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Moore Capital Summer 2014 China team presentation

This document summarizes Thomas Fu's summer research project stress testing China's banking system. It finds that total credit in China's financial system has grown significantly since 2008, with shadow banking growing the fastest. Total credit is now over 200% of GDP, exceeding levels seen before most past banking crises. The rapid credit growth has been driven by real estate lending and loans to overcapacity sectors. This high and rising debt raises concerns about China's financial stability if credit growth slows or interest rates rise.

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Stress Testing China’s Banking System Summer Research Project Thomas Fu Intern Moore Capital Management August, 2014
Global Financial Crisis (2008-2009) 20 25 30 35 40 45 50 55 60 65 70 9/30/2003 9/30/2004 9/30/2005 9/30/2006 9/30/2007 9/30/2008 9/30/2009 9/30/2010 9/30/2011 9/30/2012 9/30/2013 Global Market Cap ($tn) 58% peak to trough drop
-6% -4% -2% 0% 2% 4% 6% 8% 10% 12% 14% Global GPD Growth Rates Eurozone China USA Brazil India Average global growth
Credit Intensity of GDP Growth 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Nominal GDP growth (lhs) 9% 13% 18% 17% 20% 29% 29% 10% 19% 23% 12% 12% Tota Social Financing growth (lhs) 7% 13% 10% 9% 12% 16% 18% 31% 24% 19% 20% 18% Credit Growth / Productivity Growth (rhs) 73% 101% 55% 55% 62% 57% 61% 297% 127% 79% 159% 150% 0% 50% 100% 150% 200% 250% 300% 350% 0% 5% 10% 15% 20% 25% 30% 35% Everything comes with a price!
What was happening in China 2008, August 8, Beijing Olympics 2008, May 12, Sichuan Earthquake 2010, May 1, Shanghai Expo 2009, China High speed train Steel, Infrastructure, cement
Where did the credit go? Real Estate, 18% "Overcapacity " sectors, 28% Other Corporates, 6% Consumer, 8% Government, 40% Other, 48% 2008 Chinese System Credit (bn$) Total= $7,293 Real Estate, 24% "Overcapacity" sectors, 34% Other Corporates, 10% Consumer, 9% Government, 23% Other, 32% 2013 Chinese system Credit (bn$) Source: CICC, Goldman Sachs, Merrill Lynch, Barclays, Credit Suisse, HSBC, MCM Analysis Total= $23,034
Shadow Banking • Banking regulation has forced credit off balance sheet, exacerbating the credit intensity – Wealth Management Products – Trust Products – Entrust Loans 2007 2008 2009 2010 2011 2012 2013 Trust 117 170 299 453 746 1,193 1,776 Entrust 223 299 409 545 769 927 1,430 NSCA WMP 46 81 100 289 427 477 541 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 Sources: Barclays Research, HSBC China Research, Credit Suisse Research, Merrill Lynch Research, MCM Analysis
China Shadow Banking System Credit (tn$) 2008 2009 2010 2011 2012 2013 Shadow Banking in $ $763 $1,183 $2,046 $2,833 $4,221 $6,114 % of Shadow Banking/GDP 17% 23% 34% 39% 50% 64% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% $- $1 $2 $3 $4 $5 $6 $7 Sources: Barclays Research, Bloomberg, MCM Analysis
China Total Real Estate Credit (tn$) 2008 2009 2010 2011 2012 2013 Total Real Estate sector credit $1,294 $1,937 $2,688 $3,311 $4,155 $5,562 % Real Estate Credit/GDP 28% 38% 45% 45% 50% 58% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% $- $1 $2 $3 $4 $5 $6 Sources: Barclays Research, HSBC China Research , Credit Suisse Research . Merrill Lynch Research, MCM Analysis
China “Overcapacity” Sector Credit (tn$) 2008 2009 2010 2011 2012 2013 Total Overcapacity sector credit $1,999 $2,767 $3,722 $4,743 $6,259 $7,883 % Overcapacity/GDP 44% 54% 63% 65% 75% 83% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% $- $1 $2 $3 $4 $5 $6 $7 $8 $9 Sources: Barclays Research, HSBC China Research, Credit Suisse Research, Merrill Lynch Research, MCM Analysis
“ Debt and overcapacity form a vicious spiral….As local governments and businesses borrow more in the name of new projects to pay interest on existing debt, they exacerbate the overcapacity situation. China must stop the debt-capacity spiral. Continuing it provides no way out.” —Andy Xie (Former Morgan Stanley Chief Asia Pacific Economist) “ Very rapid growth is often driven by the worsening imbalances, a rebalancing of China is necessarily going to experience much lower growth for many years.” —Michael Pettis (Peking University) Does the rapid growth in credit make China unstable?
This is Not News! • China has a credit problem • What have I been doing all summer? • Creating detailed map of the credit system by vintage! • Using the data to create a banking system stress test
Data Resources Primary • PBOC—Bank Loans • CBRC—NPL, RE, LGFV, Overcapacity • China Trust Association— Trust sector • China Bonds Association—Bonds Secondary • Barclays (May Yan)—China Shadow Banking System, Property • CICC—LGFV Loans • Goldman Sachs (Roy Ramos, Ning Ma) • Merrill Lynch (Michael Li)—Bank Loans • Deutsch (Michael Zhang)—Banking system PnL • HSBC (Todd Dunivant)—Bonds and economic outlook • Credit Suisse (Steven Zhu)—Trust breakdown • JP Morgan—property, NPL • Bloomberg—NPL, Currency
China System Credit by Vintage 2008 2009 2010 2011 2012 2013 On Balance Sheet Loans LGFV 570 3,050 1,890 10 200 2,600 Real Estate 342 1,830 1,134 6 120 1,560 Others 228 1,220 756 4 80 1,040 Mining 103 184 211 236 262 160 Manufacturing 473 1,019 1,116 1,671 1,626 943 Construction 81 134 406 363 454 460 Transportation 352 689 745 349 409 356 Property 176 593 878 151 290 536 All other 498 404 -174 2,152 1,089 1,604 Total industry loans 2,253 6,073 5,072 4,932 4,330 6,659 Total consumer loans 454 2,084 982 1,438 1,030 2,440 Mortgage 185 1,532 1,070 856 641 1,637 Overseas loans 97 119 195 371 289 592 Policy bank loans 1,366 1,353 1,702 134 2,547 -786 Net new system loans 4,170 9,629 7,951 6,875 8,196 8,905 Bonds Mining(Materials) 56 295 108 139 265 118 Manufacturing 75 146 246 288 561 0 Property + Construction 40 127 163 135 394 326 Transportation 31 159 138 69 143 111 All other 568 393 385 506 426 681 Net new private sector bonds 769 1,121 1,039 1,136 1,788 1,236 LGFV 107 338 315 355 962 1,100 Railway 76 98 189 99 150 149 Municipal 0 200 200 200 50 212 FINS (policy banks) 877 900 736 1,518 1,741 1,263 PBOC bills 1,234 -572 -354 -1,761 -784 -612 Central government 118 674 702 419 515 916 Net new government bonds 2,412 1,638 1,788 830 2,634 3,028 Net new system bonds 3,181 2,759 2,827 1,966 4,422 4,264 Off Balance Sheet Fin guarantee 140 419 676 537 258 362 NSCA of WMP 225 107 1,257 815 235 331 Entrusted loan 426 678 875 1,296 846 2,980 LGFV -79 136 11 879 677 276 Trust 319 841 999 1,771 2,660 3,436 Infrastructure 0 148 176 21 634 952 Industrial and Commercial 0 245 292 410 914 1,039 Real Estate 0 69 82 256 0 345 Financial 0 2 149 439 123 524 Bonds 0 38 75 113 307 155 Stocks 6 15 18 24 41 89 Other 313 324 208 508 641 332 Discounted bills repo 240 480 1,486 -444 1,146 -300 Security firm's AMP 10 56 39 95 1,608 3,310 All other 441 107 332 466 1,406 997 Net new system shadow credit 1,801 2,688 5,664 4,536 8,159 11,116 Net new system credit 9,153 15,076 16,443 13,377 20,777 24,285 % of GDP 28% 43% 41% 28% 40% 41% ChinaSystemCreditbyVintage 2008 2009 2010 2011 2012 2013 Total o/wRE 1,825 4,081 4,831 3,305 4,661 8,146 o/wovercapacity 2,298 4,768 6,111 5,594 8,601 9,224 o/wconsumerloans 454 2,084 982 1,438 1,030 2,440 o/wothercorporate 904 1,490 1,344 2,431 2,267 3,333 o/wothergovernment 3,671 2,653 3,175 609 4,219 1,142 Totalsystem 9,153 15,076 16,443 13,377 20,777 24,285 OnBalanceSheet o/wRE 1,562 4,124 4,315 3,139 4,176 6,431 o/wovercapacity 2,037 4,744 5,304 5,486 7,685 6,723 o/wconsumerloans 454 2,084 982 1,438 1,030 2,440 o/wothercorporate 768 1,399 1,147 2,238 1,965 2,635 o/wothergovernment 3,671 2,653 3,175 609 4,219 1,142 Totalonbalancesheet 8,492 15,004 14,923 12,911 19,074 19,370 93% 100% 91% 97% 92% 80% OffBalanceSheet o/wRE 263 -43 516 165 485 1,715 o/wovercapacity 260 24 807 108 916 2,501 o/wconsumerloans 0 0 0 0 0 0 o/wothercorporate 136 90 197 192 302 698 o/wothergovernment 0 0 0 0 0 0 Totaloffbalancesheet 660 72 1,520 466 1,703 4,915 Vintage Model
Total Credit to GDP ahead of Banking Crises 66% 147% 151% 160% 160% 230% 241% 287% 355% 370% Indonesia 1998 Thailand 1997 Malaysia 1998 Korea 1998 China 2008 Japan 1990 China 2013 Hong Kong 1998 United States 2008 UK 2008 Source: Goldman Sachs Equity Research, MCM Analysis
Roy Ramos, from “Parting Thoughts”, after 17 years covering Asian Banks at Goldman: “…we have observed empirically…that every time interest expense for the aggregate private sector goes beyond 15% of GDP, a banking crisis has ensued for that particular sector/country…We point to several instances of banking crises ensuing at an even lower(10% to 11%) interest expense to GDP ratio—Indonesia. Japan, Korea.” Interest expense as % of GDP = (Total Banking loans/GDP) Ratio x Average borrowing cost
Roy Ramos—“Rule of 15%” Interest expense as % of GDP 6.1% 10.1% 12.2% 13.1% 14.1% 14.3% 15.0% 16.4% 16.7% 18.5% 21.3% 22.1% China, with Shadow, 2008 Japan 1990 China, with Shadow, 2013 Indonesia 1998 Korea 1998 China, with Shadow, 2014 Malaysia 1998 China, with Shadow, 2014 Hong Kong 1998 UK 2008 United States 2008 Thailand 1997 Assumes +100bps impact from interest rate liberalization
Banking System Profitability and Capital 2007 2008 2009 2010 2011 2012 2013 NIM 2.9% 3.0% 2.3% 2.4% 2.6% 2.6% 2.6% PPP ROA 1.8% 1.9% 1.5% 1.6% 1.8% 1.8% 1.9% TCER 3.1% 5.6% 5.1% 5.8% 5.9% 6.1% 6.3% ROTCE 30.1% 18.3% 18.6% 18.6% 20.1% 19.8% 19.4% 0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0%
0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% 9.0% 10.0% 11.0% 12.0% 13.0% 14.0% 15.0% 16.0% 17.0% 18.0% 3/1/2004 6/1/2004 9/1/2004 12/1/2004 3/1/2005 6/1/2005 9/1/2005 12/1/2005 3/1/2006 6/1/2006 9/1/2006 12/1/2006 3/1/2007 6/1/2007 9/1/2007 12/1/2007 3/1/2008 6/1/2008 9/1/2008 12/1/2008 3/1/2009 6/1/2009 9/1/2009 12/1/2009 3/1/2010 6/1/2010 9/1/2010 12/1/2010 3/1/2011 6/1/2011 9/1/2011 12/1/2011 3/1/2012 6/1/2012 9/1/2012 12/1/2012 3/1/2013 6/1/2013 9/1/2013 12/1/2013 3/1/2014 China Banking System NPL Ratio
Total Credit to GDP ahead of Banking Crises 66% 147% 151% 160% 160% 230% 241% 287% 355% 370% Indonesia 1998 Thailand 1997 Malaysia 1998 Korea 1998 China 2008 Japan 1990 China 2013 Hong Kong 1998 United States 2008 UK 2008 Source: Goldman Sachs Equity Research, MCM Analysis
Japan Australia Hong Kong Singapore Korea Phillipines Malaysia China Thailand Indonesia 1990's NPL 6% 7% 10% 13% 14% 18% 18% 40% 48% 59% 0% 10% 20% 30% 40% 50% 60% 1990's Global Peak NPL Ratios Australia Hong Kong Indonesia Singapore Japan USA Spain Korea Phillipines Malaysia Ireland China Thailand 2000's NPL 2% 7% 8% 8% 9% 10% 11% 12% 17% 18% 19% 20% 31% 0% 5% 10% 15% 20% 25% 30% 35% 2000's Global Peak NPL Ratios
Scenario 1: Doomsday Scenario 1 Loss Assumptions 2008 Vintage 2009 Vintage 2010 Vintage 2011 Vintage 2012 Vintage 2013 Vintage Frequency RE 40% 50% 50% 50% 40% 40% Overcapacity 40% 50% 50% 50% 40% 40% Consumer 10% 10% 10% 10% 10% 10% Other Corporate 5% 5% 5% 5% 5% 5% Government 0% 0% 0% 0% 0% 0% Severity RE 60% 70% 70% 70% 60% 60% Overcapacity 60% 70% 70% 70% 60% 60% Consumer 60% 70% 70% 70% 60% 60% Other Corporate 60% 70% 70% 70% 60% 60% Government 0% 0% 0% 0% 0% 0% Loss rate Total 11% 22% 24% 25% 16% 18% Other Assumptions Duration of loss recognition: 2 Loss on pre-2008 vintage 7% Dividends cut? Y Draw existing reserves? N Bank Loss Model 2014 2015 2016 2017 2018 2019 2020 System NIM 2.6% 2.6% NA NA NA NA NA System PPP 2,884 2,929 NA NA NA NA NA Losses on '08-'13 vintage 8,521 8,521 NA NA NA NA NA Losses on pre-'08 vintage 1,166 1,166 NA NA NA NA NA Net income -5,238 -5,203 NA NA NA NA NA System tangible common equity 4,369 -834 NA NA NA NA NA TCER 3.1% -0.6% NA NA NA NA NA ROTCE -75.0% -294.4% NA NA NA NA NA Cumulative loss 25% Current P / Burndown -12.8x Capital hole $bn -1,576 Dilution to recap to 6.3% TCER -91% • 25% cum. Loss • 2 years of loss recognition and PPP • Dividends cut • No draw on existing reserves • 0% avg asset growth • No NIM declines, no interest rate liberalization • Equity wiped out
Scenario 2: Doomsday lite • 20% cum. Loss • 3 years of loss recognition and PPP • Dividends cut • No draw on existing reserves • 0% avg asset growth • No NIM declines, no interest rate liberalization • Low single digit ROTCE’s • 2.2x 2016 burndown TBV Scenario 2 Loss Assumptions 2008 Vintage 2009 Vintage 2010 Vintage 2011 Vintage 2012 Vintage 2013 Vintage Frequency RE 30% 50% 50% 30% 30% 30% Overcapacity 30% 50% 50% 30% 30% 30% Consumer 10% 10% 10% 10% 10% 10% Other Corporate 5% 5% 5% 5% 5% 5% Government 0% 0% 0% 0% 0% 0% Severity RE 65% 65% 65% 65% 65% 65% Overcapacity 65% 65% 65% 65% 65% 65% Consumer 65% 65% 65% 65% 65% 65% Other Corporate 65% 65% 65% 65% 65% 65% Government 0% 0% 0% 0% 0% 0% Loss rate Total 9% 20% 22% 14% 13% 15% Other Assumptions Duration of loss recognition: 3 Loss on pre-2008 vintage 6% Dividends cut? Y Draw existing reserves? N Bank Loss Model 2014 2015 2016 2017 2018 2019 2020 System NIM 2.4% 2.3% 2.1% NA NA NA NA System PPP 3,032 3,236 3,450 NA NA NA NA Losses on '08-'13 vintage 4,665 4,665 4,665 NA NA NA NA Losses on pre-'08 vintage 666 666 666 NA NA NA NA Net income -1,771 -1,614 -1,449 NA NA NA NA System tangible common equity 7,836 6,222 4,774 NA NA NA NA TCER 4.9% 3.5% 2.4% NA NA NA NA ROTCE -20.3% -23.0% -26.3% NA NA NA NA Cumulative loss 20% Current P / Burndown 2.2x Capital hole $bn -1,226 Dilution to recap to 6.3% TCER -71%
Scenario 3: More realistic Scenario 3 Loss Assumptions 2008 Vintage 2009 Vintage 2010 Vintage 2011 Vintage 2012 Vintage 2013 Vintage Frequency RE 20% 25% 25% 25% 25% 20% Overcapacity 20% 25% 25% 25% 25% 20% Consumer 8% 10% 10% 10% 10% 8% Other Corporate 5% 5% 5% 5% 5% 5% Government 0% 0% 0% 0% 0% 0% Severity RE 60% 60% 60% 60% 60% 60% Overcapacity 60% 60% 60% 60% 60% 60% Consumer 60% 60% 60% 60% 60% 60% Other Corporate 60% 60% 60% 60% 60% 60% Government 0% 0% 0% 0% 0% 0% Loss rate Total 6% 10% 11% 11% 10% 9% Other Assumptions Duration of loss recognition: 4 Loss on pre-2008 vintage 6% Dividends cut? N Draw existing reserves? N Bank Loss Model 2014 2015 2016 2017 2018 2019 2020 System NIM 2.6% 2.6% 2.6% 2.6% NA NA NA System PPP 3,086 3,354 3,644 3,959 NA NA NA Losses on '08-'13 vintage 2,133 2,133 2,133 2,133 NA NA NA Losses on pre-'08 vintage 500 500 500 500 NA NA NA Net income 349 555 779 1,021 NA NA NA System tangible common equity 9,358 9,316 9,497 9,920 NA NA NA TCER 5.9% 5.5% 5.2% 5.1% NA NA NA ROTCE 3.7% 5.9% 8.3% 10.5% NA NA NA Cumulative loss 13% Current P / Burndown 1.1x Capital hole $bn -392 Dilution to recap to 6.3% TCER -23% • 13% cum. Loss • 4 years of loss recognition and PPP • Dividends not cut • No draw on existing reserves • 7% avg asset growth to support economy • No NIM declines, no interest rate liberalization • Mid single digit ROTCE’s • 1.1x 2017 burndown TBV
Scenario 4: Base case Scenario 4 Loss Assumptions 2008 Vintage 2009 Vintage 2010 Vintage 2011 Vintage 2012 Vintage 2013 Vintage Frequency RE 15% 15% 15% 15% 15% 15% Overcapacity 15% 15% 15% 15% 15% 15% Consumer 8% 10% 10% 10% 10% 8% Other Corporate 5% 5% 5% 5% 5% 5% Government 0% 0% 0% 0% 0% 0% Severity RE 60% 60% 60% 60% 60% 60% Overcapacity 60% 60% 60% 60% 60% 60% Consumer 60% 60% 60% 60% 60% 60% Other Corporate 60% 60% 60% 60% 60% 60% Government 0% 0% 0% 0% 0% 0% Loss rate Total 5% 6% 7% 7% 6% 7% Other Assumptions Duration of loss recognition: 5 Loss on pre-2008 vintage 5% Dividends cut? N Draw existing reserves? N Bank Loss Model 2014 2015 2016 2017 2018 2019 2020 System NIM 2.4% 2.3% 2.2% 2.1% 2.0% NA NA System PPP 3,032 3,236 3,507 3,800 4,117 NA NA Losses on '08-'13 vintage 1,146 1,146 1,146 1,146 1,146 NA NA Losses on pre-'08 vintage 333 333 333 333 333 NA NA Net income 1,196 1,353 1,562 1,787 2,031 NA NA System tangible common equity 10,205 10,960 11,924 13,114 14,548 NA NA TCER 6.2% 6.0% 6.0% 5.9% 6.0% NA NA ROTCE 12.1% 12.8% 13.6% 14.3% 14.7% NA NA Cumulative loss 9% Current P / Burndown 0.7x Capital hole $bn -119 Dilution to recap to 6.3% TCER -7% • 9% cum. Loss • 5 years of loss recognition and PPP • Dividends not cut • No draw on existing reserves • 10% avg asset growth • 80bps gradual NIM decline on interest rate liberalization • Low to mid teens ROTCE’s • 0.7x 2018 burndown TBV
Takeaways • In our base case China takes 5 years to clean up the NPL’s – we think the gov’t can manage this with their liquidity resources • ROTCE’s sustain in 14-15% range • If COE = ~12% in this setup, stocks would be fairly valued at ~1.3x TBV
Takeaways cont’d • In the absence of more clarity on – Real estate prices – The impact of fiscal, monetary, SOE reforms – Corruption crack down – FAI decrease – LOSS RECOGNITION AND NPL FORMATION • …we think trading the banks in a range of 0.85x – 1.3x TBV makes sense
ICBC P/TBV range Current range = 0.9x – 1.25x TBV
“ China’s future problem is not about questioning its growth potential. It is how to reform its social and economic structure. “ — Andy Xie

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Moore Capital Summer 2014 China team presentation

  • 1.
    Stress Testing China’s BankingSystem Summer Research Project Thomas Fu Intern Moore Capital Management August, 2014
  • 2.
    Global Financial Crisis(2008-2009) 20 25 30 35 40 45 50 55 60 65 70 9/30/2003 9/30/2004 9/30/2005 9/30/2006 9/30/2007 9/30/2008 9/30/2009 9/30/2010 9/30/2011 9/30/2012 9/30/2013 Global Market Cap ($tn) 58% peak to trough drop
  • 3.
    -6% -4% -2% 0% 2% 4% 6% 8% 10% 12% 14% Global GPD GrowthRates Eurozone China USA Brazil India Average global growth
  • 4.
    Credit Intensity ofGDP Growth 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Nominal GDP growth (lhs) 9% 13% 18% 17% 20% 29% 29% 10% 19% 23% 12% 12% Tota Social Financing growth (lhs) 7% 13% 10% 9% 12% 16% 18% 31% 24% 19% 20% 18% Credit Growth / Productivity Growth (rhs) 73% 101% 55% 55% 62% 57% 61% 297% 127% 79% 159% 150% 0% 50% 100% 150% 200% 250% 300% 350% 0% 5% 10% 15% 20% 25% 30% 35% Everything comes with a price!
  • 5.
    What was happeningin China 2008, August 8, Beijing Olympics 2008, May 12, Sichuan Earthquake 2010, May 1, Shanghai Expo 2009, China High speed train Steel, Infrastructure, cement
  • 6.
    Where did thecredit go? Real Estate, 18% "Overcapacity " sectors, 28% Other Corporates, 6% Consumer, 8% Government, 40% Other, 48% 2008 Chinese System Credit (bn$) Total= $7,293 Real Estate, 24% "Overcapacity" sectors, 34% Other Corporates, 10% Consumer, 9% Government, 23% Other, 32% 2013 Chinese system Credit (bn$) Source: CICC, Goldman Sachs, Merrill Lynch, Barclays, Credit Suisse, HSBC, MCM Analysis Total= $23,034
  • 7.
    Shadow Banking • Bankingregulation has forced credit off balance sheet, exacerbating the credit intensity – Wealth Management Products – Trust Products – Entrust Loans 2007 2008 2009 2010 2011 2012 2013 Trust 117 170 299 453 746 1,193 1,776 Entrust 223 299 409 545 769 927 1,430 NSCA WMP 46 81 100 289 427 477 541 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 Sources: Barclays Research, HSBC China Research, Credit Suisse Research, Merrill Lynch Research, MCM Analysis
  • 8.
    China Shadow BankingSystem Credit (tn$) 2008 2009 2010 2011 2012 2013 Shadow Banking in $ $763 $1,183 $2,046 $2,833 $4,221 $6,114 % of Shadow Banking/GDP 17% 23% 34% 39% 50% 64% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% $- $1 $2 $3 $4 $5 $6 $7 Sources: Barclays Research, Bloomberg, MCM Analysis
  • 9.
    China Total RealEstate Credit (tn$) 2008 2009 2010 2011 2012 2013 Total Real Estate sector credit $1,294 $1,937 $2,688 $3,311 $4,155 $5,562 % Real Estate Credit/GDP 28% 38% 45% 45% 50% 58% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% $- $1 $2 $3 $4 $5 $6 Sources: Barclays Research, HSBC China Research , Credit Suisse Research . Merrill Lynch Research, MCM Analysis
  • 10.
    China “Overcapacity” SectorCredit (tn$) 2008 2009 2010 2011 2012 2013 Total Overcapacity sector credit $1,999 $2,767 $3,722 $4,743 $6,259 $7,883 % Overcapacity/GDP 44% 54% 63% 65% 75% 83% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% $- $1 $2 $3 $4 $5 $6 $7 $8 $9 Sources: Barclays Research, HSBC China Research, Credit Suisse Research, Merrill Lynch Research, MCM Analysis
  • 11.
    “ Debt andovercapacity form a vicious spiral….As local governments and businesses borrow more in the name of new projects to pay interest on existing debt, they exacerbate the overcapacity situation. China must stop the debt-capacity spiral. Continuing it provides no way out.” —Andy Xie (Former Morgan Stanley Chief Asia Pacific Economist) “ Very rapid growth is often driven by the worsening imbalances, a rebalancing of China is necessarily going to experience much lower growth for many years.” —Michael Pettis (Peking University) Does the rapid growth in credit make China unstable?
  • 12.
    This is NotNews! • China has a credit problem • What have I been doing all summer? • Creating detailed map of the credit system by vintage! • Using the data to create a banking system stress test
  • 13.
    Data Resources Primary • PBOC—BankLoans • CBRC—NPL, RE, LGFV, Overcapacity • China Trust Association— Trust sector • China Bonds Association—Bonds Secondary • Barclays (May Yan)—China Shadow Banking System, Property • CICC—LGFV Loans • Goldman Sachs (Roy Ramos, Ning Ma) • Merrill Lynch (Michael Li)—Bank Loans • Deutsch (Michael Zhang)—Banking system PnL • HSBC (Todd Dunivant)—Bonds and economic outlook • Credit Suisse (Steven Zhu)—Trust breakdown • JP Morgan—property, NPL • Bloomberg—NPL, Currency
  • 14.
    China System Creditby Vintage 2008 2009 2010 2011 2012 2013 On Balance Sheet Loans LGFV 570 3,050 1,890 10 200 2,600 Real Estate 342 1,830 1,134 6 120 1,560 Others 228 1,220 756 4 80 1,040 Mining 103 184 211 236 262 160 Manufacturing 473 1,019 1,116 1,671 1,626 943 Construction 81 134 406 363 454 460 Transportation 352 689 745 349 409 356 Property 176 593 878 151 290 536 All other 498 404 -174 2,152 1,089 1,604 Total industry loans 2,253 6,073 5,072 4,932 4,330 6,659 Total consumer loans 454 2,084 982 1,438 1,030 2,440 Mortgage 185 1,532 1,070 856 641 1,637 Overseas loans 97 119 195 371 289 592 Policy bank loans 1,366 1,353 1,702 134 2,547 -786 Net new system loans 4,170 9,629 7,951 6,875 8,196 8,905 Bonds Mining(Materials) 56 295 108 139 265 118 Manufacturing 75 146 246 288 561 0 Property + Construction 40 127 163 135 394 326 Transportation 31 159 138 69 143 111 All other 568 393 385 506 426 681 Net new private sector bonds 769 1,121 1,039 1,136 1,788 1,236 LGFV 107 338 315 355 962 1,100 Railway 76 98 189 99 150 149 Municipal 0 200 200 200 50 212 FINS (policy banks) 877 900 736 1,518 1,741 1,263 PBOC bills 1,234 -572 -354 -1,761 -784 -612 Central government 118 674 702 419 515 916 Net new government bonds 2,412 1,638 1,788 830 2,634 3,028 Net new system bonds 3,181 2,759 2,827 1,966 4,422 4,264 Off Balance Sheet Fin guarantee 140 419 676 537 258 362 NSCA of WMP 225 107 1,257 815 235 331 Entrusted loan 426 678 875 1,296 846 2,980 LGFV -79 136 11 879 677 276 Trust 319 841 999 1,771 2,660 3,436 Infrastructure 0 148 176 21 634 952 Industrial and Commercial 0 245 292 410 914 1,039 Real Estate 0 69 82 256 0 345 Financial 0 2 149 439 123 524 Bonds 0 38 75 113 307 155 Stocks 6 15 18 24 41 89 Other 313 324 208 508 641 332 Discounted bills repo 240 480 1,486 -444 1,146 -300 Security firm's AMP 10 56 39 95 1,608 3,310 All other 441 107 332 466 1,406 997 Net new system shadow credit 1,801 2,688 5,664 4,536 8,159 11,116 Net new system credit 9,153 15,076 16,443 13,377 20,777 24,285 % of GDP 28% 43% 41% 28% 40% 41% ChinaSystemCreditbyVintage 2008 2009 2010 2011 2012 2013 Total o/wRE 1,825 4,081 4,831 3,305 4,661 8,146 o/wovercapacity 2,298 4,768 6,111 5,594 8,601 9,224 o/wconsumerloans 454 2,084 982 1,438 1,030 2,440 o/wothercorporate 904 1,490 1,344 2,431 2,267 3,333 o/wothergovernment 3,671 2,653 3,175 609 4,219 1,142 Totalsystem 9,153 15,076 16,443 13,377 20,777 24,285 OnBalanceSheet o/wRE 1,562 4,124 4,315 3,139 4,176 6,431 o/wovercapacity 2,037 4,744 5,304 5,486 7,685 6,723 o/wconsumerloans 454 2,084 982 1,438 1,030 2,440 o/wothercorporate 768 1,399 1,147 2,238 1,965 2,635 o/wothergovernment 3,671 2,653 3,175 609 4,219 1,142 Totalonbalancesheet 8,492 15,004 14,923 12,911 19,074 19,370 93% 100% 91% 97% 92% 80% OffBalanceSheet o/wRE 263 -43 516 165 485 1,715 o/wovercapacity 260 24 807 108 916 2,501 o/wconsumerloans 0 0 0 0 0 0 o/wothercorporate 136 90 197 192 302 698 o/wothergovernment 0 0 0 0 0 0 Totaloffbalancesheet 660 72 1,520 466 1,703 4,915 Vintage Model
  • 15.
    Total Credit toGDP ahead of Banking Crises 66% 147% 151% 160% 160% 230% 241% 287% 355% 370% Indonesia 1998 Thailand 1997 Malaysia 1998 Korea 1998 China 2008 Japan 1990 China 2013 Hong Kong 1998 United States 2008 UK 2008 Source: Goldman Sachs Equity Research, MCM Analysis
  • 16.
    Roy Ramos, from“Parting Thoughts”, after 17 years covering Asian Banks at Goldman: “…we have observed empirically…that every time interest expense for the aggregate private sector goes beyond 15% of GDP, a banking crisis has ensued for that particular sector/country…We point to several instances of banking crises ensuing at an even lower(10% to 11%) interest expense to GDP ratio—Indonesia. Japan, Korea.” Interest expense as % of GDP = (Total Banking loans/GDP) Ratio x Average borrowing cost
  • 17.
    Roy Ramos—“Rule of15%” Interest expense as % of GDP 6.1% 10.1% 12.2% 13.1% 14.1% 14.3% 15.0% 16.4% 16.7% 18.5% 21.3% 22.1% China, with Shadow, 2008 Japan 1990 China, with Shadow, 2013 Indonesia 1998 Korea 1998 China, with Shadow, 2014 Malaysia 1998 China, with Shadow, 2014 Hong Kong 1998 UK 2008 United States 2008 Thailand 1997 Assumes +100bps impact from interest rate liberalization
  • 18.
    Banking System Profitabilityand Capital 2007 2008 2009 2010 2011 2012 2013 NIM 2.9% 3.0% 2.3% 2.4% 2.6% 2.6% 2.6% PPP ROA 1.8% 1.9% 1.5% 1.6% 1.8% 1.8% 1.9% TCER 3.1% 5.6% 5.1% 5.8% 5.9% 6.1% 6.3% ROTCE 30.1% 18.3% 18.6% 18.6% 20.1% 19.8% 19.4% 0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0%
  • 19.
  • 20.
    Total Credit toGDP ahead of Banking Crises 66% 147% 151% 160% 160% 230% 241% 287% 355% 370% Indonesia 1998 Thailand 1997 Malaysia 1998 Korea 1998 China 2008 Japan 1990 China 2013 Hong Kong 1998 United States 2008 UK 2008 Source: Goldman Sachs Equity Research, MCM Analysis
  • 21.
    Japan Australia HongKong Singapore Korea Phillipines Malaysia China Thailand Indonesia 1990's NPL 6% 7% 10% 13% 14% 18% 18% 40% 48% 59% 0% 10% 20% 30% 40% 50% 60% 1990's Global Peak NPL Ratios Australia Hong Kong Indonesia Singapore Japan USA Spain Korea Phillipines Malaysia Ireland China Thailand 2000's NPL 2% 7% 8% 8% 9% 10% 11% 12% 17% 18% 19% 20% 31% 0% 5% 10% 15% 20% 25% 30% 35% 2000's Global Peak NPL Ratios
  • 22.
    Scenario 1: Doomsday Scenario1 Loss Assumptions 2008 Vintage 2009 Vintage 2010 Vintage 2011 Vintage 2012 Vintage 2013 Vintage Frequency RE 40% 50% 50% 50% 40% 40% Overcapacity 40% 50% 50% 50% 40% 40% Consumer 10% 10% 10% 10% 10% 10% Other Corporate 5% 5% 5% 5% 5% 5% Government 0% 0% 0% 0% 0% 0% Severity RE 60% 70% 70% 70% 60% 60% Overcapacity 60% 70% 70% 70% 60% 60% Consumer 60% 70% 70% 70% 60% 60% Other Corporate 60% 70% 70% 70% 60% 60% Government 0% 0% 0% 0% 0% 0% Loss rate Total 11% 22% 24% 25% 16% 18% Other Assumptions Duration of loss recognition: 2 Loss on pre-2008 vintage 7% Dividends cut? Y Draw existing reserves? N Bank Loss Model 2014 2015 2016 2017 2018 2019 2020 System NIM 2.6% 2.6% NA NA NA NA NA System PPP 2,884 2,929 NA NA NA NA NA Losses on '08-'13 vintage 8,521 8,521 NA NA NA NA NA Losses on pre-'08 vintage 1,166 1,166 NA NA NA NA NA Net income -5,238 -5,203 NA NA NA NA NA System tangible common equity 4,369 -834 NA NA NA NA NA TCER 3.1% -0.6% NA NA NA NA NA ROTCE -75.0% -294.4% NA NA NA NA NA Cumulative loss 25% Current P / Burndown -12.8x Capital hole $bn -1,576 Dilution to recap to 6.3% TCER -91% • 25% cum. Loss • 2 years of loss recognition and PPP • Dividends cut • No draw on existing reserves • 0% avg asset growth • No NIM declines, no interest rate liberalization • Equity wiped out
  • 23.
    Scenario 2: Doomsdaylite • 20% cum. Loss • 3 years of loss recognition and PPP • Dividends cut • No draw on existing reserves • 0% avg asset growth • No NIM declines, no interest rate liberalization • Low single digit ROTCE’s • 2.2x 2016 burndown TBV Scenario 2 Loss Assumptions 2008 Vintage 2009 Vintage 2010 Vintage 2011 Vintage 2012 Vintage 2013 Vintage Frequency RE 30% 50% 50% 30% 30% 30% Overcapacity 30% 50% 50% 30% 30% 30% Consumer 10% 10% 10% 10% 10% 10% Other Corporate 5% 5% 5% 5% 5% 5% Government 0% 0% 0% 0% 0% 0% Severity RE 65% 65% 65% 65% 65% 65% Overcapacity 65% 65% 65% 65% 65% 65% Consumer 65% 65% 65% 65% 65% 65% Other Corporate 65% 65% 65% 65% 65% 65% Government 0% 0% 0% 0% 0% 0% Loss rate Total 9% 20% 22% 14% 13% 15% Other Assumptions Duration of loss recognition: 3 Loss on pre-2008 vintage 6% Dividends cut? Y Draw existing reserves? N Bank Loss Model 2014 2015 2016 2017 2018 2019 2020 System NIM 2.4% 2.3% 2.1% NA NA NA NA System PPP 3,032 3,236 3,450 NA NA NA NA Losses on '08-'13 vintage 4,665 4,665 4,665 NA NA NA NA Losses on pre-'08 vintage 666 666 666 NA NA NA NA Net income -1,771 -1,614 -1,449 NA NA NA NA System tangible common equity 7,836 6,222 4,774 NA NA NA NA TCER 4.9% 3.5% 2.4% NA NA NA NA ROTCE -20.3% -23.0% -26.3% NA NA NA NA Cumulative loss 20% Current P / Burndown 2.2x Capital hole $bn -1,226 Dilution to recap to 6.3% TCER -71%
  • 24.
    Scenario 3: Morerealistic Scenario 3 Loss Assumptions 2008 Vintage 2009 Vintage 2010 Vintage 2011 Vintage 2012 Vintage 2013 Vintage Frequency RE 20% 25% 25% 25% 25% 20% Overcapacity 20% 25% 25% 25% 25% 20% Consumer 8% 10% 10% 10% 10% 8% Other Corporate 5% 5% 5% 5% 5% 5% Government 0% 0% 0% 0% 0% 0% Severity RE 60% 60% 60% 60% 60% 60% Overcapacity 60% 60% 60% 60% 60% 60% Consumer 60% 60% 60% 60% 60% 60% Other Corporate 60% 60% 60% 60% 60% 60% Government 0% 0% 0% 0% 0% 0% Loss rate Total 6% 10% 11% 11% 10% 9% Other Assumptions Duration of loss recognition: 4 Loss on pre-2008 vintage 6% Dividends cut? N Draw existing reserves? N Bank Loss Model 2014 2015 2016 2017 2018 2019 2020 System NIM 2.6% 2.6% 2.6% 2.6% NA NA NA System PPP 3,086 3,354 3,644 3,959 NA NA NA Losses on '08-'13 vintage 2,133 2,133 2,133 2,133 NA NA NA Losses on pre-'08 vintage 500 500 500 500 NA NA NA Net income 349 555 779 1,021 NA NA NA System tangible common equity 9,358 9,316 9,497 9,920 NA NA NA TCER 5.9% 5.5% 5.2% 5.1% NA NA NA ROTCE 3.7% 5.9% 8.3% 10.5% NA NA NA Cumulative loss 13% Current P / Burndown 1.1x Capital hole $bn -392 Dilution to recap to 6.3% TCER -23% • 13% cum. Loss • 4 years of loss recognition and PPP • Dividends not cut • No draw on existing reserves • 7% avg asset growth to support economy • No NIM declines, no interest rate liberalization • Mid single digit ROTCE’s • 1.1x 2017 burndown TBV
  • 25.
    Scenario 4: Basecase Scenario 4 Loss Assumptions 2008 Vintage 2009 Vintage 2010 Vintage 2011 Vintage 2012 Vintage 2013 Vintage Frequency RE 15% 15% 15% 15% 15% 15% Overcapacity 15% 15% 15% 15% 15% 15% Consumer 8% 10% 10% 10% 10% 8% Other Corporate 5% 5% 5% 5% 5% 5% Government 0% 0% 0% 0% 0% 0% Severity RE 60% 60% 60% 60% 60% 60% Overcapacity 60% 60% 60% 60% 60% 60% Consumer 60% 60% 60% 60% 60% 60% Other Corporate 60% 60% 60% 60% 60% 60% Government 0% 0% 0% 0% 0% 0% Loss rate Total 5% 6% 7% 7% 6% 7% Other Assumptions Duration of loss recognition: 5 Loss on pre-2008 vintage 5% Dividends cut? N Draw existing reserves? N Bank Loss Model 2014 2015 2016 2017 2018 2019 2020 System NIM 2.4% 2.3% 2.2% 2.1% 2.0% NA NA System PPP 3,032 3,236 3,507 3,800 4,117 NA NA Losses on '08-'13 vintage 1,146 1,146 1,146 1,146 1,146 NA NA Losses on pre-'08 vintage 333 333 333 333 333 NA NA Net income 1,196 1,353 1,562 1,787 2,031 NA NA System tangible common equity 10,205 10,960 11,924 13,114 14,548 NA NA TCER 6.2% 6.0% 6.0% 5.9% 6.0% NA NA ROTCE 12.1% 12.8% 13.6% 14.3% 14.7% NA NA Cumulative loss 9% Current P / Burndown 0.7x Capital hole $bn -119 Dilution to recap to 6.3% TCER -7% • 9% cum. Loss • 5 years of loss recognition and PPP • Dividends not cut • No draw on existing reserves • 10% avg asset growth • 80bps gradual NIM decline on interest rate liberalization • Low to mid teens ROTCE’s • 0.7x 2018 burndown TBV
  • 26.
    Takeaways • In ourbase case China takes 5 years to clean up the NPL’s – we think the gov’t can manage this with their liquidity resources • ROTCE’s sustain in 14-15% range • If COE = ~12% in this setup, stocks would be fairly valued at ~1.3x TBV
  • 27.
    Takeaways cont’d • Inthe absence of more clarity on – Real estate prices – The impact of fiscal, monetary, SOE reforms – Corruption crack down – FAI decrease – LOSS RECOGNITION AND NPL FORMATION • …we think trading the banks in a range of 0.85x – 1.3x TBV makes sense
  • 28.
    ICBC P/TBV range Current range= 0.9x – 1.25x TBV
  • 29.
    “ China’s futureproblem is not about questioning its growth potential. It is how to reform its social and economic structure. “ — Andy Xie

Editor's Notes

  • #12 If you look at what happened in 2012, in the first half, GDP growth rate slowed significantly, in the second half of the year, Beijing got a little nervous and they stepped on the credit accelerator, and the growth rate took off.