Presentation is loading. Please wait.

Presentation is loading. Please wait.

ING main colour palette 0 102 255 102 0 180 195 225 123 125 124 120 140 200 178 181 180 ING secondary colour palette 255 205 171 81 83 82 211 224 202 210.

Similar presentations


Presentation on theme: "ING main colour palette 0 102 255 102 0 180 195 225 123 125 124 120 140 200 178 181 180 ING secondary colour palette 255 205 171 81 83 82 211 224 202 210."— Presentation transcript:

1 ING main colour palette 0 102 255 102 0 180 195 225 123 125 124 120 140 200 178 181 180 ING secondary colour palette 255 205 171 81 83 82 211 224 202 210 212 211 200 220 240 162 189 144 Map colours 230 232 242 185 191 219 FillLine Charles Robertson Head of Research and Chief Economist, EEMEA 2009 charles.robertson@uk.ing.com +44 20 7767 5310 Directional Economics Emerging and Converging Markets Analysing the credit crunch

2 Page 1 Is this as bad as it gets? In every market sell-off, HY spreads reach 1100bp – we hit this level on 3 October 2008. It peaked at over 1,900bp in December – implying.. total default in the US? Or more accurately, a clear out of positions and no bid – the market barely existed. The real economy only recently began to exhibit real pain. Unemployment may not peak until 2010 with 9-11% looking a plausible range (10.8% in 1982). EM fundamentals are better than in the 1990s, but relative value trades mean EM spreads have widened and currencies may continue to face pressure. HY spreads over UST

3 Page 2 The 5 great crashes 1929-2009 Measured by working days from the peak

4 Page 3 ING global forecasts US, Eurozone, Japan – GDP %chUS Fed funds and ECB refi rate US Fed Funds vs Unemployment

5 Page 4 The World Economy – Nominal GDP in 2008 (2007 in grey and only 2007 for 21-40 th ) Political freedom ratings by Freedom House Emerging markets remain small players in the US$52tr 2008 global economy Russia is now a G-8 member, de facto and de jure China is now the 3 rd biggest economy in the world G-8 member Canada is 11 th between Brazil and India Poland is now in the top 20 All EUR-linked economies may look smaller in USD terms in 2009. In 2007, California was $1.8tr, Africa $1.28tr, Texas or New York at $1.1tr, Florida $0.75tr, Illinois $0.6tr.

6 Page 5 Total imports of merchandise goods Total imports of merchandise goods in 2008 – we need US and Eurozone demand

7 Page 6 Eurozone import growth boomed (for energy) But will collapse in 2009 due to currency effects Import growth (US$bn) – Global and emerging markets comparison In USD terms, trade value is on course to collapse. As recently as July 2008, the stronger euro meant that a good priced in euros was valued at 15% more US dollars than in July 2007. By September, it was worth about 1% less than a year before. In October 2008, it was 12% less than a year before. The US dollar value of total trade is about to shrink dramatically

8 Page 7 When German confidence collapsed in 3Q08 – so did the world economy Germany in 2007/1H08 – never better but Germany in late 2H08/1H09 – never worse ? Current conditions fell below the long-term average in Nov-08 (94.8) having been an incredibly strong 108.3 as recently as June. In Dec-08 they were 88.8. Expectations (76.8, Dec-08) are the lowest since German re-unification. This is negative for global exports, central European investment and isn’t great for Germany either.

9 Page 8 Who does China need? China’s main export markets in 2007Chinese exports and exports growth Exports rose 30% to the EU in 2007, pushing the US into second place. While Chinese exports are booming to Russia (+80%) and India (+70%), the absolute amount of exports remains small.

10 Page 9 China’s growth – more export-dependent China lending data China’s growth was investment-led until 2004- 05. Banks injected the equivalent of up to 20% of GDP, to produce annual economic growth of roughly 10%. This resulted in booming exports, but also booming imports to feed the investment and export story. Since 2004, China’s trade surplus has exploded from US$50bn to over US$250bn now, helping drive economic growth. Meanwhile, China has become ever more export-sensitive. Exports to GDP has nearly doubled from 18% in 1998 to 20% in 2001 to around 35% in 2006-07. Low ratios in 1998-2001 help explain China’s escape from the worst of the Asian crisis and the aftermath of the tech bubble in 2001. China trade

11 Page 10 Korean and Chinese trade data China's trade data Korean trade data Korea provides the most recent trade data of a major economy. Nov-Dec data were as terrible as the German IFO or oil prices suggested they would be. Worse still, Dec- 09 data were flattered by +3 working days. Jan 09 data could be -40% due to negative working day effects. China’s exports have now begun their decline. Worse still for the world economy, import value is collapsing, down roughly 20% YoY in Nov-Dec 08. CNY depreciation is plausible to support jobs in China (at the expense of jobs elsewhere in EM).

12 Page 11 Exports in 2001 – a rapid decline Exports % ch in 2000-01 US imports fell by roughly 5% in 2001. A fall in US demand and a Eurozone slowdown meant many countries saw exports decline sharply after strong growth in 2000. Today it is clear that after a strong 1H in 2008, the outlook has dramatically worsened in late 2008 and into 2009.

13 Page 12 What happened in the last recession Falling DownMisery and Happiness Deep impactApocalypse Now

14 Page 13 What happened in the last recession Shallow HalUnbreakable In 2000-02, the CIS was coming up from the very low base of 1998. Today the base has been much higher, so the downturn will be more severe. In central Europe, Hungary spent heavily ahead of 2002 elections, widened the fx bands and cut interest rates despite high inflation. Hungary will not outperform this time. Poland had 19% interest rates but much lower now. Exports/GDP are just 33% vs 68% in Hungary and the Czech Republic. Czech and Polish loan to deposit ratios are better than most, so banks might be able to support growth. Bulgaria and Romania were still recovery from the crises of 1996/97 and 1999 respectively, so were rising from a low base. This is not the same story today.

15 Page 14 The experience in previous recessions The mid-70s saw a coordinated recession in developed markets with little impact on EM. Slow years saw Turkey at 3%, Mexico at 4% and Brazil at 4% or Korea at 5%. The early 1990s was the most prolonged series of recessions, and came during political crises in China and the former Soviet bloc. It hid Brazil hard at -4%, Mexico 1%, China 4%, Turkey 1%. The early 1980s were the world’s worst recession and came after an EM boom and as oil prices fell significantly. EM was hit hard and dramatically. Brazil went from +9% to -5%, Korea from +7% to -2%, Turkey had two years of recession and China slowed to 5%. Poland had its own crisis.

16 Page 15 What happens now to oil Oil: demand destruction and price US oil demand is down 5-6%. This is roughly between the 1.7% fall in 1979 and the 7.5% decline in 1980. World demand, given the German current IFO conditions and Chinese/Korean export growth would appear to be in positive territory, similar to 1979. Oil began falling in mid- 1980. It appears the oil markets have priced in prospective price declines before 1980 levels of demand destruction as the market is more liquid and developed than in 1980. Note that based on 2007 oil prices, the rise and prospective fall of oil prices could be very similar to the 1970-1980s period. Oil price now vs 1970s

17 Page 16 Food – how neither China nor India play a big role Meat trade (000m tonnes) BEEF PORKPOULTRY ImportersExportersImportersExportersImportersExporters US1,471 Brazil2,400Japan1,200 US1,373Russia1,245Brazil3,068 Russia1,050 Australia1,450Russia855 EU1,270Japan675US2,732 EU725 Other Asia824US456 Canada1,040EU655EU810 Japan715 US650South Korea450 Brazil715Mexico612China353 Mexico400 Argentina525Mexico435 China440China513Thailand315 South Korea315 New Zealand515HK293 Mexico70Saudi Arabia440 Egypt250 Canada480Canada160Other N Africa, M East397 Canada225 EU175China130Cent America/Carib310 Philippines160Hong Kong233 Taiwan105Canada150 Note: italics indicates major exporter and importer Source: USDA Per capita meat consumption (kg annually) BeefPoultryPorkTotal United States434629118 Hong Kong163960115 Argentina6428N/A Brazil37361285 European Union18164276 Mexico23281566 China683953 Russia16171851 Japan9151944 South Korea10112951 India22N/A Source: USDA

18 Page 17 Trade ties – Latam for China, EEMEA for Eurozone Trade ties reveal the potential origin of FX threat (2006 data unless otherwise stated) Exports/ GDP (%) US (%) EU (%) (-27 if 2007) Other significantMain exports Argentina (2007)21717Brazil 19%, China 9%, Chile 7%, Mexico 3%, Vene 2%Agricultural 52%, mineral (eg oil) 14%, transport 10%, metals 5% Brazil131822Mercosur 10%, Other Latam 12%, Asia 15%Transport 15%, metallurgy 11%, soy beans 7%, oil/fuel 10%, ores 7%, meats 6% Chile411727Japan 12%, China 10%, S Korea 7%, Mercosur 7%Copper 58%, other mined ores 8%, food 9%, industrials 25% Colombia174014Venezuela 11%, Ecuador 5%, Peru 3%Petrol/derivatives 26%, coal 12%, coffee 6%, ferro-nickel 5% Mexico (2007)30836South America 4%Electrical machinery 24%, oil/other mining 17%, Vehicles 17%, machinery 12% Peru2624>9%China 9%, Switz 7%, Canada 7%, Chile 6%, Japan 5%Copper 25%, gold 17%, other mineral prod 20%, fish 6%, textiles 6% Uruguay212217Brazil 14%, Argentina 8%, Mexico 4%, China 4%Frozen meat 17%, leather/skin 8%, dairy products 8%, textile 7%, rice 6% Venezuela405910<Colombia 5%, Mexico 5%Mineral products 64%, metals 20% Bulgaria (2007)47261Turkey 12%, Serbia 5%Iron/steel + other metals 20%, petroleum products 13%, clothing & footwear 11% Croatia (2007)24360Bosnia and Herzegovina 14%, Asia 5%Mach & transport equip 31%, mineral fuels 13%, chemicals 9%, food 8% Czech Rep (2007)68285Russia 2%, Switz 1%, Ukraine 1%, China 1%,Mach & elec equip 36%, road vehicles 17%, iron/steel + other 10% Estonia (2007)52467Russia 9%, Norway 3%, Togo 3%Machinery 21%, mineral prod 12%, wood 10%, metals 10% Hungary (2007 data)68279Russia 3%, Ukraine 2%, Turkey 2%, China 1%Manufactured goods 27%, machinery 21%, telecoms 18%, vehicles 12%, Kazakhstan (2007)46158Switzerland 16%, China 12%, Russia 10%Mineral products 50%, fuels 36.5% Latvia30273Russia 9%, Belarus 2%, Other CIS 3%, Norw 2%Wood 24%, base metals 15%, food & ag 13%, mach 10% Lithuania (2007)45363Russia 15%, Belarus 4%, Other CIS 5%, Norway 2%Mineral products 14%, machinery 13%, transport equip 11%, food/agric 11% Poland (2007)34279Russia 5%, Ukraine 4%Transport equip 17%, machinery 23%, metals 12%, food 9% (2006 data) Romania (2007)24272Turkey 7%Machinery 22%, metals 16%, textiles 13%, transport equip 12% Russia (2007)28253Turkey 5%, Belarus 5%, Ukraine 5%, China 5%,Mineral prod 64%, metals 16%, machinery 6%, chemicals 6% Serbia (2007)16156Bosnia-Herz 12%, Montenegro 11%, Russia 5%Iron/steel + other metals 20%, food 15%, machinery 14%, chemicals 10% Slovakia (2007)77284Russia 2% Ukraine 1%, Turkey 1%Machinery/elec equip 30%, vehicles 25%, base metals 14% Turkey (2007 data)18356Russia 4%, Iran 3%, Oman 3%, Palestine 2%Textiles/clothes 21%, motor vehicles 16%, iron/steel 12%, agric/food 8% Ukraine (2007)35228Russia 25%, Other CIS 12%, Turkey 7%, Egypt 2%Base metals 42%, mach/eq 10%, minerals 9%, chemicals 8%, vehicles 7% Egypt (2007)2232 Asia 14%, Arab countries 12%Fuel products 52%, finished goods 31% of which iron 2% and clothes 3% Israel (2007)333530Hong Kong 6%, India 2%Rough diamonds 34%, chemicals 18%, pharma 7% Nigeria (2005 data)433822India 10%, Brazil 7%, Japan 4.0%Fuel and mining products 90% South Africa (2007)231130Japan 10%, China 6%, Switz 2% (Zimb 2% in 2006)Precious metals 27%, base metals 18%, mineral products 16%, machinery 11% China (2007)351921Hong Kong 15%, Japan 8%, South Korea 5%Mechanical & electrical products 57%, hi-tech products 29%, clothing 11% Hong Kong (2007)9 or 1672215-20estChina 37%, Taiwan 4%, Japan 3%, Australia 2%Apparel 39%, electrical mach 10%, jewellery 6%, textile yarn 2% India (2006-07)131517UAE 10%, China 7%, Singapore 5%Pearls 13%, mineral fuels 15%, iron/steel 4% Indonesia281112Japan 22%, Singapore 9%Gas 10.1%, crude petroleum 8%, textiles 9%, coal 6%, copper 5%, rubber 5% Malaysia1031913Singapore 15%, Japan 9%, China 7%, Hong Kong 5%Electronic equip24%, semi-conductors 18%, electrical prod 7%, chemicals 6% Pakistan122322UAE 7%, Afghanistan 5%, HK 5%, Saudi Arabia 2%Clothing/apparel 34%, cotton 21%, rice 7%, leather 4%, petroleum products 2% Philippines405918Japan 17%, China 10%, HK 8%, Singapore 7%Electronic products 63%, clothing/apparel 6%, cathodes 3% Singapore1721011Malaysia 13%, HK 10%, China 10%, Indonesia 9%,Oil 26%, electrical machinery 21%, office machinery 13%, chemicals 17% South Korea371315China 21%, Japan 8%, Hong Kong 6%Elec mach 15%, telecom 12%, vehicle 13%, other transport 7%, petroleum 6% Thailand (2007)611514Japan 12%, China 10%, Singapore 7%Machinery 46%, manufactured goods 13% Vietnam6420 Japan 14%, China 9%, Australia 7%Textiles 24%, crude oil 21%, seafood 8%, electronics 5%, wood products 5% Source: ING, IMF, National sources (central banks and statistical offices)

19 ING main colour palette 0 102 255 102 0 180 195 225 123 125 124 120 140 200 178 181 180 ING secondary colour palette 255 205 171 81 83 82 211 224 202 210 212 211 200 220 240 162 189 144 Map colours 230 232 242 185 191 219 FillLine Credit and the crunch

20 Page 19 The credit crunch – private sector debt Lending/GDP – households and corporates (2007) High credit levels in rich and Asian countries Latam and CIS countries have low credit levels Emerging European credit is heading towards Eurozone levels

21 Page 20 The credit crunch – total debt in the economy Private and public sector debt/GDP (2007)

22 Page 21 The US credit boom – Greenspan 1987-2006 The rise in GDP and the change in credit each year as a % of GDP

23 Page 22 Bank lending – credit and GDP growth China lending dataIndia lending data Russia lending dataIceland lending data

24 Page 23 Bank lending – credit and GDP growth Hungary lending dataPoland lending data Bulgaria lending dataRomania lending data

25 Page 24 The credit crunch – Asia in the 1990s Credit rose too fast in south-east Asia in the 1990s. Credit from 1991-97 jumped by 80pp of GDP in Malaysia and Thailand. The collapse in 1997 quickly spread to Malaysia and eventually even South Korea and Indonesia where credit growth was just 10-30pp of GDP, vs 80pp in Thailand and Malaysia. India did not get impacted as credit had not risen, nor did China where credit growth was domestically financed. Change in credit stock 1991-97 in key Asian countries

26 Page 25 EMEA credit growth was very high Though some developed markets were higher Credit growth: Developed marketsCredit growth: EMEA Ireland even beat Iceland in terms of credit growth, with Spain not far behind and equal to Thailand in the 1990s. Germany, Japan, Italy and Austria seem to have been restrained. Most EMs saw high growth, but the Baltics, Bulgaria, Kazakhstan and Ukraine rose most. Egypt, Czech Republic, Poland and Turkey seem to have been more restrained.

27 Page 26 Asia and Latin America were restrained So will be hit mainly by the global slowdown, not directly by a credit crunch Credit growth: Asia 2001-07Credit growth: Latam 2001-07 In Asia, only Vietnam saw very high credit growth in the 1990s. The rest of Asia has learnt lessons from the 1990s. In Latin America, credit only began to rise after 2004, and only took off in 2007. This was too late to reach extremely high levels.

28 Page 27 What happens when credit stops rising so fast Latvia: monthly credit and real %ch YoYLatvia: stock of outstanding credit Even when total credit is rising, an economy can go into recession. While new monthly credit extension in Latvia was still around LVL130m each month in 3Q08, GDP was already negative. It is the rate of change in credit that is crucial.

29 Page 28 What happens when credit stops rising so fast This graph shows the amount of credit extended each month as a percentage of the peak month, tracked against GDP. Growth disappears when monthly credit is 60% lower than the peak month. When the figure is -100%, it means the debt stock is declining. Late 2008 saw a dramatic fall in credit growth in every country – the Baltic decline was slow by comparison Latvia and Estonia credit and GDP growth

30 Page 29 The sudden collapse in credit growth The Latvian/Estonian experience was a long drawn out collapse in credit compared to what is happening today. With a few rare exceptions, like Poland, credit has begun contracting and very fast. It has taken just 5 months for Bulgaria to see a collapse in credit growth that took Estonia 17 months over 2007-08. Bulgaria vs Estonia – credit extensionRomanian GDP set to fall

31 Page 30 What happens when credit stops rising so fast The Latvian/Estonian experience implies that Kazakhstan could have negative GDP data by early 2009, Lithuania by 2Q09, and even central Europe by 2010 though a global recovery would offset that. Note oil and agriculture may have distorted 3Q08 GDP data. More worrying is that credit growth slowdowns have become more dramatic in recent months so the descent into recession will be quicker. The caveat is that credit is half as important in Russia or Romania when compared to Latvia/Estonia, so the impact may be less. Big falls in credit growth will hit economies with high stock of debt the most. Bulgaria, Lithuania and Kazakhstan may suffer more than Romania or Russia for example. Months since credit peak vs GDP growthCredit to GDP and depth of decline

32 ING main colour palette 0 102 255 102 0 180 195 225 123 125 124 120 140 200 178 181 180 ING secondary colour palette 255 205 171 81 83 82 211 224 202 210 212 211 200 220 240 162 189 144 Map colours 230 232 242 185 191 219 FillLine Credit crisis Financing and other risks

33 Page 32 The external debt trigger 100% usually a threshold for a crisis External debt due to foreign banks within 12 months as % of fx reserves (excl gold) 4Q074Q064Q054Q044Q034Q024Q014Q004Q994Q984Q974Q964Q954Q944Q934Q924Q914Q90 Argentina4929264285126194154134137154139152133114144167154 Brazil3443504455619010399939673656897111262298 Ecuador7812672101 124909366138988286102114185169194 Mexico4234283246 5963739293138154528104121130183 China87777791112212325313469722630 HK67645653 44556576104181268376430409 480534 India292524201691424262831354337437188269 Indonesia535253463843627172104212188201175167164163180 Korea563525 293130344757289198166157145156174138 Malaysia2224222319202625 366941332627242721 Philippines42456460614649505793163776453507199347 Thailand12172219201932 4283147121 10687787466 Bulgaria555742292018111413153520746706605201586NA Czech514137222123404441605638282724NA Croatia1371061227874654258454856342313160NA Estonia17721324222316020414711014142 134220NA Hungary11283788576655147446146472641315068240 Latvia175216176919962434628238551NA Lithuania77891017252475758502815206610NA Poland433639323842392825221814 2892899673 Romania13814452423533434976533355763558504044 Slovakia665138242219443556876938221918NA Russia2117262333 4544129226251235142432142NA Kazakhstan84577738474845283234211920172NA Ukraine54362216141522313971451918401330NA Georgia19121325242040482823916 NA Egypt4035282226283132272315141516 2255111 Israel17 221917131613141827 25333034 South Africa546240721361491601822122842921157369513643743667683 Turkey83717482565510011791107877072102182128139128 Iceland1705589833355378600635531430375223187241202141157135138 US3413193315921027842806975938764000000000 New Zealand14610214119618213117813514417914583968712615515784 Bold is crisis year. Shading indicates a number >=100%. Source: JEDH

34 Page 33 Which EM countries are at risk? Short-term debt as a ratio of reserves, June 2008 high=worrying low=reassuring Emerging markets don’t take the fx risks that they used to. Short-term debt is below the 100% threshold that has often coincided with a crisis. Where it is above 100%, it is often foreign-owned banks that owe money to foreign parent banks, so risk is lower.

35 Page 34 Emerging markets safer than some developed markets The great EM disasters of the 1990s were usually the consequence of poor policy choices by EM governments, with the crisis occurring when foreign financing for these bad policies disappeared. The triggers came when: 1) Governments could no longer borrow money (Russia 1998, Argentina 2001). 2) Foreign banks would not roll over private sector external debt (Korea 1997, Mexico 1994, Brazil 2002). 3) The current account position made them vulnerable (Turkey 2001, Mexico 1994, Thailand 1997). Now governments do not borrow money – or not much. Short-term external borrowing is low. The current account + FDI picture is much improved. Gross external debt (to BIS banks and for int’l debt securities) due in 12 months + 2008 FDI + C/A, all as % of fx reserves in Jun 2008, with forecasts for 2009 The chart shows the total of the external debt due within 12 months + the C/A + FDI, as a ratio of fx reserves. Ie, it would take Turkey 10 months to run out of reserves if they could not roll over any debt. But it would take Iceland less than 3 weeks (Iceland is off the scale of our chart). Russian reserves would grow!

36 Page 35 EM loan-to-deposit ratios Loan-to-deposit ratios (Jun-08 or Sep-08)

37 Page 36 (Lack of) foreign ownership helps predict a crisis Foreign bank ownership vs Loan/deposit ratio

38 Page 37 The absurd case scenario If all deposits leave the system Short-term ext debt as % of fx reserves Bank deposits as % of fx reserves The absurd case scenario (US$bn) RussiaKazakhstanUkraine*TurkeyRomaniaHungarySouth Africa 20082009200820092008200920082009200820092008200920082009 All converted at this fx rate28.01207.251.693.0221310.3 All lcl currency deposits of the banking system -278-24-32-161-31-38-195 As of6/08 9/08 6/08 C/A position (US$bn)94-346-10-14-7-52-38-28-14-10-6-21-20.4 FDI (US$bn)121344851591464486 12-mth external debt due to BIS banks (Jun-08) -100 -11 -18 -55 -38 -28 -14 International debt securities and IMF payments due within 12 months (Jun-08) -3 0-2 -3 -3 -2 Total excluding deposits issue 2-124-2-19-26-22-96-87-53-47-37-33-29-30 Total-276-26-58-257-84-74-224 Much of the debt owed by Hungary and Romania will be inter-company loans Reserves396483870352333 Incl Welfare and Stabilisation fund Incl National Fund Add 16.4 from IMF Add 15.7 from IMF+ 9 from EU and WB * Note non-time deposits are only US$6bn Source: JEDH, ING, Bloomberg, Reuters

39 Page 38 Credit crunch – bank ownership vs sovereign risk RussiaKazakhCzechSlovakUkraineSth AfrPolandLithBulgTurkeyHungRomLatviaEstoniaIceland Loans to deposits (Jun 2008)14916476NA*1611119317011684122134154187NA* Foreign bank ownership (2006/07) 378969737.5NA6791822685886997NA* Sovereign risk (2007)V low Med High V high Loan to deposit riskV high V lowNAV highMedLowV highMedLowM/highHighV high Lack of "parent" riskHighV highV low High Med.V lowLowHighLow MedV lowV high AverageMedHighLow HighMed High V high While sovereign risk may be low, banks may be more vulnerable if they have borrowed significantly abroad (eg common in the former Soviet Union). However, if they have borrowed from parent banks abroad (eg the Baltics), then this is less problematic. Then the greater risk is recession rather than devaluation. The table below also highlights the sovereign risk as seen in short-term external debt figures relative to fx reserves. The data imply the Czech banking system is the most secure, while Ukraine, Latvia, Estonia and Kazakhstan are most at risk, though none are so risky as Iceland. Risk ranking

40 Page 39 Conclusions on credit Since 2000, many Emerging European countries have dramatically increased their borrowing as a percentage of GDP – those that borrowed most are now facing recession. The greatest concerns have all been connected to locally owned banks, OTP in Hungary (unjustified though that seemed to be), Parex bank in Latvia, Prominvestbank in Ukraine and nearly all the Kazakh banks. And Iceland of course. Only Turkey still looks vulnerable on this measure. High loan to deposit ratios is a negative for all countries except Poland, Turkey and best of all, the Czech Republic. Others will have to raise deposit rates and cut back on lending. This is an acute need in Russia, but also Romania, Ukraine etc. Recession can still be very deep even while credit growth is still rising in real terms. Lastly – connected to apparently low sovereign risk – note that economists can be particularly bad at forecasting an end to currency regimes. Most investment bank reports as late as 4Q1994 predicted Mexico would not be forced to devalue!

41 ING main colour palette 0 102 255 102 0 180 195 225 123 125 124 120 140 200 178 181 180 ING secondary colour palette 255 205 171 81 83 82 211 224 202 210 212 211 200 220 240 162 189 144 Map colours 230 232 242 185 191 219 FillLine Currencies The demise of the carry trade

42 Page 41 The US dollar long-term fair value is 1.10-1.20 based on REER EUR/USD long-term fair value – using the real effective exchange rate

43 Page 42 ING PPP (November 2008) ING PPP baskets purchased per EUR100 This is a long-run indicator and much like The Economist’s Big Mac index. It is not a real effective exchange rate index which is often flawed by its starting point. Our index tells us how much 23 goods cost in these countries.

44 Page 43 ING PPP vs per capita GDP 2008 Low per capita income countries NEED a currency that goes a long way Given that India’s per capita GDP is roughly US$1,000, a hundred euros needs to buy a lot of goods in Mumbai. Given how much richer Mexico is, this is not necessary. When combined with the balance of payments and interest rates, this suggests the rupee may still be expensive at 50/USD while the MXN is extremely undervalued at 13.5/USD. Sell KZT and RON (to 4.2-4.5), hold HUF at 260/EUR and buy PLN and CZK.

45 Page 44 EM currencies now at average level of 2004-08 EM currencies have not “overshot” on the weakening side The global liquidity surge of 2004-07 drove EM fx to artificially strong levels. After weakening in late 2008, it may not appreciate again, especially when yields on sovereign debt (and other assets) are now so high. Why appreciate in risky local market assets when such high yields are available closer to home or in in hard currency EM assets.

46 Page 45 Carry trade – fx levels ING3Pi – implied exchange rates Implied ING3Pi rate/€Implied ING3Pi rate/US$ Exchange rate vs €* Regional avg as benchmarkEM as benchmark Spain as benchmark Exchange rate vs US$* Regional avg as benchmarkEM as benchmark US as benchmark (lc/€) (lc/US$) Emerging Europe Bulgaria1.961.691.891.331.531.321.481.01 Czech Republic24.026.329.420.818.920.723.115.8 Hungary256261292206201205229157 Kazakhstan153206231163120162181124 Poland3.533.063.432.422.772.412.691.84 Romania3.754.054.523.202.943.173.552.43 Russia34.538.743.330.627.130.434.023.2 Slovakia30.433.437.426.423.926.329.420.1 South Africa12.669.7410.907.709.777.528.415.75 Turkey1.972.362.641.861.521.832.041.40 Ukraine7.406.216.954.915.864.915.493.76 Latin America Argentina4.375.164.713.333.373.983.642.49 Brazil2.763.182.902.052.122.442.231.52 Chile870838765540670645589403 Mexico16.3213.0811.938.4312.8310.279.386.41 Asia China8.718.348.255.836.846.556.484.43 Hong Kong9.913.713.69.67.7510.810.77.30 India63.051.250.735.849.540.239.827.2 Philippines62.962.461.843.748.748.347.832.7 * Exchange rate on day local offices priced up the basket. Source: National sources, Reuters, ING

47 Page 46 Central European currencies Within central Europe, the cheapest place to go shopping (among freely floated currencies) last November was Poland where we could buy 15% more than in Hungary. Prices were equally high in Romania, Slovakia and the Czech Republic, though affordability was quite different. This implies the RON should have weakened and the PLN strengthened against their partners.

48 Page 47 EU and Euro entry dates Key EU and earliest possible euro adoption dates Entry applications Negotiations begun EU entry ERM membershipEuro adoptionCurrencyRegimeCentral parity rate EU MEMBERS (since 1960) and those that have completed negotiations Ireland1961/67/721973Mar-791999EuroN/A Denmark1961/67/711973Mar-792011-12+KronerERM peg to euro with 2.25% bands7.46 UK1961/67/711973(10/90-9/92)UnlikelyPoundFree-float Greece197519761981Mar-982001EuroN/A Spain197719791986Jun-891999EuroN/A Portugal197719781986Apr-921999EuroN/A Austria198919931995Jan-951999EuroN/A Finland199219931995Oct-961999EuroN/A Sweden1991199319952009+2012+KronaFree-float Slovenia199619982004Jun-042007EuroEntered at 239.6 Cyprus199019982004Apr-052008EuroEntered at 0.585 Malta1990/9820002004Apr-052008EuroEntered at 0.429 Slovakia199520002004Nov-052009EuroEntered at 30.126 Lithuania199520002004Jun-042012+LitasERM currency board to euro3.45 Estonia199519982004Jun-042012+KroonERM currency board to euro15.65 Latvia199520002004Apr-052012+LatERM peg to euro 1% bands0.703 Czech Republic1996199820042010/11+2014+KorunaFree-float Poland19941998200420092012+ZlotyFree-float Hungary1994199820042009/10+2013+ForintFree-float282 Bulgaria1995200020072010+2012+LevCurrency board to euro1.96 Romania1995200020072012+2015+LeuManaged float vs euro IN NEGOTIATIONS Croatia200320052011+ 2014+KunaManaged float vs euro Turkey19872005No (2015+) No (2018+)LiraFree-float NOT IN NEGOTIATIONS Albania2010+2012+2017+ 2020+LekManaged float vs euro Macedonia20042010+2015+ 2018+DenarTightly managed float vs euro Bosnia2010+2012+2017+ 2020+MarkaCurrency board to euro1.96 Serbia2009+2010+2015+ 2018+DinarDirty free-float with euro reference Montenegro2010+ 2015+ 2018+EuroDeutschemark (now euro) adopted as only legal tender in Nov-00 Ukraine2012+2015+2020+ 2025+HryvniaManaged float vs US$ Source: European Commission, ING forecasts

49 Page 48 Conclusions We are seeing the most dramatic worsening of economic data in our working careers. We are faced with a financial crisis at least as bad as 1974-75 and potentially a global recession as bad as 1980-82. A more negative scenario is likely if China implodes in 2009. Our base case is global monetary and fiscal stimuli will keep the recession centred on 4Q08 and 1H09, with recovery as we head into 2010. There are many risks to this scenario. Emerging European GDP in 2009 may range from a -5% fall in Latvia to -4.5% in Ukraine, -3.5% in Romania, -2.5% in Hungary, to stagnation or small falls (up to -2%) in Russia, Kazakhstan, Czech Republic and potentially 2% growth in Poland. Recession is plausible in Bulgaria and Lithuania by late 2009 due to slowing credit growth. Political risk is likely to grow across the whole emerging market universe. Local interest rates on deposits need to rise fastest in countries with poor loan to deposit ratios, particularly in the CIS, Baltics, Romania and to a lesser extent Hungary. Currencies have sold off and are now at a 2004-08 average relative to the US or Eurozone. Further weakness is possible – and is probable if China implodes. The best value is in the PLN, MXN and the UAH (but only in the long-term). The worst value is in the KZT, with depreciation very justified in Romania and Argentina. We see Russia’s band widening as echoing the fx depreciation in all commodity currencies. Inflation targeting may be well be adopted as a formal policy in 2010, with a full free float. Yields in developed markets are now so high, that these may benefit first from any market recovery in early 2009, followed by hard currency bonds. Local currency debt is very unlikely to attract the volumes of 2006- 07. A poor harvest in 2009 could hurt local debt as we go into 2010. Equity markets may begin to recover later in 2009, pricing in a recovery well before unemployment has peaked in 2010.

50 Page 49 ING Emerging Markets Research Contacts LondonCharles RobertsonHead of Research & Chief Economist, EMEA(44 20) 7767 5310charles.robertson@uk.ing.com Agata UrbańskaSenior Economist, Emerging Europe(44 20) 7767 6970agata.urbanska@uk.ing.com Dorothée Gasser-ChâteauvieuxSenior Economist, Middle East and Africa(44 20) 7767 6023dorothee.gasser@uk.ing.com Courtney RueschResearch Assistant, Baltics(44 20) 7767 5567courtney.ruesch@uk.ing.com BratislavaJan TothChief Economist, Slovakia(421 2) 5934 6381jan.toth@ing.sk Eduard HagaraEconomist, Slovakia(421 2) 5934 6392eduard.hagara@ing.sk BucharestNicolaie Alexandru-ChidesciucSenior Economist, Romania(40 21) 209 1294nicolaie.alexandru@ingromania.ro Vlad MuscaluEconomist, Romania(40 21) 209 1393vlad.muscalu@ingromania.ro BudapestDavid NemethSenior Economist, Hungary(36 1) 255 5581nemeth.david@ing.hu Balazs CsontoEconomist, Hungary(36 1) 255 5597csonto.balazs@ing.hu IstanbulSengül DağdevirenHead of Research & Chief Economist, Turkey(90 212) 329 0752sengul.dagdeviren@ingbank.com.tr Pınar UsluSenior Economist, Turkey(90 212) 329 0751pinar.uslu@ingbank.com.tr KievAlexander PecherytsynHead of Research, Ukraine(38 044) 230 3017alexander.pecherytsyn@ingbank.com Daria VolchenkoResearch Analyst(38 044) 590 3587daria.volchenko@ingbank.com Mexico CitySalvador MorenoChief Economist, Latin America(52 55) 5258 2199salvador.moreno@americas.ing.com Debora LunaEconomist, Mexico(52 55) 5258 2057debora.luna@americas.ing.com Felipe HernandezEconomist, Colombia and Peru(52 55) 5258 2144felipe.hernandez@americas.ing.com MoscowStanislav PonomarenkoHead of Research, Russia(7 495) 755 5480stanislav.ponomarenko@ingbank.com Tatiana OrlovaEconomist, Russia, Kazakhstan, Other CIS(7 495) 755 5489tatiana.orlova@ingbank.com ManilaJoey CuyegkengEconomist, Philippines(632) 479 8855joey.cuyegkeng@asia.ing.com New YorkH David SpegelGlobal Head of Emerging Markets Strategy(1 646) 424 6464david.spegel@americas.ing.com WR Eric OllomHead of Corporate Debt Research (LatAm)(1 646) 424 7913william.ollom@americas.ing.com Diego TorresCorporate Debt Analyst(1 646) 424 7247diego.torres@americas.ing.com PragueVojtech BendaSenior Economist, Czech Republic(420 2) 5747 4432vojtech.benda@ing.cz Sao PauloZeina Abdel LatifChief Economist, Brazil(55 11) 4504 6131zeina.latif@americas.ing.com SingaporeTim CondonHead of Research & Chief Economist, Asia(65) 6232 6020tim.condon@asia.ing.com Prakash SakpalEconomist, Asia(65) 6232 6181prakashb.sakpal@asia.ing.com WarsawMateusz SzczurekChief Economist, Poland(48 22) 820 4698mateusz.szczurek@ingbank.pl Rafal BeneckiSenior Economist, Poland(48 22) 820 4696rafal.benecki@ingbank.pl Grzegorz OgonekEconomist, Poland(48 22) 820 4608grzegorz.ogonek@ingbank.pl

51 Page 50

52 Page 51 Bank ownership BALKANS (1st, 2nd and 3rd EU Enlargement waves) Share of assets (%)Assets (EURbn) Bosnia2007200520072005 93.7% foreign, 2.0% state (2007)10.0125.999 Unicredit21252.11.5 Hypo Alpe-Adria (Mostar and Banja Luka)21192.11.2 Raiffeisen20212.01.3 NLB Group90.9 Volksbank60.6 Intesa (UPI banka)540.50.2 Croatia 90.4% foreign, 4.7% state (2007)47.07335.39 Unicredit (Zagrebacka)23.22410.98.6 Intesa (Privedna Banka Zagreb)17.8188.46.4 Erste (Erste and Steiermarkishche Banke)11.8125.64.1 Raiffeisen11.1115.23.9 Hypo Alpe-Adria (Slavonska banka and HAA)10.7105.03.6 Soc Gen (Splitska Banka)7.593.53.2 HPB4.22.0 OTP3.531.61.2 Bulgaria 82.3 foreign, 0.4% state (2007)30.21216.796 Unicredit (Bulbank, Hebros, Biochim)15214.63.5 OTP (DSK)13144.02.3 NBG (UBB)10 3.11.6 Raiffeisen1093.11.4 EFG Eurobank (Bulgarian Post Bank)752.20.9 First Investment Bank782.11.3 Piraeus Bank61.8 KBC (Investment Bank)31.0 Soc Gen (SG Expressbank)30.9 Share of assets (%)Assets (EURbn) Romania2007200520072005 87.9% foreign, 5.5% state (2007)72.043735.3569 Erste (BCR)242617.69 Soc Gen (BRD)15 10.85.2 Raiffeisen694.43 Banca Transilvania53.8 EFG Eurobank (Banc Post)543.71.6 Unicredit593.53.1 Alpha bank53.5 Volksbank53.5 CEC442.91.5 ING52.241.8 Slovenia 29.3% foreign (was 40% in 2006), 4.5% state - 200742.19528.508 KBC & State (Nova Ljubljanska banka)363115.39.2 Nova kreditna banka Maribor10 4.23 Abanka Vipa893.52.5 Nova Ljubljanska banka (Banca Celje)662.31.7 Soc Gen (SKB banka)572.32 IntesaSanPaolo (Banka Koper)562.21.8 Unicredit (Bank Austria Creditanstalt)562.21.9 Hypo Alpe Adria51.9 Serbia 75.5% foreign, 16.5% state (2007)21.110.7 Intesa12112.51 Raiffeisen9162.01.4 Komercijalna banka Beograd9101.90.9 Hypo Alpe-Adria (HAAB Beograd)891.70.8 EFG Eurobank51.1 AIK Bank51.0 Unicredito460.90.5 Soc Gen40.8 ProCredit40.8 NBG (Vojvodanska banka Novi Sad)450.80.5

53 Page 52 Bank ownership CE 4 (1st EU Enlargement wave) Share of assets (%)Assets (EURbn) Poland2007200520072005 66.9% foreign, 18.8% state (2007)233.793163.4 Unicredit (Bank Pekao - Bank BPH)152034.431 PKO BP131630.223.8 Commerzbank (BRE)7615.48.6 ING (Bank Slaski)6714.510.9 AIB (Bank Zachodni WBK)5511.57.7 Citigroup (Handlowy)5610.88.5 BCP (Bank Millenium)48.4 BGK37.7 KBC (Kredyt bank)37.5 Hungary 84.5% foreign (2007)107.70878.41 OTP231924.914.2 KBC (K&H)9109.37.5 Bayerische Landesbank (MKB)898.96.5 Intesa San Paolo (CIB)888.95.8 Raiffeisen878.25 Erste787.95.7 Unicredit (HVB)656.04 Share of assets (%)Assets (EURbn) Czech Republic2007200520072005 96.4% foreign, 3.0% state (2007)139.84100.5 Erste (Ceska Sporitelna)22 30.622.6 KBC (CSOB)212529.825.4 Soc Gen (Komercni)181725.017.8 Unicredit7710.17.4 Raiffeisenbank435.52.7 Citi44.9 GE Money2.3.2 Commerzbank243.13.6 Slovakia 97.4% foreign, 1.0% state49.380438.75 Erste (Slovenske Sporitelna)19189.16.8 Intesa San Paolo (VUB)17168.46 Raiffeisen (Tatra Banka)16137.84.9 KBC (CSOB)11135.24.8 Unicredito (HVB and UniBanka)894.13.4 ING572.62.8 Dexia42.2 OTP31.5 KBC (Istrobanka)31.2

54 Page 53 Bank ownership OTHER EMEA Share of assets (%)Assets (EURbn) Russia2007200520072005 2006, state owned 37.4%, foreign 12.1%) Sberbank2426137.373.7 Vneshtorgbank7640.518.4 Gazprom4421.412.4 Soc Gen (Rosbank and Societe Generale Vostok)3214.65.9 Bank of Moscow3214.16.5 Alfa2213.56.8 Rosselkhosbank212.9 Raiffeisen211.3 UniCredito210.1 Uralsib229.66.7 Ukraine Foreign 37.5%, state 8.0% (2007), state 12% inc Prominvestbank Privatbank9.4117.63.9 Raiffeisen (Aval)7.486.03.1Soc Gen was reportedly interested BNP Paribas (UkrSibbank)6.265.02.2Soc Gen was reportedly interested Unicredito (Ukrsotsbank)5.254.21.8Intesa close to finalising purchase (by 1q07? Oct 06), Russia's Alfa bank was interested Ukreximbank4.853.91.9State Prominvestbank4.463.62.3Taken over by Klyuev brothers Nov 08, roughly 75% sold to Russia’s VEB in Jan 09. Nadra3.532.81.2Taken over by Dmitry Firtash, 87% for US$600m says Izvestiya Nov 08 Oshchadbank3.242.61.4State OTP332.41.3Was Raiffeisenbank Alfa2.52.0 Finance and Credit Bank 20.00.8Possible take-over target Turkey(Jun-06) 26% foreign329.1 Ziraat141546.433.8State Is141545.935.1Isbank Pension fund AK131241.128.1Sabanci and Citigroup (20%), Franklin Templeton owns stake Garanti121038.723.4Dogus Group and GE (25.5%) YKB91030.323.840% owned by Koc, 40% by Unicredito, 19.8% free-float Vakif8725.216.9State 59%, employees 16%, 25% floated Halk7723.916.3State seeking buyer, up to US$6bn, sale by May 07 ? NBG (Finansbank)4412.58.6NBG owns 46% plus buying shares Dexia (Denizbank)329.35.375% ING (Oyakbank)227.75.3 HSBC27.5 TEB26.9BNP Paribas Fortis25.7BNP Paribas ?

55 Page 54 Democracy

56 Page 55 Democracy and GDP Regime change: the influence of per capita GDP 1985 PPP dollars Life expectancy of Chance of democracy dying (%)Chance of autocracy becoming democracy (%)2006 PPP dollars*** democracy based on average** Average yearIf incomes shrinking If incomes growingAverage yearIf incomes shrinking If incomes growing Under 1,0008 yrs12.5021.748.160.661.010.39Under 1,850 1,00017.5 years5.718.334.352.483.262.151,850 2,00026 years3.807.322.82.763.752.383,710 3,00030 years3.334.882.751.611.921.495,580 4,000Just 2% chance1.874.551.184.926.254.447,420 5,0000.8801.03*6.4110.535.089,330 6,0000.833.44*06.2540.0*011,180 7,000 or moreImmortal0003.3303.7*13,040 * Based on 1-3 examples (Argentina alone for democracies). ** Expected life in any state is the inverse of probability of transition away from that state. *** Based on 87% accumulated US CPI from the end of 1985 to the end of 2006. Source: “Modernization: Theories and facts", Adam Przeworski and Fernando Limongi, 1997 Politics has often been the trigger for significant economic change in the past – eg the oil shocks of 1973/74 and 1980-81 resulting from Middle Eastern political developments – or in emerging markets, the consequences of populist policies. Economic shocks can trigger political change – except in wealthy democracies which are immortal. Potential changes worth considering include China, Russia and the Middle East (again).

57 Page 56 Democracy danger levels Danger levels for regime change Per capita GDP (2006 PPP dollars) Freedom House rating in 2006 Spain270001 Israel262001.5 South Korea242001.5 Czech Republic216001 Hungary173001 Argentina150002 Poland141001 Autocracies 3.3% chance of dyingSaudi Arabia138006.5Not Free South Africa130002 Democracies 0.8% chance of dyingChile127001 Malaysia127004Partly Free Autocracies 6.3% chance of dyingRussia121005.5Not Free Autocracies 6.4% chance of dyingMexico106002.5 Democracies 0.9% chance of dyingBulgaria104001.5 Thailand91005.5Not Free Autocracies 4.9% chance of dyingKazakhstan91005.5Not Free Iran89006Not Free Turkey89003Partly Free Democracies 1.9% chance of dyingRomania (74th)*88002 Brazil86002 Dominican Republic80002 Algeria77005.5Not Free Ukraine76002.5 China76006.5Not Free Autocracies 1.6% chance of dyingAzerbaijan73005.5Not Free Democracies 3.3% chance of dyingVenezuela69004Partly Free Lebanon55004.5Partly Free Philippines50003 Democracies 3.8% chance of dyingSerbia44002.5 Autocracies 2.8%chance of dyingEgypt42005.5Not Free Indonesia38002.5 Georgia38003Partly Free Democracy only likely to last 18 yearsIndia37002.5 Autocracies 2.5% chance of dyingVietnam31006Not Free Pakistan26005.5Not Free Democracy only likely to last 8 yearsCote D'Ivoire16006.5Not Free Autocracies 0.7% chance of dyingNigeria (171st)*14004Partly Free *Rank out of 171 countries in the full survey. Source: Freedom House, Modernism and Liberalism, CIA Factbook

58 Page 57 Net oil importers and freedom Net oil importers (2005) thousand barrels, and Freedom Ratings (2006) Energy importers tend to be democracies. These are countries without natural wealth, so governments must impose taxes on their population, who then say “No taxation without representation”.

59 Page 58 Net oil exporters and freedom Oil exporters tend to be autocracies – there are only 6 full democracies of the 39 oil exporters cited by BP. Note energy exporters with large populations (eg Nigeria, Indonesia, Egypt) tend to be poorer and more corrupt than countries where the wealth effects are not so dispersed. Russia has defaulted to autocracy as higher oil prices have risen – allowing Putin to cut income taxes to just 13% for example. No taxes = no representation. Russia’s Freedom Ratings and oil prices Top 20 net oil exporters and political freedom Net exports (2005) (000 bpd) Freedom House rating (2006) Saudi Arabia91446.5Not Free Russian Federation67985.5Not Free Norway27561 Nigeria25804Partly Free Venezuela24544Partly Free Iran23916Not Free United Arab Emirates23745.5Not Free Kuwait23634Partly Free Iraq18206Not Free Mexico17812.5 Algeria17615.5Not Free Libya17027Not Free Angola12425.5Not Free Kazakhstan11565.5Not Free Qatar10005.5Not Free Canada8061 Oman7805.5Not Free Syria4696.5Not Free Yemen4265.5Partly Free Ecuador3933Partly Free Source: Freedom House, BP _

60 Page 59 Freedom and Corruption Political Freedom scores vs Corruption perceptions – 155 countries in total

61 Page 60 Orthodoxy in 3/5 of the EMBI Global after crises in the 1990s (2006 budget estimates) Mexico (1994-95) Turkey (1994, 1997, 2001) Brazil (1994, 1999, 2002) Russia (1998) Source: Instituto Federal Electoral Source: Election result, Jul-07 Source: Wikipedia (Justica Eleitoral) Source: Yury Levada Analytical Center, Feb-06 0% budget balance -1% budget deficit -3% budget deficit 8% budget surplus Orthodox Populist Orthodox Populist Orthodox Populist Orthodox Populist


Download ppt "ING main colour palette 0 102 255 102 0 180 195 225 123 125 124 120 140 200 178 181 180 ING secondary colour palette 255 205 171 81 83 82 211 224 202 210."

Similar presentations


Ads by Google