汇丰银行-中国房地产行业报告-那些掠夺性城市-20170811-56页-hsbc-chinarealestateth’raven’cities

,EQUITIESCHINAAugust 2017By: Michelle KwokChina Real EstateThe raven citiesMigration-driven demand is thedriver of new home price growth,particularly in regions outside ofthe big metropolisesbut not all cities are equal; weapply our proprietary analysisto identify those with theweakest outlookWe call those cities ravens; thecompanies we cover have onlyminimal exposure to them,,Disclaimer & Disclosures: This report must be read with the disclosures and the analystcertifications in the Disclosure appendix, and with the Disclaimer, which forms part of it,1,EQUITIES CHINA,August 2017,Figure 1: Cumulative ASP performance of cities in China, 2012-2016Note: Showing 95 cities in which we track property sales data.Source: CREIS, HSBC,2,EQUITIES CHINA,Figure 2: Recap of our 20 phoenix cities (see our report Catching phoenixes, dated 5 June 2017)Note: “JS” stands for the Jiangsu province to avoid confusion with another Suzhou city in Anhui (AH).Source: CREIS, HSBC,August2017,EQUITIES CHINAAugust 2017,ContentsExecutive summaryChinas twenty least attractivecitiesRaven cities vs ghost citiesRevisiting migration-drivenhousing demandReality check on supplyValuation perspectiveAppendixDisclosure appendixDisclaimer,4912142426374952,3,EQUITIES CHINAAugust 2017,Executive summary We revisit our propriety analysis of the migration-driven home pricegrowth prospects of Chinas cities Having identified those cities that are the most likely to benefit frommigration, we now point to those most likely to underperform Our coverage universe has minimal land bank exposure to those cities, Vote in Asiamoney Brokers Poll 2017Voting starts 6th JulyIf you value our service and insight, vote for HSBCClick here to votePhoenix cities are aboutpromised prosperity; ravenones are about bad omens4,The 20 cities in China with the weakest migration driversIn June we published a report (China Real Estate: Catching phoenixes, 5 June 2017) featuringthe 20 cities in China that we believe are set to lead a new phase of home price growth in Chinaas migration-driven demand spills over from the countrys big metropolises. In this report, we goto the opposite end of the city league and identify for investors those 20 cities that are likely tounderperform in terms of future home prices. These cities lack the characteristics of the top 20,which means job prospects at the bottom end are not strong and access to quality primaryschools is relatively limited. This in turn implies relatively weaker immigration opportunities andhence subdued future home price growth. We called the top 20 phoenix cities because inChinese mythology that bird symbolises prosperity and new beginnings. In this report weidentify the bottom 20 cities with the least home price growth prospects as ravens which is abird that is generally associated with impending bad news in folklore and mythology.,5,EQUITIES CHINA,Figure 3: The 20 raven cities in ChinaSource: CREIS, HSBC,August2017,EQUITIESCHINA,August 2017,Raven cities have littlebearing on the outlook forcompanies we cover,because the exposure tothem is limited,Our coverage universe has insignificant exposure to the raven citiesWe are not, of course, positing a simple causal connection between the performance outlook forcompanies that are exposed to phoenix cities and those that have some exposure to ravencities. There are plenty of company-specific issues that would need to be taken into account. Asit happens, stocks under our coverage universe have less than 11% of their land bank (in termsof gross floor area, or GFA) located in the raven cities, a relatively small portion. In fact, four namely China Jinmao, Longfor, Shui On Land and Yanlord have zero exposure. All but oneare Buy rated (we have a Hold rating on Shui On Land, due to its high leverage and risksassociated with execution outside Shanghai).Four stocks with no exposure to the raven cities (refer to page 26 for investment theses):1. Longfor (960 HK, Buy, HKD19.20, TP HKD20.30)2. China Jinmao (817 HK, Buy, HKD3.53, TP HKD4.00)3. Yanlord (YLLG SP, Buy, SGD1.79, TP HKD2.00)4. Shui On Land (272 HK, Hold, HKD1.87, TP HKD1.50)We have not made any changes to our earnings estimates, target prices and ratings in this report.Figure 4: Land bank exposure to raven citiesLongfor0.0%China Jinmao0.0%Yanlord0.0%Shui On0.0%Agile0.4%Shimao1.5%CG2.6%GZ R&F3.8%COLI4.7%Sino Ocean4.9%CRL8.9%KWG10.6%,0%,2%,4%,6%,8%,10%,12%,% of landbank located in raven cities,Source: Company data, HSBC,6,EQUITIESCHINA,August 2017,What are the implications for our coverage?Positive implications: COLI, Longfor and ShimaoBased on the theme of migration-driven housing demand, a simple approach to stock selectioncould be to own stocks with the most exposure to the phoenix cities and no exposure to theraven cities. However, the share prices of Chinese property developers are driven by amultitude of factors beyond geographic land bank exposure; other company-specific factors andvaluations must also be taken into consideration. In this respect, COLI, Longfor and Shimaoare the standouts within our coverage.COLI and Shimao are two of the three names within our coverage that have the most exposureto the phoenix cities, and both are trading at relatively attractive valuations as their share priceperformances have lagged YTD, which offers scope for catch-up. On the other hand, whileLongfor has relatively low exposure to the phoenix cities, we should point out that the phoenixesaccount for c30% of its overall land bank, which we consider a decent level of exposure. Inaddition, we like Longfor on the basis that it has achieved one of the strongest contracted salesgrowth rates YTD, along with one of the strongest balance sheets among the privately ownedenterprises (POEs).Yanlord appears to have the most optimal land bank mix, with the most exposure to the phoenixcities and no exposure to raven cities at all. The fact that its land bank is relatively concentratedin Nanjing and other cities that have already seen strong home price growth momentum implypotentially higher contracted sales risk in 2H17 amid more stringent policy implementation inthese cities.Figure 5: Land bank exposure to phoenix and raven cities for covered companiesGZ R&FCGAgileShui OnLongforChina JinmaoSino OceanCRLKWGShimaoCOLIYanlord,0%,10%,20%,30%,40%,50%,60%,70%,80%,90% 100%,Phoenix cities %,Raven cities %,Others %,Source: Company data, HSBCImplications for stocks with high exposure to raven citiesTwo stocks under our coverage, namely China Resources Land (CRL) and KWG, that have themost exposure to raven cities around 10% of their land bank are rated Buy due to company-specific reasons. We like CRL (1109 HK; HKD23.10) because it has among the highestrecurrent income in our coverage, which helps strengthen its balance sheet management, whileexposure to investment properties also helps enhance the competitiveness of its margin profile.7,EQUITIESCHINA,August 2017,KWG (1813 HK; HKD5.48), on the other hand, has consistently been able to generate a sector-leading residential margin profile, while remaining the highest yielding stock in our coverage.In any case, we consider around 10% land bank exposure to the raven cities reasonablyacceptable given that developers land reserve tenure ranges on average from 3 to 5 years. Inthis respect, we believe that a prudently managed project launch schedule could help minimisethe heavy concentration of sales in any particular city in any one year. This helps alleviate thepotential negative impact from having some land bank exposure to these less attractive cities,and limit the downside risks.Figure 6: Land bank exposures to phoenix and raven cities for non-covered companiesCOGOEvergrandePowerlongVankeYuexiuCIFIPoly Real EstateTimes PropertyYuzhouSunac,0%,10%,20%,30%,40%,50%,60%,70%,80%,90% 100%,Phoenix cities %,Raven cities %,Others %,Source: Company data, HSBC,Figure 7: Valuation summary,COLICRLCGChina JinmaoJoy CityKWGLongforShimaoShui OnSOHO ChinaYanlord (SGD)Average,Ticker688 HK1109 HK2007 HK817 HK207 HK1813 HK960 HK813 HK272 HK410 HKYLLG SP,RatingBuyBuyReduceBuyBuyBuyBuyBuyHoldHoldBuy,Price(HKD)25.8023.1010.063.531.175.4819.2014.161.874.131.79,TargetPrice(HKD)29.5028.004.704.001.306.3020.3018.501.503.502.00,Upside/(Downside)(%)1421(53)131115631(20)(15)12,MktCap(USDbn)36.220.5,3M ADTV(USDm)67.329.747.96.73.0,NAV(HKD/sh)32.835.021.033.830.97.511.83.6,(Disc)/Prem (%)(21)(34)62(60)(73)(74)(43)(54)(75)(65)(50)(46),FY16aPE (x)8.49.815.914.97.28.6,FY17ePE (x)7.88.012.77.96.011.4,FY18ePE (x)6.57.010.46.95.18.8,FY17eYield (%),FY16a PB(x),Average ex Joy City, Shui On Land and SOHOSource: Bloomberg, HSBCPriced at 10 August 20178,(39),10.0,7.7,6.5,5.0,1.2,EQUITIESCHINA,August 2017,We quantify citiesattractiveness based on threekey drivers of migrationand then take in a variety ofqualitative factors,Chinas twenty leastattractive cities We revisit our proprietary analysis measuring the attractiveness of 95Chinese cities in the context of population movement The analysis gauges a citys attractiveness based on three migrationdrivers: job opportunities, access to education and population density In this report, we focus on raven cities, the 20 cities that we judge ashaving the least attractive home price growth prospectsIn our last thematic report on migration-driven housing demand in China (China Real Estate:Catching phoenixes, 5 June 2017), we introduced a two-step approach to identifying the 20 phoenixcities that we judged as having the best long-term home price growth prospects based on theirattractiveness to internal migration flows. In this report, we use the same methodology to zoom in onthe 20 raven cities with the least attractive long-term home price growth prospects.To recap, the first step in our analysis is quantitative. We use a scorecard-based approach tomeasure the attractiveness of Chinese cities based on three factors that we believe are keydrivers of migration and/or have a high correlation with home prices: Job opportunities measured by the resident-to-hukou (registered right to residency) ratioin 2016 Access to education measured by 2012-2015 cumulative primary school student growth Population density measured by population per unit of administrative land area in 2016We assign a different weighting to each of these three metrics based on our view of their relativeimportance: 50% to job opportunities, 30% to access to education and 20% to populationdensity, respectively. We assign the highest weight to job opportunities as we believe this is thesingle most important driver behind migration. We apply this scorecard to 95 Chinese cities forwhich there is sufficient historical home price data to undertake this level of analysis (althoughsee our note below about lack of in-depth inventory data in smaller cities).In the second step, we focus on qualitative factors that could affect a citys real estate market.These include housing supply (measured by inventory level), a local governments hukou policyand the citys infrastructure or transportation system.As a reminder, our analysis excludes tier-1 cities. Additionally, although they scoreunfavourably, we have also excluded Chongqing and Baoding as raven cities owing to specialconsiderations. Chongqing is one of four strategically important municipalities (along withBeijing, Shanghai and Tianjin) that are directly controlled by the central government and it hasan inventory level of just two months as of May 2017. Baoding is excluded because XionganNew Area (a special economic development zone) is expected to drive investment in the city.9,EQUITIESCHINA,Huaian,Dezhou,Guilin,Beihai,August 2017,In Figure 10, we can see 16 of the 20 raven cities are tier-3 cities and all raven cities haverelatively low per capita income. Although raven cities have seen relatively mild home pricegrowth in the past, Nanning recorded a 13% increase in ASP in 2016, which is above the 95-cityaverage of 10.5%, as shown in Figure 9. Since raven cities generally have weakerfundamentals to support housing demand, cities with higher price increases in the past tend toharbour a higher risk of price correction if the macro environment deteriorates or policy tightens.In terms of supply, we acknowledge that most of the cities are small and lack comprehensiveinventory data, with inventory data only available for four cities out of the 20.Figure 8: 2016 ASP change vs. China property attractiveness score of 95 cities60%,Potential raven cities,Potential phoenix cities,50%,Higher policy risk,2016ASPchange,40%30%20%,95-city average,Lower policy risk,10%0%-10%,0.0,0.5,1.0,1.5,2.0,2.5,3.0,3.5,China property attractivenes scoreNote: China property attractiveness score is estimated based on the weighted score of the three quantitative factors.Source: CREIS, NBS, HSBC estimatesFigure 9: 2016 ASP change vs. China property attractiveness score of the 20 raven cities20%15%,2016ASPchange,10%5%0%,ZhanjiangGanzhouMianyangHarbinBaoji,NanningYichangMaanshanChangchunLiuzhouLuoyangSuqianYingkou,95-city averageMost raven cities have low policy risk,-5%-10%,Jilin,DongyingAnshan,Lower policy risk,0.40,0.45,0.50,0.55,0.60,0.65,0.70,0.75,0.80,0.85,0.90,China property attractiveness scoreNote: The 20 raven cities exclude Chongqing and Baoding. China property attractiveness score is estimated based on the weighted average score of the three quantitativefactors.Source: CREIS, NBS, HSBC estimates,10,11,EQUITIES CHINA,August 2017,Figure 10: Snapshot of phoenix cities, raven cities, and tier-1 cities,Rank1234567891011121314151617181920,CityDongguanXiamenZhongshanFoshanSuzhou (JS)TianjinWuxiZhuhaiZhengzhouNanjingJiaxingChangzhouChengduWuhanNingboQuanzhouQingdaoHuizhouZhenjiangJinanPhoenix cities average,Province/RegionGuangdongFujianGuangdongGuangdongJiangsuTianjinJiangsuGuangdongHenanJiangsuZhejiangJiangsuSichuanHubeiZhejiangFujianShandongGuangdongJiangsuShandong,TierTier 2Tier 2Tier 3Tier 3Tier 2Tier 2Tier 3Tier 3Tier 2Tier 2Tier 3Tier 3Tier 2Tier 2Tier 3Tier 3Tier 2Tier 3Tier 3Tier 2,GDP (RMB bn)6833783208631,5481,7899212237991,0503765771,2171,1918546651,001341383654792,Population (000)8,2613,9203,2307,46310,64715,6216,5291,6759,7248,2704,6144,70814,65810,7667,8758,5809,2044,7753,1817,2337,547,Per capita income (RMB)43,09646,25441,61343,12054,34137,13648,62842,53733,21449,99748,92646,05835,90239,73751,56039,65643,59833,21341,79443,05243,172,Job opportunities4.111.782.001.911.571.501.341.411.261.191.291.32,Education18.3%24.8%12.4%8.2%47.8%13.1%9.1%15.8%27.1%16.6%6.4%16.8%14.8%-26.6%0.3%16.2%10.6%19.7%7.1%6.1%13.2%,Density (per sq km)3,3422,4921,7941,9391,2541,3111,4111,0131,3061,2561,1791,0771,2091,2688027798384208278851,320,Rank from bottom,2019181716151413121110987654321,YingkouDezhouMaanshanSuqianChangchunAnshanDongyingBeihaiHuaianYichangNanningLiuzhouLuoyangGuilinZhanjiangHarbinBaojiMianyangGanzhouJilinRaven cities average95-city averageBeijingShanghaiGuangzhouShenzhen,LiaoningShandongAnhuiJiangsuJilinLiaoningShandongGuangxiJiangsuHubeiGuangxiGuangxiHenanGuangxiGuangdongHeilongjiangShaanxiSichuanJiangxiJilinBeijingShanghaiGuangdongGuangdong,Tier 3Tier 3Tier 3Tier 3Tier 2Tier 3Tier 3Tier 3Tier 3Tier 3Tier 2Tier 3Tier 3Tier 3Tier 3Tier 2Tier 3Tier 3Tier 3Tier 2Tier 1Tier 1Tier 1Tier 1,1302931492355932123481013053713702483782082586101931832192532835502,4902,7471,9611,949,2,4435,7922,2764,8797,6193,5742,1321,6444,8904,1307,0623,9596,7435,0097,27310,0043,7754,8118,8644,2955,0596,64821,72924,19714,04411,908,32,28522,76038,14224,08630,98831,59041,58029,41230,33529,73530,72830,27030,75230,12424,88733,19031,73029,40727,08625,52030,23036,25457,27557,69250,94148,695,1.050.990.990.821.031.031.120.930.861.050.940.990.960.930.881.040.980.880.911.020.971.191.591.681.612.94,-8.1%-5.5%-7.5%18.5%-1.7%-6.6%-11.5%-2.0%10.4%3.0%10.7%10.1%-5.4%16.0%-8.6%-7.5%-5.1%8.0%-1.3%-18.7%-0.6%6.7%18.3%5.0%14.0%26.6%,4665595635703703862684934861963192134441805501892082372251583548111,3243,8161,9276,097,Colour codes: Blue for data above the population average plus 0.5 standard deviation of the 95 cities; and red for negative data.Source: CEIC, CREIS, CRIC, NBS, HSBC estimates,EQUITIES CHINAAugust 2017,Places labelled ghost citiesmight be unoccupied simplybecause they are still underdevelopment12,Raven cities vs ghost cities Dont confuse raven cities with ghost cities; they are conceptuallyvery different Ghost cities are places that appear unoccupied, possibly becausethey are still under development Raven cities are not empty but rather lack home price growth potentialfrom the perspective of their attractiveness to internal migration flowsRavens arent ghostsThe term ghost city or ghost town has b