中国各个城市债务健康检查（中国房地产行业报告）

1、EQUITIESREAL ESTATEJanuary 2019Michelle HYPERLINK / China Real EstateA city-by-city debt health checkis is a Play interview with Michelle KwokDisclaimer & Disclosures: This report must be read with the disclosures and the analystcertifications in the Disclosure appendix, and with the Disclaimer, whi

2、ch forms part of itWhy read this report?After two years of rapid price increases, we examine the risk profile of the residential real estate market at the city level. The focus is on leverage excessive increases in debt reflect a greater risk of a sharp fall in house pricesOur analysis covers 63 cit

3、ies in China for which household debt data is available. We identify 16 that we think have the highest risk profiles in a slowing property market and deleveraging environmentWe highlight the developers whose land banks have the highest exposure to these 16 cities, namely, Logan (25.6%), SZ Investmen

4、t (20.3%) and Country Garden (16.5%)1China Real Estate: A city-by-city debt health checkRisk factorsOur city-by-city check isbasedon the following factors:(Red shading denotes the in thecities;shadingtheinourThe 16 cities with thehighest risk profilesCities with high loan-to-deposit risk profiles in

5、 a property and Land bank exposureKey Chinese developers gross floor area(GFA) exposure in these 16 cities:63-city sample)Household loan-to-deposit ratio(absolute basis, 2017)69%Change in household loan-to-deposit-ratioenvironment SZ Household loan-to-depositHousehold loan-to-depositratio(absolute b

6、asis, 2017)Harbin56%67%Beijing49%DalianZhengzhou HuaianYangzhou97%188% 79%133% 105% 59%ZhenjiangShanghaiHefei67%SuzhouHuzhou86%WenzhouZhuhaiXiamen104%139%43%HuizhouJiangmen49%SanyaCR GZ25.6%20.3%16.5%16.5%16.2%15.6%14.8%13.8%13.2%City-levelrealestateinvestmentasapercentage of GDP (2017)China JinmaoC

7、hina SCEKWG10.3%9.5%7.6%Grey barsCity-level government debt as apercentage of GDP (2017)Area in detailSino 6.9%1.5% represent companies notcovered byHSBCEquityResearchKey facts in Chinas debt-funded housing boomChina household loan-to-deposit ratio has increased from 37% in January 2012 to 63% in 1H

8、18The percentage growth inoutstanding mortgages since 2007; in September 2018thetotalhadreachedRMB24.9trnTotal borrowing for real estate development on a national level increased from RMB1.8trn in 2007 to RMB10.1trn in September 2018 Source: CRIC, PBOC, Company data, HSBC estimates 2Figure 1: Cumula

9、tive average selling price (ASP) performance of cities in China (9M18)HarbinChangchunUrumqiBaotouOrdosHohhotBeijing LangfangBaodingAnshan QinhuangdaoTangshan TianjinShenyangYingkou DalianJilinYinchuanShijiazhuangTaiyuanHengshui DongyingDezhouYantaiWeihaiXiningHandan ZiboLiaocheng JinanWeifangQingdao

10、LanzhouXianXinxiangRizhaoHezeXuzhouLianyungangSuqianLuoyang Zhengzhou SuqianBaojiHefei MaanshanHuaianJiangsu ShanghaiHuaianYangzhouTaizhouMianyangYichangWuhanWuhuJiaxing HuzhouNanjingZhenjiangNantongChengduChongqingChangsha XiangtanHangzhouShaoxingNanchangJinhuaNingboTaizhouChangzhou WuxiSuzhouLegen

11、d 9M18 ASP change Numberof cities%GuiyangZhuzhouGanzhouFuzhou QuanzhouWenzhou5-10%3638%0-5%3335%10%5-10%3638%0-5%3335%KunmingLiuzhouGuilin GuangzhouXiamenShantou-5-0%4 -5%0NanningBeihaiFoshan ZhongshanJiangmenDongguanShenzhen ZhuhaiTotal95ZhanjiangHaikouNote: The maps shows the 95 cities where we tr

12、ack home price data Source: CREIS, HSBCSanyaEQUITIES EQUITIES REAL ESTATEJanuary 20193EQUITIES REAL ESTATEJanuary 2019450% or above17EQUITIES REAL ESTATEJanuary 2019450% or above1718%25-50%2425%HarbinChangchunJilinUrumqiShenyangAnshanHarbinChangchunJilinUrumqiShenyangAnshanYingkouBaotouHohhotOrdosBe

13、ijingLangfang BaodingQinhuangdaoTangshanDalianShijiazhuang Hengshui Dongying YantaiTianjinYinchuanWeihaiTaiyuanHandanDezhouXiningXinxiang Liaocheng JinanZiboLanzhouHezeWeifangQingdaoRizhao LianyungangXuzhouXuzhouLianyungangXianLuoyang Zhengzhou SuqianBaojiHuaianSuqianHuaianMianyangYichangWuhanHefeiM

14、aanshan WuhuHangzhouJiangsu ProvinceShanghaiYangzhouJiaxingHuzhouChengduNingboChongqingChangshaXiangtanNanchangShaoxingJinhuaTaizhouNanjing Zhenjiang Nantong Changzhou SuzhouWuxiTaizhouWenzhouZhuzhouFuzhouLegend 2012-17 ASP change Number of cities%GuiyangGanzhou QuanzhouXiamenKunmingLiuzhouGuilin Gu

15、angzhou FoshanHuizhouDongguan ShantouShenzhen Zhuhai0-25%4446%NanningZhongshan-10-0%77%BeihaiJiangmenless than -10%33%Total95100%ZhanjiangHaikouSanyaNote: The maps shows the 95 cities where we track home price data Source: CREIS, HSBCContents HYPERLINK l _bookmark0 Why readthisreport?1 HYPERLINK l _

16、bookmark1 Time for adebtcheck6 HYPERLINK l _bookmark2 The rising tideofdebt6 HYPERLINK l _bookmark3 Key facts and stats about Chinas HYPERLINK l _bookmark3 debt-fundedhousingboom HYPERLINK l _bookmark4 Screening for cities with high HYPERLINK l _bookmark4 riskprofiles8 HYPERLINK l _bookmark5 Our 201

17、9 China real estate HYPERLINK l _bookmark5 sector outlook12 HYPERLINK l _bookmark7 Keyvaluationcharts16 HYPERLINK l _bookmark9 Thebigpicture17 HYPERLINK l _bookmark10 Risingdebtlevels18 HYPERLINK l _bookmark13 The impactofdeleveraging22 HYPERLINK l _bookmark15 Citycheck-up27 HYPERLINK l _bookmark16

18、Measuringvulnerability28 HYPERLINK l _bookmark25 Citiestowatch48 HYPERLINK l _bookmark30 Companyvaluations55 HYPERLINK l _bookmark31 Appendix76 HYPERLINK l _bookmark33 Disclosureappendix93 HYPERLINK l _bookmark34 Disclaimer965Time for a debt checkWe have written a series of reports in the past two y

19、ears identifying investment opportunities in Chinas sprawling property market. As the real estate market starts to cool, we shift the focus to assessing which cities face the highest risk in the event of a correction in house prices. As the government tries to put a cap on leverage, we look at the l

20、evel of household debt and how dependent city economies are on the property sector for raising revenue. We identify the 16 cities we think are most vulnerable to a slowdown in the housing market and also highlight the developers whose land banks have the highest level of exposure to these cities.Fro

21、m finding the hot cities to a risk assessmentOver the past two years we have published three thematic reports identifying what we believe have been the 25 cities in China with the most investible residential real estate markets during a period of rapid growth in property prices. Times have changed,

22、and the real estate boom now appears to be over. The government, concerned about debt levels at the local government, corporate, and household level, is making efforts to take the heat out of the property market.These measures seem to be working, as sales volumes and house prices are starting to coo

23、l. In this report, we turn our attention to assessing the potential risks associated with a real estate slowdown, focusing on the following: The level of household debt in 63 cities; The scale of local government leverage at the city level; The 16 cities we think are most vulnerable to a slowdown in

24、 the property market; The developers whose land banks have the most exposure to these cities; and A scenario analysis on different mortgage scenariosThe rising tide of debtWe the in is to that have prevailed since 2016. Home buyers have had easy access to cheap mortgages and developers were able to

25、tap the onshore and offshore bond markets at historically low interest rates. The accommodative credit environment led to asset price inflation across all levels of the residential property market, from giant tier-1cities like Beijing and Shanghai to much smaller lower tier cities in less prosperous

26、 provinces. In extreme cases, prices in some cities have risen by more than 70% in the last three years. Times have changed, and concerns about the rising tide of debt have resulted in policymakers trying to place a cap on leverage.6Scenario analysisDeleveraging in the form of more restricted mortga

27、ge lending to home buyers will have an impact on the market. This report quantifies the potential impact on housing market based on three different mortgage scenarios.In the base case we assume the annual new mortgage-to-property sales ratio remains unchanged, at c35%, with 2019e residential housing

28、 sales of 1,231m sqm, which implies a 10% decline in national sales volume in 2019e. We calculate that annual new mortgages totalling RMB3,530bn will flow into the residential property market. This implies a loan-to-deposit ratio of 52.1% in 2019, slightly higher than 49.2% in 2018e.In the bear case

29、, we demonstrate the effect of extreme tightness in mortgage conditions similar to 2012. Our calculation shows a decline in the loan-to-deposit ratio, to 48.6%, which signifies effortsatdeleveraging.Theoutcomeimpliesafurther20%downsidetonationalresidentialsales GFA from our base case of 1,231m sqm t

30、o our bear case of 985m sqm, implying a 28% y-o-y decline in national sales volume in2019e.In the bull case mortgage lending remains accommodative and the loan-to-deposit ratio grows to 54.7%, we project a 15% upside to national property sales to our base case scenario.Please see pages 22-25 and HYP

31、ERLINK l _bookmark14 Figure 25 for more details.Key facts and stats about Chinas debt-funded housing boomMortgages and leverage Outstanding mortgages have grown by 823% since 2007 to RMB24.9trn (USD3.61trn) in September 2018, according to data released by the Peoples Bank of China (PBOC). Outstandin

32、g mortgage loans as a percentage of GDP stood at 26% in 2017, up from 10% in 2007. Outstanding mortgages in China exceeded the GDP of both the UK (USD2.62trn) and France (USD2.58trn) in 2017, which are the second and third largest economies in Europe. China household leverage is increasing rapidly t

33、he household loan-to-deposit ratio has risen from 37% in January 2012 to 63% in 1H18. Over RMB300bn of short-term consumption loans were channelled into the property market between March and August 2017, according to industry estimates. Real estate developers have relied heavily on debt to fund grow

34、th. Total borrowing for real estate development increased from RMB1.8trn in 2007 to RMB6.6trn in 2015 and RMB10.1trn in September 2018, cumulative growth of 459%.Home price growth Shenzhen (131%) and Xiamen (113%) recorded the highest rate of price increases between 2011 and October 2018. These two

35、cities also had close to the highest household loan-to-deposit ratios in 1H18 157% and 178%respectively. 14 cities in China recorded increases in home prices of more than 80% between 2011 and October 2018. Of the 99 cities we track only three registered a decline in home prices during this period Sa

36、nya (-10%), Jilin (-5%) and Yingkou (-1%).7Screening for cities with high risk profilesThree steps: risk, macroeconomics and housing supplyA three-pronged approachFirst, we calculate a risk index for each city to gauge their respective risk profiles. The index is a weighted average value calculated

37、based on four factors: (1) 2017 household loan-to-deposit ratio (35% weighting), (2) change in household loan-to-deposit ratio during 2015-17 (35% weighting), (3) city-level real estate investment as a percentage of GDP (15% weighting), and(4) city-level government debt as a percentage of GDP (15% w

38、eighting). Cities that have leveraged up aggressively are seen to be more vulnerable to potential shocks from a deflating housing market.Second, we compare our assessment of city-level risk to macro indicators such as strong economic growth and population inflows in order to understand the potential

39、 offsetting factors that help reduce a citys risk profile. The logic here is that macro strength increases the ability to service higher levels of debt which, in turn, means more manageable risk levels. This analysis is based on our macro growth index.Third, we take city-level property supply (using

40、 inventory levels and inventory months) into consideration as cities with tight supply are likely to be better shielded from a housing market correction. This process eliminates 11 cities from our preliminary list of cities with potentially higher risk profiles.Based on this three-pronged screening

41、methodology, we identify 16 cities Zhuhai, Xiamen, Huaian, Sanya, Huizhou, Hefei, Zhengzhou, Suzhou, Zhenjiang, Huzhou, Yangzhou, Baotou, Wenzhou, Harbin, Jiangmen and Dalian as cities with potentially higher risk profiles.Figure 3: HSBCs list of 16 cities with potentially higher risk profiles Loan-

42、to-depositratio REI/GDPGovdebt/GDP ASPchange Cities2017Change in 2015-2017 (ppt)201720172016-1H189M18Zhuhai139%6125%64%53.9%-0.4%Xiamen181%4820%44%32.8%1.1%Huaian188%309%74%19.6%3.3%Sanya49%26104%34%25.0%5.8%Huizhou104%4423%19%41.7%-0.6%Hefei133%3722%25%46.8%10.0%Zhengzhou97%3537%38%22.7%3.3%Suzhou1

43、05%3213%19%22.3%1.1%Zhenjiang59%338%76%32.7%9.8%Huzhou67%1412%104%20.8%3.7%Yangzhou79%169%38%36.2%9.4%Baotou67%174%30%8.5%5.4%Wenzhou86%519%32%20.6%3.3%Harbin56%118%36%27.4%7.8%Jiangmen43%1317%21%28.7%3.3%Dalian49%68%45%19.3%7.1%Average94%2721%44%28.7%4.7%Sample average69%1516%38%29.2%6.1%Note: Base

44、d on the 63 cities in our sample. Ranked by our own risk index with the highest on the top Source: CEIC, CREIS, local governments websites, PBOC, HSBC estimates8Figure 4: The 16 cities, by geography: the highest presence is in south and the east of the countryHarbinBaotouDalianZhengzhouJiangsu Huaia

45、nYangzhouHefeiHuzhouZhenjiangSuzhouWenzhouHSBCscitieswiththehighestriskprofiles HSBCs House ofTechHSBCs phoenixcitiesJiangmenHuizhou ZhuhaiXiamenSanyaSource: HSBC9Figure 5: The 16 cities change in home prices (9M18)ZhuhaiXiamenZhuhaiXiamenHuaianHuizhouSanyaZhengzhouSuzhouZhenjiangHefeiHarbinWenzhouH

46、uzhouYangzhouBaotouDalianAverage 9M18 ASP changeJiangmen3.002.502.00Risk Index1.50Risk Index1.000.500.000.000.501.001.502.002.50Macro Growth IndexNote: Based on the 63 cities in our sample. Zhuhai and Huizhou recorded -0.4% and -0.6% ASP growth in 9M18, respectively Source: CEIC, CREIS, local govern

47、ment websites, PBOC, HSBC estimatesChinese developers exposureFor key Chinese developers we track, their gross floor area (GFA) exposure to the 16 cities that we think are most vulnerable to a slowdown in the housing market ranges from 1% to 26%, according to our estimates. Among our covered univers

48、e, those with the highest exposure are Logan (25.6%), Shenzhen Investment (20.3%) and Country Garden (16.5%). Of these companies, Logan is the only stock that has a Buy rating, while SZ Investment is rated Hold and Country Garden Reduce. At the other end of the spectrum among the stocks we cover, fi

49、ve out of the six companies which have the lowest land bank exposure to the vulnerable cities are rated Buy; the exception isKWG.Note that in this report we do not change any estimates, ratings or target prices for the companies under our coverage.10Figure 6: Chinese developers land bank exposure to

50、 the 16 cities25.6%20.3%16.2%25.6%20.3%16.2%15.6%14.8%13.8%13.2%11.6%11.1%10.3%9.5%7.6%7.0%6.9%1.5%CGAgile CR Shimao YanlordCIFI GZVanke COLIChina ChinaKWGEvergrandeLongfor Sino0%5%10%15%20%25%30%grey in of on How this fits into the bigger pictureIn the last two years we have devoted a good deal of

51、time to identifying hot cities in China. These arent the high-profile urban giants with mature property markets, but rather the smaller cities (a relative term in China) that we feel are the most investible in the long run. The analysis is based on our view that a citys ability to attract smart, wel

52、l-paid people to new economy industries is the most genuine and sustainable source of housing demand.Our three previous thematic reports HYPERLINK /R/10/zZPJHws Catching Phoenixes (5 June 2017), HYPERLINK /R/10/DsVbJj9 House of Tech(22 January 2018) and HYPERLINK /R/10/TswRBmP Joining the dots, find

53、ing the new property hot spots (23 May 2018) identified what we considered to be the 25 most investible tier two and three cities, and 16 new areas. As a reminder, we define phoenix cities as those driven by strong migration-driven housing demand, HYPERLINK /R/10/DsVbJj9 House of Tech refers to thos

54、e well positioned to attract tech talent, and HYPERLINK /R/10/TswRBmP Joining the dots looks at new districts being developed by the government.These reports helped us map the 25 most investible cities in China. We find that some of these cities overlap with the 16 we identify in this report. As a r

55、esult, we are fine-tuning the number of most investible cities from 25 to 21. While our thesis for the investible cities remains unchanged, it appears that easy lending conditions have distorted the dynamics of the housing market and attracted an undesirable level of speculative investment. Having c

56、onsidered the risk profiles of the cities that have already benefited from rapid increases in home prices, we remove four cities Zhuhai, Xiamen, Huizhou, and Zhenjiang from the list of investible cities.11Our 2019 China real estate sector outlookDivergent share price performance of Chinese developer

57、s in 2018Despite the risk of a near- term value trap, selected stocks look attractive on a 12-month horizonIn 4Q18 real estate sales have clearly slowed and home price growth has also moderated. Despite this, key indicators still reflect respectable y-o-y growth momentum. This means that the residen

58、tial market is far from entering a severe downturn even though there is still an element of uncertainty with respect to how 2019 will play out.The share prices of companies in this sector have suffered since mid-June 2018, but, as shown in HYPERLINK l _bookmark8 Figure 12, on a full-year 2018 basis

59、there has been a great disparity in performance, ranging from +31% to 39%. Although there have been signs of a recovery in 4Q18, we argue that is likely to be short lived. In our view, given concerns about economic growth, investors might have become prematurely optimistic about the prospects of bro

60、ad-based policy relaxation, which they think would boost share prices. We highlight that there is no precedent that housing policy relaxation is positive for property stocks. Hence, we maintain our cautious stance on the sector and believe trading will be range bound in the absence of a catalyst. Re