengthened and

sizable destocking, and 3) an increasingly easier yoy comparison base.

Indeed, we find that domestic commodity prices have grinded higher again

across the board in recent weeks, after a short-lived pullback during May. See

our earlier note on the same topic, Joining the dots: Inventory, demand and

prices point to a cyclical recovery, 3 Mar.

As activity stabilizes and PPI expands, nominal growth has rebounded notably

YTD (see China 1Q16 Earnings Review - Growth rebounded further, 5 May).

Looking ahead, we see extended nominal growth acceleration amid a rising

PPI, further reviving corporate fundamentals, especially profit margin/ROE.

Specifically, many up-/mid-stream sectors (such as steel, coal, oil, cement,

machinery, etc) have already seen an ASP and/or volume pick-up in 2Q16,

reinforcing our earlier expectation of strengthening earnings momentum in the

quarter, and we continue to expect more consensus upgrades as interim

results loom.

Rising industrial demand on lagged effect of supportive policies

Credit creation: We prefer adjusted total social financing (TSF;

excluding equity financing, while adding back municipal bond balance)

as the most comprehensive gauge for China’s credit creation,

considering that the local government debt swaps have under-

reported the actual credit extended (see China Equity Strategy - PBoC

suggests actual credit creation strengthened further in April, 16 May).

The indicator troughed in June last year and since then has grinded

higher to 16.8% in May this year (Figure 9), suggesting a visible

acceleration in credit growth, especially in the key credit channels,

including bank loans, corporate bonds, trusts, etc (Figure 10).

Figure 9: Adjusted TSF troughed in Jun 2015 and

accelerated to 16.8% in May 2016

Figure 10: Key credit channels have strengthened since

last summer; forex loans & bill have contracted notably

12.6%

16.8%

11.8%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Jan

-04

Ju

l-04

Jan

-05

Ju

l-05

Jan

-06

Ju

l-06

Jan

-07

Ju

l-07

Jan

-08

Ju

l-08

Jan

-09

Ju

l-09

Jan

-10

Ju

l-10

Jan

-11

Ju

l-11

Jan

-12

Ju

l-12

Jan

-13

Ju

l-13

Jan

-14

Ju

l-14

Jan

-15

Ju

l-15

Jan

-16

balance growth yoy

Reported headline total social financing (TSF)

Adjusted TSF (ex. equity; added muni-bond)

M2

Adjusted TSF growth

stayed strong in May

-25.9%

20.7%

16.8%

8%

12%

16%

20%

24%

28%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

Jan

-12

Ap

r-1

2

Ju

l-12

Oct-

12

Jan

-13

Ap

r-1

3

Ju

l-13

Oct-

13

Jan

-14

Ap

r-1

4

Ju

l-14

Oct-

14

Jan

-15

Ap

r-1

5

Ju

l-15

Oct-

15

Jan

-16

Ap

r-1

6

Ju

l-16

yoyyoyForex loans + accepted bills

Loans + bonds + trusts + entrusts + muni-bond (RHS)

Adjusted TSF (ex. equity; added muni-bond; RHS)

Key credit channels

expanded further in May, sustaining the strength in adjusted TSF

Forex loans and bills

contracted significantly

Source: CEIC, Wind, Deutsche Bank Strategy Research

Source: CEIC, Wind, Deutsche Bank Strategy Research

M1/M2 spread: The M1/M2 spread has consistently led PPI by six

months in the past decade (Figure 11), and the PPI surge YTD has

13 July 2016



closely followed the widening M1/M2 spread. A wider M1/M2 spread

generally indicates abundant corporate liquidity in a liquid format

(demand deposit), implying potentially higher corporate spending/

disbursement ahead, and we think PPI is likely to gather pace in the

coming months, if this tight historical correlation still holds.

Fiscal expansion: The Chinese government generally increases the

realized fiscal deficit as a share of GDP notably to combat any global/

regional crisis, including the Asian Financial Crisis (AFC) in 1997, the

Global Financial Crisis (GFC) in 2008 and the European Financial Crisis

(EFC) in 2011 (Figure 12), while raising the fiscal surplus when the

domestic economy overheats, e.g. during 2006~1H08. Most recently,

this ratio troughed by end-2014 at -1.8% and since then has kept

expanding to beyond -4% in 2Q16, creating notable aggregate

demand for the economy as government spending consistently

surpasses revenues (Figure 13).

Figure 11: A rising spread of M1 minus M2 generally

leads to stronger PPI, with a six-month lag

Figure 12: Realized fiscal deficit as a share of GDP has

surged strongly since end-2014, now at a historical high

-2.8

10.2

-15

-10

-5

0

5

10

15

-15

-10

-5

0

5

10

15

Jan

-04

Ju

l-04

Jan

-05

Ju

l-05

Jan

-06

Ju

l-06

Jan

-07

Ju

l-07

Jan

-08

Ju

l-08

Jan

-09

Ju

l-09

Jan

-10

Ju

l-10

Jan

-11

Ju

l-11

Jan

-12

Ju

l-12

Jan

-13

Ju

l-13

Jan

-14

Ju

l-14

Jan

-15

Ju

l-15

Jan

-16

pptyoy % PPI (lag 6m) M1 minus M2 (3m MA; RHS)

M1-M2 vs. PPI (lag 6m)

Correlation = 75%

3Q97

-0.3%

3Q02

-2.7%

2Q08

1.8%

2Q09

-2.4%

3Q11

-0.6%

4Q14

-1.8%

2Q16e

-4.4%

-6%

-4%

-2%

0%

2%

4%

1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Actual fiscal deficit/surplus as % of GDP (4Q MA)

'97 AFC '08 GFC '11 EFC

Expansionary

fiscal policy

Contractionary

fiscal policy


Source: Wind, Deutsche Bank Strategy Research Note: June and 2Q16 fiscal deficit is based on our estimate

Figure 13: Fiscal expenditure growth has been

consistently higher than revenues in recent quarters

Figure 14: Planned FAI investment for new projects

accelerated to 32.2% in 5M16 vs. 5.5% in 2015

13.6%

8.3%

0%

5%

10%

15%

20%

25%

30%

35%

40%

Mar-

11

Ju

n-1

1

Sep

-11

Dec-1

1

Mar-

12

Ju

n-1

2

Sep

-12

Dec-1

2

Mar-

13

Ju

n-1

3

Sep

-13

Dec-1

3

Mar-

14

Ju

n-1

4

Sep

-14

Dec-1

4

Mar-

15

Ju

n-1

5

Sep

-15

Dec-1

5

Mar-

16

Ju

n-1

6

ytd yoy Fiscal expenditure Fiscal revenue (RHS)

Fiscal deficit widens as expenditure surges

despite softening

revenues

7.4

32.2

-60

-40

-20

0

20

40

60

80

100

120

140

0

5

10

15

20

25

30

35

40

45

50

Ju

n-0

4

Dec-0

4

Ju

n-0

5

Dec-0

5

Ju

n-0

6

Dec-0

6

Ju

n-0

7

Dec-0

7

Ju

n-0

8

Dec-0

8

Ju

n-0

9

Dec-0

9

Ju

n-1

0

Dec-1

0

Ju

n-1

1

Dec-1

1

Ju

n-1

2

Dec-1

2

Ju

n-1

3

Dec-1

3

Ju

n-1

4

Dec-1

4

Ju

n-1

5

Dec-1

5

Ju

n-1

6ytd yoy %ytd yoy %

Planned FAI: projects under construction

FAI

Planned FAI: new projects (RHS)

Planned investments in

new projects jumped significantly in 2016



New investment project starts: Thanks to monetary, fiscal and

property policy loosening in the past few quarters, infrastructure and

property project new starts have increased significantly YTD, as

13 July 2016



evidenced by the higher planned investment for new FAI projects

(32% in 5M16 vs. 6% in 2015; Figure 14), stronger property new starts

(18% in 5M16 vs. -14% in 2015; Figure 15), and more land acquisitions

(41% in 5M16 vs. 5% in 2015; Figure 16). It is clear that these newly

started projects should raise demand for industrial products across the

supply chain, and may boost industrial pricing.

Figure 15: Property new project starts growth recovered

strongly to 18% in 5M16

Figure 16: Land auction sales surged to 41% in 5M16,

NBS-reported land transaction sales may follow soon

33%

18%

25 months 24m

13m

0

5

10

15

20

25 -50%

-25%

0%

25%

50%

75%

100%

125%

Dec-0

6

Ap

r-07

Au

g-0

7

Dec-0

7

Ap

r-08

Au

g-0

8

Dec-0

8

Ap

r-09

Au

g-0

9

Dec-0

9

Ap

r-10

Au

g-1

0

Dec-1

0

Ap

r-11

Au

g-1

1

Dec-1

1

Ap

r-12

Au

g-1

2

Dec-1

2

Ap

r-13

Au

g-1

3

Dec-1

3

Ap

r-14

Au

g-1

4

Dec-1

4

Ap

r-15

Au

g-1

5

Dec-1

5

Ap

r-16

Au

g-1

6

monthsytd yoyNationwide GFA sold

Nationwide GFA new start (lag 6m)

57-city 3m MA inventory months (reversed scale, RHS)

GFA new

start

GFA sold

77%

41% 34% 20%

-24%

5%

-75%

-50%

-25%

-0%

25%

50%

75%

100%

125%

150%

-100%

-50%

0%

50%

100%

150%

200%

Jan

-09

May-0

9

Sep

-09

Jan

-10

May-1

0

Sep

-10

Jan

-11

May-1

1

Sep

-11

Jan

-12

May-1

2

Sep

-12

Jan

-13

May-1

3

Sep

-13

Jan

-14

May-1

4

Sep

-14

Jan

-15

May-1

5

Sep

-15

Jan

-16

May-1

6

ytd yoyytd yoy SouFun land auction sales value

NBS land transaction value (lag 6m; RHS)

NBS land transaction

value (lag 6m)

SouFun land

auction value

Source: CEIC, SouFun, Wind, Deutsche Bank Strategy Research

Source: SouFun, Wind, Deutsche Bank Strategy Research

Figure 17: Property sales growth has moderated in

recent months on a higher comparison base last year

Figure 18: Absolute property sales volume has remained

elevated in recent weeks

9%

-20%

115%

22%

7%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

140%

Jan

-14

Mar-

14

May-1

4

Ju

l-14

Sep

-14

Nov-1

4

Jan

-15

Mar-

15

May-1

5

Ju

l-15

Sep

-15

Nov-1

5

Jan

-16

Mar-

16

May-1

6

Ju

l-16

Commodity house GFA soldmonthly yoy

30 large/med-size cities Tier 1

Tier 2 Tier 3

Jul-16 data updated

as of 10 Jul

800

1,039

867

0

200

400

600

800

1,000

1,200

2011 2012 2013 2014 2015 2016

GFAthousand sqm

30-city daily property sales volume (20D MA)



Durable goods consumption: Property sales have surged significantly

YTD, with nation-wide gross floor area (GFA) growth jumping to 33%

in 5M16, and property sales revenues growth leaping to 33% in 5M16.

Property sales growth may slow in the coming months, mainly due to

an escalating yoy comparison base last year (Figure 17), but sales

volumes have stayed at a very high absolute level lately (Figure 18).

The overall strength in nation-wide property sales (esp. tier-2 cities)

may continue, as the policy stance remains broadly supportive and

household affordability is improving (Figure 19). Passenger vehicle

(PV) wholesales have surged YTD and monthly growth reached 17.7%

in Jun vs. -1.5% in Feb (Figure 20), thanks to the ongoing effectiveness

of the 5ppt partial purchase tax cut for sub-1.6L PVs. See our auto

13 July 2016



analyst’s note June auto wholesale momentum surged on low base,

11 Jul.

Figure 19: Household affordability may have improved as

more banks offer lower mortgage rates

Figure 20: Passenger vehicle sales growth shot up

strongly to 17.7% in Jun

33

59

85

6.1

4.6

4.5

6.8

5.4

5.4

0

20

40

60

80

100

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

8.0

Jan

-15

Feb

-15

Mar-

15

Ap

r-15

May-1

5

Ju

n-1

5

Ju

l-15

Au

g-1

5

Sep

-15

Oct-

15

Nov-1

5

Dec-1

5

Jan

-16

Feb

-16

Mar-

16

Ap

r-16

May-1

6

Ju

n-1

6

%% % of banks offering discounts for first home mortgage (RHS)

Avg. mortgage rate for first house buyers

Avg. mortgage rate for second house buyers

Dec'14

16.0%

Jul'15

-6.6%

Nov'15

23.7%

Feb'16

-1.5%

Jun'16

17.7%

-10%

0%

10%

20%

30%

Mar-

13

May-1

3

Ju

l-1

3

Sep

-13

Nov-1

3

Jan

-14

Mar-

14

May-1

4

Ju

l-1

4

Sep

-14

Nov-1

4

Jan

-15

Mar-

15

May-1

5

Ju

l-15

Sep

-15

Nov-1

5

Jan

-16

Mar-

16

May-1

6

monthly yoy Passenger vehicle sales

Source: Rong360, Deutsche Bank Strategy Research


Figure 21: Industrial inventory destocking has lasted 21

months; its growth reached -1.1% in May 2016

Figure 22: Product inventory as a share of total assets

declined to 3.7% in May 2016

-1.1%

-20

0

20

40

60

80

-10

0

10

20

30

40

50

Jan

-00

Sep

-00

May-0

1

Jan

-02

Sep

-02

May-0

3

Jan

-04

Sep

-04

May-0

5

Jan

-06

Sep

-06

May-0

7

Jan

-08

Sep

-08

May-0

9

Jan

-10

Sep

-10

May-1

1

Jan

-12

Sep

-12

May-1

3

Jan

-14

Sep

-14

May-1

5

Jan

-16

yoy %yoy %Industrial enterprise inventory Mid-stream

Downstream Upstream (RHS)

22 months

12 months17 months

16 months21 months

Industrial inventorydestocking

50

46

3.7

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

40

42

44

46

48

50

52

54

Jan

-00

Sep

-00

May-0

1

Jan

-02

Sep

-02

May-0

3

Jan

-04

Sep

-04

May-0

5

Jan

-06

Sep

-06

May-0

7

Jan

-08

Sep

-08

May-0

9

Jan

-10

Sep

-10

May-1

1

Jan

-12

Sep

-12

May-1

3

Jan

-14

Sep

-14

May-1

5

Jan

-16

%% Industrial enterprise current asset as % of total asset

Industrial enterprise inventory as % of total assets (RHS)

Source: CEIC, Deutsche Bank Strategy Research


Low industrial inventory after lengthened and sizable destocking

Industrial inventory: Industrial enterprises’ (a comprehensive database

maintained by the National Bureau of Statistics) inventory growth

peaked in Aug 2014 and since then has kept contracting to -1.1% in

May this year, implying 21 months of inventory destocking (Figure 21).

Compared with historical cases, this episode seems long and large

enough (considering that the historical average is 17 months and the

-1.1% in May was the lowest-ever read). Meanwhile, industrial

enterprises’ current assets and inventory has been taking a smaller

share of total assets (Figure 22). We think the current destocking cycle

may have ended and we may see a re-stocking cycle soon as demand

recovers and risk aversion subsides.

PMI: The China manufacturing PMI shows both finished goods and

raw materials inventory staying in contraction territory. In particular,

the finished goods inventory and raw materials sub-indexes of the

NBS manufacturing PMI have been broadly underwater (<50) since

13 July 2016



1Q13 (Figure 23), suggesting that both inventories have been

contracting in the past few years. The Caixin manufacturing PMI’s two

inventory sub-indexes exhibit more monthly volatility but the overall

picture remains contraction in the past few years (Figure 24).

Figure 23: NBS manufacturing PMI’s two inventory sub-

indexes have been underwater since 1Q13

Figure 24: Caixin PMI’s raw materials and finished goods

inventory also mostly contracting in recent years

48.0

44.6

46.4

42

44

46

48

50

52

54

56

Jan

-12

Mar-

12

May-1

2

Ju

l-12

Sep

-12

Nov-1

2

Jan

-13

Mar-

13

May-1

3

Ju

l-13

Sep

-13

Nov-1

3

Jan

-14

Mar-

14

May-1

4

Ju

l-14

Sep

-14

Nov-1

4

Jan

-15

Mar-

15

May-1

5

Ju

l-15

Sep

-15

Nov-1

5

Jan

-16

China NBS manufacturing PMI%

Raw materials inventory Finished goods inventory

48.8

47.8

44

46

48

50

52

54

56

Jan

-12

Mar-

12

May-1

2

Ju

l-12

Sep

-12

Nov-1

2

Jan

-13

Mar-

13

May-1

3

Ju

l-13

Sep

-13

Nov-1

3

Jan

-14

Mar-

14

May-1

4

Ju

l-14

Sep

-14

Nov-1

4

Jan

-15

Mar-

15

May-1

5

Ju

l-15

Sep

-15

Nov-1

5

Jan

-16

Caixin China manufacturing PMI%

Raw materials inventory Finished goods inventory


Source: Haver Analytics, Deutsche Bank Strategy Research

Figure 25: A-share non-financial companies have been

cutting inventory receivables to free up working capital

and generate operating cash flow

Figure 26: Upstream inventory dropped notably to 7.7%

of assets in 1Q16 from 9.1% a year earlier, while mid-

/downstream inventory stayed largely flat

Net income (+)

DD&A (+)

Inventory (-)

Receivables (-)

Payables (+)

-600

-400

-200

0

200

400

600

800

201 2012 2013 2014 2015

Others Net income (+) DD&A (+)

Inventory (-) Receivables (-) Payables (+)

A-shr aggregate OCF(yoy chg Rmb bn)

Non-financials

7.7%

16.2%

31.5%

5%

10%

15%

20%

25%

30%

35%

40%

3M

03

9M

03

3M

04

9M

04

3M

05

9M

05

3M

06

9M

06

3M

07

9M

07

3M

08

9M

08

3M

09

9M

09

3M

10

9M

10

3M

11

9M

11

3M

12

9M

12

3M

13

9M

13

3M

14

9M

14

3M

15

9M

15

3M

16

Overall inventory as % of asset Upstream

Mid-stream Downstream

A-sharenon-financialsytd



A-share non-financials: As overall growth slowed, we found A-share

non-financial companies proactively destocking inventory and cutting

receivables to free up working capital and generate operating cash

flow (OCF; Figure 25). Accordingly, upstream sectors’ inventory

dropped notably to 7.7% of assets in 1Q16 from 9.1% a year earlier,

while mid-/downstream inventory stayed largely flat (Figure 26).

Steel and coal: Steel traders’ holding of steel inventory fell to 8.6mn

tons in early Jan. When steel prices surged, steel production resumed

and inventory piled up to 12.6mn tons in early Mar. Since then, steel

inventory has trended down again despite escalating production

growth and now stands at 8.5mn tons, the lowest level since 1Q09

(Figure 27). For coal, there is little doubt that inventory has shrunk at

key IPPs, key mines and a key port (Qinhuangdao; Figure 28). Perhaps

13 July 2016



more importantly, as the new 276-day rule was implemented in major

production areas, effective coal mine capacity contracted significantly,

as evidenced by the sharply lower coal production volume growth of

-11%/-15.5% in Apr/May, vs. rising cement/steel production growth.

Figure 27: Steel trade held inventory declined recently to

8.5mn, despite higher production volume

Figure 28: Coal inventory has shrunk visibly at key power

plants, key mines and key port

8.9

12.6

8.5

10-yr avg. = 11.8

-20%

-10%

0%

10%

20%

30%

40%

0

5

10

15

20

25

30

Mar-

06

Au

g-0

6

Jan

-07

Ju

n-0

7

Nov-0

7

Ap

r-0

8

Sep

-08

Feb

-09

Ju

l-09

Dec-0

9

May-1

0

Oct-

10

Mar-

11

Au

g-1

1

Jan

-12

Ju

n-1

2

Nov-1

2

Ap

r-1

3

Sep

-13

Feb

-14

Ju

l-14

Dec-1

4

May-1

5

Oct-

15

Mar-

16

mn tonnes Social-wide steel inventory (at steel traders)

Daily crude steel output growth yoy 4wk MA (RHS)

0

2

4

6

8

10

12

14

16

18

20

0

20

40

60

80

100

120

Dec-1

1

Mar-

12

Ju

n-1

2

Sep

-12

Dec-1

2

Mar-

13

Ju

n-1

3

Sep

-13

Dec-1

3

Mar-

14

Ju

n-1

4

Sep

-14

Dec-1

4

Mar-

15

Ju

n-1

5

Sep

-15

Dec-1

5

Mar-

16

Ju

n-1

6

mntonnes

mntonnes

Coal inventory at key IPP groups

Coal inventory at key mines

Coal inventory at QHD port (RHS)



Figure 29: 57-city property inventory decelerated to -9%

in May, led by tier-1 and tier-2 cities

Figure 30: 57-city inventory months declined sharply to

only 8.6 months, the lowest level since Jan 2011

-9%

-15%

-13%

4.5%

-20%

-10%

0%

10%

20%

30%

40%

50%

Ap

r-13

Ju

n-1

3

Au

g-1

3

Oct-

13

Dec-1

3

Feb

-14

Ap

r-14

Ju

n-1

4

Au

g-1

4

Oct-

14

Dec-1

4

Feb

-15

Ap

r-15

Ju

n-1

5

Au

g-1

5

Oct-

15

Dec-1

5

Feb

-16

Ap

r-16

SouFun property inventory yoy

57-city total Tier-1 cities Tier-2 cities Tier-3/4 cities

13.1

8.6

5.9 6.8 7.5

10.4 7.6

24.6

21.3

18.9

13.6

0

5

10

15

20

25

30

Jan

-10

Ap

r-10

Ju

l-10

Oct-

10

Jan

-11

Ap

r-11

Ju

l-11

Oct-

11

Jan

-12

Ap

r-12

Ju

l-12

Oct-

12

Jan

-13

Ap

r-13

Ju

l-13

Oct-

13

Jan

-14

Ap

r-14

Ju

l-14

Oct-

14

Jan

-15

Ap

r-15

Ju

l-15

Oct-

15

Jan

-16

Ap

r-16

SouFun propertyinventory months

57-city overall Tier-1 cities Tier-2 cities Tier-3/4 cities

Source: SouFun, Deutsche Bank Strategy Research

Source: SouFun, Deutsche Bank Strategy Research

Property: The yoy growth of 57-city property inventory peaked at 24%

in Sep 2014; since then it decelerated all the way to -9% in May 2016.

This is very similar to the trend we have seen in industrial enterprise

inventory in Figure 21 on page 8. The inventory contraction was

significant in tier-1 and tier-2 cities, whose growth stood at -15% and

-13%, respectively, in May 2016, while inventory in tier-3/4 cities was

still growing at 4.5% (Figure 29). Looking at the inventory months,

which shows the number of months needed to clean out all ready-for-

sale inventory based on the pace of sales in the past three months, we

find the ratio has come down sharply to only 8.6 months in May 2016,

the lowest level since Jan 2011 (Figure 30); tier-2 cities witnessed the

biggest drop in the past few months, plummeting 40% to only 7.6

months in May from 12.7 months in Feb this year.

13 July 2016



Supply-side reform: President Xi Jinping chaired an economic

conference on 8 Jul1. In the meeting, he stressed that the government

should “unswervingly push forward the supply-side structural reform”

(this sentence is also the title of the Xinhua press release), and would

“stabilize market expectation with stable macroeconomic policies, and

boost development confidence by launching key reform measures”. It

seems that the central leadership is moving one step closer to pulling

the trigger to accelerate the supply-side reform in 2H16. We will

watch closely the mid-year economic review conference at end-Jul,

when President Xi may crystallize the politburo standing committee’s

(PSC) policy determination on supply-side reform. After that, various

government agencies (NDRC, SASAC, PBoC, MoF, etc) may endorse

more specific implementation in the following months, especially in

SOE consolidation, steel and coal industry capacity cuts, etc. If we do

see meaningful progress in the supply-side reform, it could help

alleviate the oversupply situation in many industries and support

industrial product prices.

An increasingly easy yoy comparison base

Domestic commodity prices declined meaningfully in 3Q15, dragging down

the sequential PPI MoM change to deeply negative levels of -0.7/-0.8% in

Jul/Aug (Figure 31), and pushing the PPI yoy change to -5.9%, the lowest level

since Oct 2009 (Figure 32). The downward trending PPI in 3Q15 has made an

increasingly easier base for yoy comparison in the coming months; e.g.

mathematically, 3Q16 PPI yoy growth will shoot up further, as long as the PPI

sequential MoM decrease is less than the -0.7/-0.8/-0.4% seen in 3Q15.

Figure 31: 3Q16 PPI may pick up further, as long as the

sequential MoM change is better than -0.4%~-0.8%

Figure 32: PPI plunged in 3Q15, making an easier yoy

comparison base for 3Q16

-0.4

-0.7

-0.8

-0.4

-0.2

-1.2

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

PPI MoM % 2015 2016

PPI plunged in 3Q15, making an easier yoy comparison base for 3Q16

-4.8

-5.4

-5.9

-2.6

-7.0

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0


PPI YoY % 2015 2016

PPI plunged in 3Q15, making an easier yoy comparison base for 3Q16



Based on our above analysis of rising demand vs. subdued inventory, and

potentially intensifying supply-side reform (e.g. capacity cut), we think

domestic commodity and industrial product prices may strengthen

sequentially in the coming months, or at least drop less than last year,

sending PPI yoy growth higher.

Most recently, many domestic commodity prices have grinded higher again,

including steel, coal, metals, etc (Figure 33~Figure 34), reversing the earlier

1 See http://news.xinhuanet.com/politics/2016-07/08/c_1119189505.htm

13 July 2016



downward pressure seen in May. We suggest closely monitoring high-

frequency commodity prices to contemplate the future path of PPI.

Figure 33: Domestic commodity prices have picked up

again after a short-lived pullback in May

Figure 34: Industrial metal futures prices have shot up

again in recent weeks

50

60

70

80

90

100

110

Dec-1

3

Feb

-14

Ap

r-14

Ju

n-1

4

Au

g-1

4

Oct-

14

Dec-1

4

Feb

-15

Ap

r-15

Ju

n-1

5

Au

g-1

5

Oct-

15

Dec-1

5

Feb

-16

Ap

r-16

Ju

n-1

6

Rebased price Cement national avg. price Rebar steel: HRB400 20mm

Coal price (QHD 5500) Industrial commodities futures

20

30

40

50

60

70

80

90

100

110

120

130

Dec-1

3

Feb

-14

Ap

r-14

Ju

n-1

4

Au

g-1

4

Oct-

14

Dec-1

4

Feb

-15

Ap

r-15

Ju

n-1

5

Au

g-1

5

Oct-

15

Dec-1

5

Feb

-16

Ap

r-16

Ju

n-1

6

Rebasedfutures price

LME Copper Shanghai Copper Shanghai Aluminium

Shanghai Rebar Dalian Iron Ore

Industrial metal prices surged again since Jun

Source: Digital Cement, Wind, Deutsche Bank Strategy Research


Figure 35: Our economists expect GDP to stabilize at

6.7% in 2Q16

Figure 36: Power production growth shot up to 2% in

Jun, vs. -10% in May, boding well for industrial activity

7.3

7.4

7.2 7.2

7.0 7.0

6.9

6.8

6.7

6.6

6.56.5

6.7

6.6

6.4

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

6.0

6.5

7.0

7.5

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2014: 7.4% 2015: 6.9% 2016E: 6.7%

ppt% GDP yoy Spread: DB vs. consensus (RHS)

DB forecastConensus

forecast

2.1%

6%

2

4

6

8

10

12

14

16

18

-30

-20

-10

0

10

20

30

40

50

Oct-

10

Jan

-11

Ap

r-11

Ju

l-11

Oct-

11

Jan

-12

Ap

r-12

Ju

l-12

Oct-

12

Jan

-13

Ap

r-13

Ju

l-13

Oct-

13

Jan

-14

Ap

r-14

Ju

l-14

Oct-

14

Jan

-15

Ap

r-15

Ju

l-15

Oct-

15

Jan

-16

Ap

r-16

yoy %yoy %Coal consumption by 6 key IPP groups

Industrial production (RHS)

Thermal coal consumption vs. IP

Correlation = 77%

Thermal coal

consumption by IPPs spiked up in Jun, implying a rising IP



Nominal growth has rebounded YTD; a rising PPI could extend the uptrend

Economic activity growth has stabilized in recent quarters, and our chief

China economist Zhiwei Zhang expects 6.7% GDP growth in 2Q16, similar to

the level in 1Q16 (Figure 35). Coal-fired power production (based on coal

consumption by key power plants as a proxy) accelerated notably to 2% in Jun

from -10% in May, implying higher industrial production in the month, given

their tight historical correlation (Figure 36).

Taking into account the rising PPI, nominal growth has rebounded YTD.

Nominal GDP rose to 7.2% in 1Q16 vs. 6.4% in 2015, as the GDP

deflator recovered to 0.5% from -0.5% in 2015 (Figure 37).

Industrial companies’ revenues and earnings growth shot up to

2.9%/6.4% in 5M16 vs. 0.8%/-2.3% in 2015 (Figure 38).

13 July 2016



A-share non-financials’ revenues and earnings growth climbed to

4.6%/7.7% yoy in 1Q16 vs. -2%/-12.7% in 2015 (Figure 39).

A-share non-financials’ operating cash flow (OCF) also recovered, as

the ratio of trailing 12-month OCF to sales steadily picked up to 10.1%

in 1Q16 from 6.3% in 1Q14 (Figure 40).

Figure 37: GDP deflator has been lagging M1/M2 spread

by six months and may climb in coming months

Figure 38: Industrial revenues and earnings growth shot

up to 2.9% and 6.4% in 5M16

-15

-10

-5

0

5

10

15

-4

0

4

8

12

16

Mar-

02

Oct-

02

May-0

3

Dec-0

3

Ju

l-04

Feb

-05

Sep

-05

Ap

r-06

Nov-0

6

Ju

n-0

7

Jan

-08

Au

g-0

8

Mar-

09

Oct-

09

May-1

0

Dec-1

0

Ju

l-11

Feb

-12

Sep

-12

Ap

r-13

Nov-1

3

Ju

n-1

4

Jan

-15

Au

g-1

5

Mar-

16

pptytd yoy % GDP deflator (lag 6m) M1 minus M2 (3m MA; RHS)

M1-M2 vs. GDP deflator (lag 6m)

Correlation = 68%

2015

-2.3

7.4

5M16

6.4

0.8

2.9

0

1

2

3

4

5

6

7

8

9

10

-6

-4

-2

0

2

4

6

8

10

12

14

Jan

-14

Feb

-14

Mar-

14

Ap

r-14

May-1

4

Ju

n-1

4

Ju

l-14

Au

g-1

4

Sep

-14

Oct-

14

Nov-1

4

Dec-1

4

Jan

-15

Feb

-15

Mar-

15

Ap

r-15

May-1

5

Ju

n-1

5

Ju

l-15

Au

g-1

5

Sep

-15

Oct-

15

Nov-1

5

Dec-1

5

Jan

-16

Feb

-16

Mar-

16

Ap

r-16

May-1

6

Ju

n-1

6

Ju

l-16

ytd yoy %ytd yoy % Industrial profits growth Industrial revenue growth



Figure 39: A-share non-financials’ revenues and earnings

growth climbed to 4.6%/7.7% yoy in 1Q16

Figure 40: The ratio of trailing 12-month OCF to sales

steadily picked up to 10.1% in 1Q16 from 6.3% in 1Q14

-17.0%

13.3%

0.9% -0.5%

-12.7%

7.7%

6.2%

9.2%

4.4%

-2.0%

4.6%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

3M

12

1H

12

9M

12

2012

3M

13

1H

13

9M

13

2013

3M

14

1H

14

9M

14

2014

3M

15

1H

15

9M

15

2015

3M

16

A-share non-financialsytd yoy

Net income Sales

19.4%

8.0%

10.1%

0%

5%

10%

15%

20%

0%

5%

10%

15%

20%

25%

2003

1H

04

2004

1H

05

2005

1H

06

2006

1H

07

2007

1H

08

2008

1H

09

2009

1H

10

2010

1H

11

2011

1H

12

2012

1H

13

2013

1H

14

2014

1H

15

2015

Inventory as % of asset

Receivables as % of asset

OCF to sales (RHS)

A-sharenon-financialstrailing 12M

Continuous inventory and receivables

cuts have been boosting the ability to

generate cash from sales



Looking ahead, if PPI rises further (as we expect), nominal growth

acceleration will likely continue, further reviving corporate fundamentals,

especially profit margin/ROE and cash flow.

As PPI and nominal GDP growth recover, non-financial companies’

top-line revenue growth should also gather pace, based on their tight

historical correlation (Figure 41). This may 1) raise asset turnover

given the continuous working capital cut (especially inventory and

receivables), and 2) boost profit margins given Chinese companies’

high operational leverage.

Indeed, we find up-/mid-stream sectors’ net profit margin is highly

(76%) correlated with PPI yoy growth (Figure 42). This should not be

13 July 2016



surprising, as rising industrial output prices, as proxied by PPI,

generally imply stronger bargaining power for industrial companies.

Based on DuPont analysis, we think non-financials’ ROE may rebound

thanks mainly to higher asset turnover and stronger net profit margins,

while financial leverage may stay largely flat or even dip a bit.

In addition, stronger top-line revenue growth is clearly conducive to

corporate operating cash flows and liquidity conditions, restoring

Chinese non-financial companies’ overall debt servicing ability.

Figure 41: Non-financial top-line sales growth has been

highly correlated with nominal GDP growth

Figure 42: Up-/mid-stream profit margin corresponds

closely to PPI

1H16 DBe

7.5%

A-shr

3M16

7.5%

H-shr

2015

-5.3% -20%

0%

20%

40%

60%

80%

0

5

10

15

20

25

30

Mar-

03

Sep

-03

Mar-

04

Sep

-04

Mar-

05

Sep

-05

Mar-

06

Sep

-06

Mar-

07

Sep

-07

Mar-

08

Sep

-08

Mar-

09

Sep

-09

Mar-

10

Sep

-10

Mar-

11

Sep

-11

Mar-

12

Sep

-12

Mar-

13

Sep

-13

Mar-

14

Sep

-14

Mar-

15

Sep

-15

Mar-

16

ytd yoyytd yoy Nominal GDP growth

A-share non-financial sales growth (RHS)

H-share non-financial sales growth (RHS)

Non-fin. sales vs. Nominal GDP

Correlation = 79%

-2.9

-10

-5

0

5

10

15

2

4

6

8

10

Sep

-03

Mar-

04

Sep

-04

Mar-

05

Sep

-05

Mar-

06

Sep

-06

Mar-

07

Sep

-07

Mar-

08

Sep

-08

Mar-

09

Sep

-09

Mar-

10

Sep

-10

Mar-

11

Sep

-11

Mar-

12

Sep

-12

Mar-

13

Sep

-13

Mar-

14

Sep

-14

Mar-

15

Sep

-15

Mar-

16

yoy %ytd % A-share up-/mid-stream net profit margin (4Q MA) PPI (RHS)

PPI vs. up/mid-stream margin

Correlation = 76%



2Q16 growth has recovered; consensus sees upgrades as interim results loom

Many up-/mid-stream sectors (steel, coal, oil, cement, machinery, etc) have

already seen an ASP and/or volume pickup in 2Q16, reinforcing our earlier

expectation of strengthening earnings momentum. See Industrial profits

surged further, earnings upgrades may follow, 27 Apr.

Cement: The national average cement price change recovered to -8%

in 2Q16 from -20% in 1Q16 (Figure 43); meanwhile, nation-wide

production volume growth stayed healthy at 3.7% in 5M16, largely the

same as the 3.5% in 3M16 (Figure 46).

Steel: Rebar steel’s (HRB 400 20mm) national average price

appreciated 6% in 2Q16, a sharp leap from the -18% in 1Q16 (Figure

44); the crude steel production volume improved to -1.4% in 5M16 vs.

-3.2% in 3M16 (Figure 46).

Coal: Qinhuangdao’s 5500k coal price change improved to -6% in

2Q16 from -23% in 1Q16 (Figure 45); however, its production volume

growth slowed to -8.4% in 5M16 from -5.3% in 3M16 (Figure 46), as

the newly enacted 276-day rule weighs on production.

13 July 2016



Figure 43: Cement ASP yoy growth recovered to -8% in

2Q16 from the deeply negative -20% in 1Q16

Figure 44: Rebar steel ASP yoy change accelerated to

+6% in 2Q16 vs. -18% in 1Q16

220

240

260

280

300

320

Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Cement national avg. price (Rmb/t)

2015 2016

1Q15 avg = 298

1Q16 avg = 238

-20% yoy

2Q15 avg = 274

2Q16 avg = 252

-8% yoy

1,800

2,000

2,200

2,400

2,600

2,800

3,000

3,200


Rebar steel HRB400 20mm national avg. price (Rmb/t)

2015 2016

1Q15 avg = 2,579

1Q16 avg = 2,123

-18% yoy

2Q15 avg = 2,403

2Q16 avg = 2,538

+6% yoy

Source: Digital Cement, Deutsche Bank Strategy Research


Figure 45: Coal price (QHD 5500k) yoy growth improved

to -6% in 2Q16 vs. -23% in 1Q16

Figure 46: Cement/steel production accelerated in 2Q16,

while that of coal slowed due to the new 276-day rule

300

350

400

450

500

550


Coal QHD5500k price (Rmb/t)

2015 2016

1Q15 avg = 487

1Q16 avg = 373

-23% yoy

2Q15 avg = 411

2Q16 avg = 387

-6% yoy

11.2

-8.2

3.7

-1.4

-8.4

-10

-8

-6

-4

-2

0

2

4

6

-12

-6

0

6

12

18

24Feb

-14

Mar-

14

Ap

r-14

May-1

4

Ju

n-1

4

Ju

l-14

Au

g-1

4

Sep

-14

Oct-

14

Nov-1

4

Dec-1

4

Jan

-15

Feb

-15

Mar-

15

Ap

r-15

May-1

5

Ju

n-1

5

Ju

l-15

Au

g-1

5

Sep

-15

Oct-

15

Nov-1

5

Dec-1

5

Jan

-16

Feb

-16

Mar-

16

Ap

r-16

May-1

6

ytd yoy %ytd yoy % Cement production volume growth

Crude steel production volume growth (RHS)

Coal production volume growth (RHS)



Figure 47: Excavator sales growth surprisingly

accelerated to 11% in Jun

Figure 48: Excavator utilization hours’ yoy growth

recovered to a healthy 10% level in Jun

11.5

3.8

12.7

6.5

4.2

33%

-23%

11%

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

0

5

10

15

20

25

Jan

-14

Feb

-14

Mar-

14

Ap

r-14

May-1

4

Ju

n-1

4

Ju

l-14

Au

g-1

4

Sep

-14

Oct-

14

Nov-1

4

Dec-1

4

Jan

-15

Feb

-15

Mar-

15

Ap

r-15

May-1

5

Ju

n-1

5

Ju

l-15

Au

g-1

5

Sep

-15

Oct-

15

Nov-1

5

Dec-1

5

Jan

-16

Feb

-16

Mar-

16

Ap

r-16

May-1

6

Ju

n-1

6

China excavator sales (ex. XCMG) Monthly growth yoy (RHS)Thousand units

117

130

5%

-10%

29%

1%

10%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

0

50

100

150

200

Jan

-14

Feb

-14

Mar-

14

Ap

r-14

May-1

4

Ju

n-1

4

Ju

l-14

Au

g-1

4

Sep

-14

Oct-

14

Nov-1

4

Dec-1

4

Jan

-15

Feb

-15

Mar-

15

Ap

r-15

May-1

5

Ju

n-1

5

Ju

l-15

Au

g-1

5

Sep

-15

Oct-

15

Nov-1

5

Dec-1

5

Jan

-16

Feb

-16

Mar-

16

Ap

r-16

May-1

6

Ju

n-1

6

Komatsu China monthly avg. utilization hours Growth yoy (RHS)Hours


Source: Komatsu, Deutsche Bank Strategy Research

13 July 2016



Machinery: Excavator sales growth spiked to 33% in Mar this year,

thanks mainly to front-loaded demand on the back of newly

implemented emission standards, before plunging back into negative

territory. However, excavator sales shot up strongly to 4.2k units in

Jun, or 11% growth (Figure 47), due to a substitution effect (from

wheel loader to excavator) and solid demand from

infrastructure/property investment and the rural market, as shown in

the robust 10% growth in Komatsu’s China excavator utilization hours

(Figure 48). See our machinery analyst’s note China excavator sales

surprisingly turn positive in June, 8 Jul.

Analysts were still cutting consensus earnings estimates on the headline MSCI

China level in recent weeks, while some cyclical sectors have received visible

upgrades, such as energy and materials (Figure 49). As Jun macro data

releases will be wrapped up by 15 Jul (IP, FAI, retail sales and GDP are due),

investors may start to focus on the upcoming interim results in Aug. We think

up-/mid-stream sectors are likely to deliver stronger-than-consensus growth

in 2Q16 and analysts may further raise their estimates in the coming weeks,

providing fundamental support to Chinese equities.

Indeed, select cyclicals have pre-announced positive news. For instance, China

Coal has indicated a preliminary 1H16 NPAT of Rmb350mn~520mn, citing

increasing coal prices, improving product structure, cost control and asset

disposal. See China Coal announces a profit alert, 11 Jul.

We expected 4% earnings growth for MSCI China from a top-down

perspective, well ahead of the -3.4% implied by current consensus.

Meanwhile, our 6% earnings growth projection for 2017 is lower than

consensus (Figure 50).

Figure 49: Energy and materials have received earnings

upgrades in the past month

Figure 50: We expect 4%/6% earnings growth for MSCI

China in 2016/17

Sector 1M 3M YTD Sector 1M 3M YTD

Energy 5.1% 3% -62% Energy 1.7% -4% -34%

Materials 2.6% 6% -13% Materials 0.5% 7% -24%

Cons. Stap. -0.3% -1% -9% Comm. Serv. 0.1% -1% -9%

Comm. Serv. -0.9% -2% -9% Cons. Stap. -1.1% -3% -15%

Div. Financials -1.1% -4% -9% Div. Financials -1.3% 3% -4%

Health Care -1.6% -3% -2% Capital Goods -1.4% -2% -6%

Real Estate -1.7% -3% -10% Health Care -1.4% -3% -4%

Telecom -1.7% -6% -13% Real Estate -1.5% -2% -8%

Cons. Disc. -1.9% -4% -14% Utilities -1.6% -5% -12%

MSCI China -2.1% -4% -12% Info. Tech. -1.6% -6% -8%

Banks -2.2% -3% -7% Telecom -1.7% -5% -12%

Utilities -2.3% -5% -9% MSCI China -2.0% -4% -12%

Capital Goods -2.4% -3% -8% Insurance -2.5% -6% -18%

Info. Tech. -3.0% -5% -7% Banks -2.6% -5% -11%

Insurance -3.4% -6% -19% Cons. Disc. -3.4% -6% -14%

Transportation -4.0% -14% -29% Transportation -4.1% -12% -17%

2016E 2017E

MSCI China consensus EPS revision

DB

forecast

Consensus

forecast

Implied

revisions

2016E Non-financials 8.4% 2.2% 6.0%

Financials 0.0% -8.1% 8.8%

MSCI China 3.7% -3.4% 7.3%

2017E Non-financials 8.9% 24.1% -12.3%

Financials 3.0% 5.5% -2.3%

MSCI China 5.7% 14.5% -7.7%

DB top-down earnings

forecast vs. consensus



13 July 2016



Why CPI may stay weak and how that may weigh on domestic market rates

Although recent floods in southern China may raise food prices in the near

term, we believe China’s CPI is likely to stay weak in the coming months,

considering 1) sluggish consumption demand due to the lagged effect of the

earlier industrial slowdown weighing on current employment and household

income; 2) increasing food price pressure, which could drag down overall

consumer prices, and 3) an increasingly tough yoy comparison base.

Global uncertainties have clearly intensified in the past few weeks, especially

post-Brexit. Accordingly, major central banks have been readying additional

easing in the form of more rate cuts/QE or delaying rate hikes. The resulting

unprecedentedly low interest rates across DM fixed income markets, including

over US$12trn of negative yields in sovereign debt, have widened the EM vs.

DM yield spread and may lure yield-hungry institutions back to EMs,

including China. See Brexit’s loss could be EM’s gain, 1 Jul, from our chief

Asia economist.

Thanks to the PBoC’s continued supportive monetary stance, China’s domestic

market rates are hovering at low levels and credit spreads have tightened

again after a transient widening back in May. If CPI weakens further (as we

expect) and DM authorities introduce more monetary loosening, onshore

market rates may remain subdued in the coming months, boding well for

economic fundamentals, commodity prices and equity valuations.

China’s CPI is likely to stay weak in the coming months

Figure 51: Employment conditions have deteriorated

consistently in the past few years

Figure 52: Household disposable income growth has

been lagging nominal GDP growth by six months

44

46

48

50

52

54

56

58

Jan

-07

May-0

7

Sep

-07

Jan

-08

May-0

8

Sep

-08

Jan

-09

May-0

9

Sep

-09

Jan

-10

May-1

0

Sep

-10

Jan

-11

May-1

1

Sep

-11

Jan

-12

May-1

2

Sep

-12

Jan

-13

May-1

3

Sep

-13

Jan

-14

May-1

4

Sep

-14

Jan

-15

May-1

5

Sep

-15

Jan

-16

May-1

6

China NBS PMIEmployment index

Non-manufacturing Manufacturing

Employment conditions trended lower since 2010

6M09

6.5%

3M16

7.2%2009

8.8%

3M16

8.0%

3M14

9.8%

4

8

12

16

20

24

0

5

10

15

20

25

30

6M

03

2003

6M

04

2004

6M

05

2005

6M

06

2006

6M

07

2007

6M

08

2008

6M

09

2009

6M

10

2010

6M

11

2011

6M

12

2012

6M

13

2013

6M

14

2014

6M

15

2015

ytd yoy %ytd yoy % China nominal GDP

Household disposable income (nominal, lag 6m; RHS)

Household income

lags N.GDP by 6m

N.GDP vs. HH income (lag 6m)

Correlation = 72%



1) Sluggish consumption demand.

There is little doubt that the continuous industrial and therefore

economic slowdown since 2011 has weighed on overall employment

conditions, as indicated by the downward trending employment sub-

index in both the manufacturing and non-manufacturing NBS PMI

(Figure 51); in particular, the manufacturing employment sub-index

has been contracting (below 50) since May 2012.

13 July 2016



Accordingly, we find China’s household disposable income growth

has been lagging nominal GDP by six months (Figure 52); most

recently, household income growth slowed further to 8% in 1Q16, the

lowest level in the past decade. This contributed to the sluggish

consumption demand, especially in low-end categories such as food.

If nominal GDP accelerates further this year as we expect, we believe

household income and overall consumption demand could also

strengthen later as the lagged effect kicks in. For the next few months,

however, we see only sluggish consumption demand as household

income softens.

2) Increasing food (especially hog/pork) supply.

After a transient price surge at the Chinese New Year in February, food

prices (especially pork and vegetables) have notably subsided: pork

prices dropped to 30% yoy in June after peaking at 34% in May, while

vegetable prices have dropped into negative territory at -6.5% yoy

after peaking at 36% in March (Figure 53).

The price outlook for pork and vegetables is important for the CPI

trend down the road, as food has typically explained c.60% of the

CPI’s yoy growth since 2008 because of its volatility (Figure 54).

Figure 53: Headline CPI dipped in Jun alongside

softening food prices; core CPI stable

Figure 54: Food prices have higher volatility and explain

the majority of the change in headline CPI

1.9

1.6

30.1

-6.5

40

20

0

20

40

60

80

0

2

4

6

8

Jan

-10

Ap

r-10

Ju

l-10

Oct-

10

Jan

-11

Ap

r-11

Ju

l-11

Oct-

11

Jan

-12

Ap

r-12

Ju

l-12

Oct-

12

Jan

-13

Ap

r-13

Ju

l-13

Oct-

13

Jan

-14

Ap

r-14

Ju

l-14

Oct-

14

Jan

-15

Ap

r-15

Ju

l-15

Oct-

15

Jan

-16

Ap

r-16

Ju

l-16

yoy %yoy % China CPI Core CPI Pork (RHS) Vegetable (RHS)

Headline CPI has been well anchored by core CPI since 2012, despite food price volatility

Core CPI

stays stable

50%

55%

60%

65%

70%

-2

0

2

4

6

8

10

Jan

-08

May-0

8

Sep

-08

Jan

-09

May-0

9

Sep

-09

Jan

-10

May-1

0

Sep

-10

Jan

-11

May-1

1

Sep

-11

Jan

-12

May-1

2

Sep

-12

Jan

-13

May-1

3

Sep

-13

Jan

-14

May-1

4

Sep

-14

Jan

-15

May-1

5

Sep

-15

Jan

-16

May-1

6

ppt Food's contribution to CPI yoy growth Non-food

Food's contribution to change in CPI (avg. since 2008) = 59%



Recent floods in southern and eastern China may cause temporary

supply shocks in certain areas and push up local food prices, but we

believe the impact on nation-wide food prices should be limited, as the

government is closely monitoring food prices in the affected areas and

is ready to deliver reserves if needed.

Looking ahead, we think food prices may continue to weigh on

headline CPI, considering the following:

Vegetables generally grow fast and do not have a long-lasting

effect on food prices. We think vegetable supply may increase as

the weather cools off and rainfall eases.

We notice a tight correlation with a 6-month lag between the hog-

raising profit margin (using the hog-to-grain ratio as a proxy) and

live hog inventory (Figure 55). The ratio troughed in 2Q15 and

since then has shot up significantly over 10x. After six months,

13 July 2016



hog farmers started to respond to the richer profitability by

increasing inventory. We see more inventory buildup in the

coming months, which may weigh on hog/pork prices. Indeed,

hog/pork prices have already turned south in Jun (Figure 56), and

the downtrend may well extend.

Figure 55: Live hog inventory is likely to build up further

alongside a rising hog-raising profit margin

Figure 56: Most recently, hog and pork prices have

moderated notably

-16%

-12%

-8%

-4%

0%

4%

8%

12%

4

5

6

7

8

9

10

11

12

13

Jan

-10

Ap

r-10

Ju

l-10

Oct-

10

Jan

-11

Ap

r-11

Ju

l-11

Oct-

11

Jan

-12

Ap

r-12

Ju

l-12

Oct-

12

Jan

-13

Ap

r-13

Ju

l-13

Oct-

13

Jan

-14

Ap

r-14

Ju

l-14

Oct-

14

Jan

-15

Ap

r-15

Ju

l-15

Oct-

15

Jan

-16

Ap

r-16

yoyX Hog price-to-grain ratio Live hog inventory (lag 6m; RHS)

Hog raising margin has shot up since 2H15; live hog stock

follows it closely with 6m lag

2%

Apr 16

46%

22%

30%

Mar 16

64%

16%

-40%

-20%

0%

20%

40%

60%

80%

Jan

-12

Mar-

12

May-1

2

Ju

l-12

Sep

-12

Nov-1

2

Jan

-13

Mar-

13

May-1

3

Ju

l-13

Sep

-13

Nov-1

3

Jan

-14

Mar-

14

May-1

4

Ju

l-14

Sep

-14

Nov-1

4

Jan

-15

Mar-

15

May-1

5

Ju

l-15

Sep

-15

Nov-1

5

Jan

-16

Mar-

16

May-1

6

22-city avg. price change yoy

Pork Live hog



Figure 57: CPI is likely to weaken in 3Q16 given an

escalating comparison base in 3Q15…

Figure 58: …as long as the sequential MoM read of CPI

comes in lower than the 0.1~0.5% seen in 3Q15

1.4

1.6

2.0

1.6

1.9

0.5

1.0

1.5

2.0

2.5

3.0


CPI YoY % 2015 2016

CPI spiked up in 3Q15, making a tougher yoy comparison base for 3Q16

0

0.3

0.5

0.1

-0.1

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0


CPI MoM % 2015 2016

CPI spiked up in 3Q15, making a tougher yoy comparison base for 3Q16



3) An increasingly tough yoy comparison base. CPI’s base will pick up as it

plotted a gradually rising trajectory during 2H15: CPI averaged 1.6% in 2H15

vs. 1.3% in 1H15. What’s more, the CPI base is quite high over the next three

months (July to October) as it registered 1.6%/2.0%/1.6% during the same

period last year, recording the first- and second-highest levels in 2015 (Figure

57). As long as CPI’s monthly sequential growth stays below last year’s levels

of 0.3%/0.5%/0.1% during 3Q15, its yoy growth should ease in 3Q16 (Figure

58).

The widening carry between EM vs. DM bodes well for lower EM rates ahead

Global uncertainty has visibly increased in the past few weeks with major

global events such as Brexit and the Italian banking problem. Accordingly,

more and more DMs are joining the club of negative interest rates (Figure 59).

13 July 2016



Currently over US$12trn worth of DM sovereign debt is trading at negative

yields, which widens the carry between EM and DM and may bring EM yields

to the attention of yield-hungry institutions such as pension funds and insurers.

See Brexit’s loss could be EM’s gain, 1 Jul, from our chief Asia economist.

More specifically on major DM central banks, we note:

1) In the UK, our UK economist expects the Bank of England to loosen

policy by lowering the Bank Rate from 0.50% to 0.25% at the August

meeting and thereafter continue to cut rates to the lowest level it is

willing to go and restart the QE program as of the September meeting.

See Thinking about contagion channels, 8 July.

2) On the ECB, our economist thinks a further deposit rate cut is

unlikely. More likely would be a decision to extend the timeframe for

QE and hold more TLTRO2 auctions to signal its commitment to policy

easing. If market pressures build, a front-loading of QE and/or

temporary deviation from the capital key is possible. The latter has a

non-negligible political cost, however. There may be less costly ways

of achieving a differentiated policy impact, e.g., our dedicated TLTRO2

suggestion. See What Brexit means for the euro area page 9, 24 Jun.

3) For the Fed, the fed funds futures-implied probability of another rate

hike this year dropped to near zero after the Brexit referendum (Figure

60). After the strong June employment report, however, the fed funds

futures-implied probability of a rate hike in September increased to

roughly 14%, from 2% previously. Our US economist’s base case

remains that the Fed will hike in December, though policymakers will

want to keep their options open for September. We will watch closely

the FOMC meeting due by 26~27 Jul. See A flurry of fedspeak this

week, 11 Jul.

Figure 59: More DM sovereign bond yields have dipped

into negative territory

Figure 60: Market expectations of Fed rate hike have

plunged significantly post-Brexit

YTM % 1Y 2Y 3Y 5Y 10Y 30Y

Switzerland (1.0) (1.0) (1.1) (1.0) (0.6) (0.1)

Germany (0.6) (0.7) (0.7) (0.6) (0.2) 0.4

Japan (0.4) (0.3) (0.3) (0.3) (0.3) 0.1

France (0.6) (0.6) (0.6) (0.4) 0.1 0.9

Italy (0.2) (0.1) 0.0 0.3 1.2 2.2

US 0.5 0.6 0.8 1.0 1.4 2.2

UK 0.2 0.2 0.2 0.4 0.8 1.6

Canada 0.5 0.5 0.5 0.5 1.0 1.6

Korea 1.3 1.2 1.2 1.2 1.4 1.5

China 2.4 2.5 2.5 2.8 2.9 N/A

India 6.8 7.0 7.0 7.2 7.4 7.9

Russia 9.5 9.4 9.2 8.7 8.4 N/A

Brazil 13.6 12.6 12.2 12.0 12.0 N/A

Government bond yield

EM

DM

July, 4%

Sept, 14%Nov, 13%

Dec, 29%

Feb-17, 29%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16

Fed fund ratefutures' impliedrate hike probability

July Sept Nov Dec Feb-17

Source: Bloomberg Finance LP, Deutsche Bank Strategy Research, as of 11 July


Domestic market rates may remain subdued

Thanks to the PBoC’s accommodative policy stance, China’s domestic market-

based interest rates are hovering at low levels (Figure 61) and credit spreads

remain tight (Figure 62). If CPI stays weak as we expect and DM central banks

roll out additional monetary loosening, the PBoC may be equipped with

13 July 2016



incremental policy room to keep or even add monetary accommodation

(when needed). For instance, real interest rates may creep up as CPI softens in

the coming months (Figure 63), and the PBoC may want to avoid too much

real interest rate pickup, given the lingering structural downward pressure in

the economy.

Our economist believes RRR and/or rate cuts are not likely in July but does

expect the policy stance to be loosened in 2H16, most likely in 4Q16 (see

China: Further policy easing unlikely in July, 11 Jul). Meanwhile, we will watch

closely the PBoC’s open market operations, especially how (at what size and

price) the authority rolls over the Rmb529bn MLF (medium-term liquidity

facility; Figure 64) expiry in July, which should provide more hints about its

policy intention.

Bearing all this in mind, we think domestic market rates may remain subdued

in the coming months, boding well for economic fundamentals, commodity

prices and equity valuations.

Figure 61: Domestic market rates remain at low levels as

PBoC maintains an accommodative policy stance

Figure 62: Credit spreads have tightened significantly in

the past few years, currently close to historical lows

2.8%2.5%

4.0%

3.2%

1%

2%

3%

4%

5%

6%

7%

8%

Ju

l-14

Au

g-1

4

Sep

-14

Oct-

14

Nov-1

4

Dec-1

4

Jan

-15

Feb

-15

Mar-

15

Ap

r-15

May-1

5

Ju

n-1

5

Ju

l-15

Au

g-1

5

Sep

-15

Oct-

15

Nov-1

5

Dec-1

5

Jan

-16

Feb

-16

Mar-

16

Ap

r-16

May-1

6

Ju

n-1

6

Ju

l-16

Au

g-1

6

10y China gov't bond 7d repo (20D MA)

3m wealth mgmt product 6m bill discount rate

Market rates stay low, suggesting accommodative financial conditions

54

100

59

71

228

104

148

103

30

70

110

150

190

230

270

310Jan

-14

Mar-

14

May-1

4

Ju

l-14

Sep

-14

Nov-1

4

Jan

-15

Mar-

15

May-1

5

Ju

l-15

Sep

-15

Nov-1

5

Jan

-16

Mar-

16

May-1

6

Ju

l-16

AAA AAA- AA+

Credit spreads stay very tight

5-yr YTM spread: corp. bond minus CGB



Figure 63: Real interest rates creep up as CPI softens;

PBoC may want to avoid too much real rates increase

Figure 64: Rmb529bn of MLF will expire in July; PBoC is

likely to roll it over to maintain loose monetary conditions

-4.6

4.1

-3.1

-0.4

-1.2

7.1

0.0

2.5

-6

-4

-2

0

2

4

6

8

10

Jan

-08

May-0

8

Sep

-08

Jan

-09

May-0

9

Sep

-09

Jan

-10

May-1

0

Sep

-10

Jan

-11

May-1

1

Sep

-11

Jan

-12

May-1

2

Sep

-12

Jan

-13

May-1

3

Sep

-13

Jan

-14

May-1

4

Sep

-14

Jan

-15

May-1

5

Sep

-15

Jan

-16

May-1

6

1-yr benchmark rates minus CPI yoy, %

Real deposit rate Real lending rate

250

110

-

551

148

100

529

237

123

404

115

12 0

100

200

300

400

500

600

700

800

Jan

-16

Feb

-16

Mar-

16

Ap

r-16

May-1

6

Ju

n-1

6

Ju

l-16

Au

g-1

6

Sep

-16

Oct-

16

Nov-1

6

Dec-1

6RMB bn PBOC MLF expiry schedule



13 July 2016



Appendix 1

Important Disclosures

Additional information available upon request

*Prices are current as of the end of the previous trading session unless otherwise indicated and are sourced from local exchanges via Reuters, Bloomberg and other vendors . Other information is sourced from Deutsche Bank, subject companies, and other sources. For disclosures pertaining to recommendations or estimates made on securities other than the primary subject of this research, please see the most recently published company report or visit our global disclosure look-up page on our website at http://gm.db.com/ger/disclosure/DisclosureDirectory.eqsr

Analyst Certification

The views expressed in this report accurately reflect the personal views of the undersigned lead analyst(s). In addition, the undersigned lead analyst(s) has not and will not receive any compensation for providing a specific recommendation or view in this report. Yuliang Chang/Joseph Huo

Equity rating key Equity rating dispersion and banking relationships

Buy: Based on a current 12- month view of total share-holder return (TSR = percentage change in share price from current price to projected target price plus pro-jected dividend yield ) , we recommend that investors buy the stock.

Sell: Based on a current 12-month view of total share-holder return, we recommend that investors sell the stock

Hold: We take a neutral view on the stock 12-months out and, based on this time horizon, do not recommend either a Buy or Sell.

Newly issued research recommendations and target prices supersede previously published research.

53 %

36 %

11 %15 % 15 % 20 %

050

100150200250300350400450500

Buy Hold Sell

Asia-Pacific Universe

Companies Covered Cos. w/ Banking Relationship

Regulatory Disclosures

1.Important Additional Conflict Disclosures

Aside from within this report, important conflict disclosures can also be found at https://gm.db.com/equities under the

"Disclosures Lookup" and "Legal" tabs. Investors are strongly encouraged to review this information before investing.

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Deutsche Bank equity research analysts sometimes have shorter-term trade ideas (known as SOLAR ideas) that are

consistent or inconsistent with Deutsche Bank's existing longer term ratings. These trade ideas can be found at the

SOLAR link at http://gm.db.com.

13 July 2016



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Documents

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