Rise of Cross-Asset Correlations

Transcription

1 Global Equty Dervatves & Delta One Strategy Rse of Cross-Asset Correlatons Asset Class Roadmap for Equty Investors Summary Cross-Asset Correlatons: Over the past ten years, cross-asset correlatons roughly doubled. Globalzaton of captal markets, and new rsk-management and alphaextracton technques have drven the secular ncrease of cross-asset correlatons. The recent cyclcal ncrease s a result of elevated macro volatlty. We beleve that understandng the fundamentals and techncals of cross-asset correlaton wll be an ncreasngly mportant task for nvestors. Currences: The ncreasng share of EM equtes, US and Japan debt, and the declnng share of US equtes n Global market captalzaton s an mportant drver of correlaton between currences and equtes. Rsk-on/off tradng, currency carry trades, and cross-asset arbtrage are further strengthenng ths correlaton. Interest Rates: Investors who decrease rsk exposure usually sell equtes to buy Treasury bonds. These rsk flows cause a postve rate/equty correlaton. Postve rate/equty correlaton and a breakdown of the so-called Fed Model occurred n 1997 when three successve crses caused global de-rskng and a flght to Treasures. Rsk of a correlaton reversal s posed by severe stagflaton or treasury/ equty contagon. Commodtes: Hstorcally, dversfcaton benefts resulted n sgnfcant nvestment nterest for commodtes. The tradtonally negatve correlaton to equtes reversed sharply n 008, as a result of deleverng and demand destructon. About 4 of current commodty/equty correlaton s a spllover from FX/equty correlaton. Despte dversfcaton benefts, commodtes are not mmune to tal events such as the one recently exhbted by slver. Credt: Wth current correlaton of ~8, credt, equtes, and equty volatlty are the most correlated assets. Correlaton of credt and equtes s logcal as both are prced based on the value and volatlty of company assets. In practce, correlaton s drven by captal structure arbtrage and hedgng of credt wth equty nstruments. Equtes: Due to the globalzaton of captal markets, cross-regonal equty correlaton rose steadly over the past 0 years. Recent hgh levels have dmnshed the benefts of cross-regonal dversfcaton. Macro volatlty s a more sgnfcant drver of sector and stock correlaton. Specfc rsk-management and alphaextracton trends mpactng correlaton were dscussed n our report: Why we have correlaton bubble. Alternatve Assets: Low correlaton between strateges and ablty to generate alpha make hedge funds an attractve asset class. Over the past ten years, hedge fund assets ncreased notably relatve to the sze of global equty markets. Dscplned rskmanagement technques and alpha extracton employed by hedge funds lkely contrbuted to the secular ncrease of correlatons. Hybrd Dervatve Trades: In ths secton we hghlght several trade deas that take advantage of current levels of cross-asset correlatons. Equty hedges contngent on nterest rates, currences, or commodtes can sgnfcantly reduce the cost of equty hedgng and be talored for specfc scenaros such as US stagflaton or a debt crss. Global Equty Dervatves & Delta One Strategy Marko Kolanovc AC (Global Head) [email protected] J.P. Morgan Securtes LLC Davde Slvestrn (EMEA) (44-0) [email protected] J.P. Morgan Securtes Ltd. Tony SK Lee (Asa Pacfc) (85) [email protected] J.P. Morgan Securtes (Asa Pacfc) Lmted Mchro Nato (Japan) (81-3) [email protected] JPMorgan Securtes Japan Co., Ltd. Equty Dervatves Strategy US Marko Kolanovc Adam Rudd Amyn Bharwan Kapl Dhngra Mn Moon EMEA Davde Slvestrn Bram Kaplan Peng Cheng Asa Ex-Japan Tony Lee Clara Law Sue Lee Japan Mchro Nato Hayato Ono [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] See page 6 for analyst certfcaton and mportant dsclosures, ncludng non-us analyst dsclosures. J.P. Morgan does and seeks to do busness wth companes covered n ts research reports. As a result, nvestors should be aware that the frm may have a conflct of nterest that could affect the objectvty of ths report. Investors should consder ths report as only a sngle factor n makng ther nvestment decson. In the Unted States, ths nformaton s avalable only to persons who have receved the proper opton rsk dsclosure documents. Please contact your J.P. Morgan representatve or vst

2 Table of Contents Drvers of Cross-Asset Correlatons...3 Rse of Cross-Asset Correlatons...3 Correlaton Rsk/Reward...4 Volatlty, Rsk Management, and Alpha as Drvers of Correlaton...4 Currences...7 Rsk On/Off and Global Currency Flows...7 Interest Rates...10 End of Fed Model and Use of US Treasures as Global Rsk-Free Asset...10 Commodtes...1 Slver Bullet for Asset Allocaton...1 Credt...15 Captal Structure Arbtraged...15 Equtes...17 Why We Have a Correlaton Bubble...17 Alternatve Assets...19 Hedge Funds and Correlaton...19 Hybrd Dervatve Trades...1 Implementng Cross-Asset Vews...1 Appendx: Smple Correlaton Model...4

3 Drvers of Cross-Asset Correlatons Rse of Cross-Asset Correlatons Correlaton measures the degree to whch prces of assets move together. Over the past decade, nvestors wtnessed a sgnfcant ncrease of correlaton between equtes as well as an ncrease of correlaton between other rsky assets such as credt, foregn exchange, nterest rates, and commodtes. 1 Hgh levels of correlaton usually pont to a common source of rsk for asset prces. In tmes of hgh macro uncertanty, the prces of equtes, rsky bonds, ol, gold, and emergng market currences are largely drven by changes n the macroeconomc outlook. In addton to a recent ncrease due to macro volatlty, cross-asset correlaton has been on a secular rse due to changes n market structure. Integraton of global economes, ncreased effcency and globalzaton of fnancal markets, and new rsk-management and alpha-extracton technques have all contrbuted to a rse n cross-asset correlaton levels. In ths report we dscuss trends n cross-asset correlatons and ther mpact on nvestors. Fgure 1 shows the average correlaton between 45 developed world and emergng market country equty benchmarks contaned n the MSCI All Country World Index. Over the past 0 years, the average correlaton between these country benchmarks roughly doubled. Ths secular ncrease of cross-regonal equty correlaton s a result of the ntegraton of global economes and captal markets. Lberalzaton of flows of goods between economes (free trade, outsourcng of labor), the rse of Emergng Markets (e.g., BRICS), and globalzaton of the fnancal ndustry (e.g., global banks and hedge funds) all contrbuted to the ncrease of cross-regonal correlatons. Whle the globalzaton of captal markets reduced dversfcaton and cross-market arbtrage opportuntes, the benefts of globalzaton are mmense the rapd growth of emergng economes has led to mproved economc well-beng for bllons. Smlar to cross-regonal equty correlaton, the correlaton between equtes, credt, foregn exchange, nterest rates, and commodtes all ncreased over the past two decades. Fgure shows the average levels of cross-asset correlatons for the tme perod, and compares them to the average correlaton levels over the past fve years. On average, correlatons between dfferent asset classes more than doubled. Each of these cross-asset correlatons wll be dscussed n the rest of the report. Fgure 1: Globalzaton Rse of Correlaton Between Equty Market Benchmarks for 45 Emergng and Developed Economes Average Correlaton Between 45 Equty Country Benchmarks Feb, 86 Mar, 89 Apr, 9 May, 95 Jun, 98 Jul, 01 Aug, 04 Sep, 07 Oct, 10 Fgure : Cross-Asset Correlaton Levels Increased for Equtes, Credt, Foregn Exchange, Interest Rates, and Commodtes Asset Class Correlaton Between * Past 5Y Change Equty DM Country Indces 31% 47% 17% Equty EM Country Indces 3% 45% 3% Equty DM and EM Indces 38% 74% 36% Equty Economc Sectors 57% 69% 1% Equty Indvdual Stocks 5% 41% 16% Credt Hgh Yeld and Equtes 46% 64% 19% Credt Hgh Yeld and VIX 37% 6 4% Foregn Exch. DM Currences and Equtes -1% 8% 9% Foregn Exch. EM Currences and Equtes 6% 4% 36% Interest Rates 10Y Rate and Equtes -38% 9% 67% Commodty All Commodtes 5% 5% 1% Commodty Commodtes and Equtes -5% 1% 17% Average 19% 45% 6% * For Credt All Currences vs. USD 1 For a detaled study of equty correlatons and ther drvers, please see our report: Why we have a correlaton bubble. 3

4 Correlaton Rsk/Reward A common lst of asset classes ncludes: equtes, credt, nterest rates, foregn exchange, commodtes, and alternatve assets. Asset class s generally defned as a group of securtes that exhbt smlar characterstcs, behave smlarly n the marketplace, and are subject to the same regulatons. In other words, the correlaton between assets plays an mportant role n the defnng of an asset class tself. In the early 1990s, correlaton between Emergng Market (EM) stocks and Developed Markets (DM) stocks was ~3 and the two sets of equtes were consdered separate asset classes. Over the past three years, EM/DM correlaton was ~8 and the two asset classes morphed nto one. Smlarly, the recent correlaton of Hgh Yeld credt spreads to equtes of ~75% s hgher than the current average correlaton between S&P 500 stocks of ~45%. Below we consder the mpact of cross-asset correlaton on the rsk and reward of mult-asset portfolos. The volatlty of a mult-asset portfolo ncreases wth the level of cross-asset correlaton and the volatlty of the assets n the portfolo. 3 Hence, the hgher the cross-asset correlaton, the hgher the portfolo volatlty. If the portfolo volatlty s reduced by lower cross-asset correlaton, nvestors can free up rsk captal that can be employed to generate addtonal returns. Consder a portfolo of the followng rsky assets: emergng and developed market stocks, hgh yeld bonds, commodtes, and currences. As shown n Fgure, these assets are hghly correlated. Over the past 15 years, the correlaton between these assets ncreased from ~ to ~45%, ncreasng by 5 correlaton ponts. Assumng an average annualzed asset volatlty equal to that of equtes (14.3% US equty volatlty snce 1871), ths ncrease of cross-asset correlaton would cause portfolo rsk to ncrease by more than a thrd (35% ncrease n rsk). Assumng that ted rsk captal could have been employed to generate the average return of equtes (8.9% annualzed total return for US equtes snce 1871), the mplct cost of ths cross-correlaton ncrease s estmated at 31 bass ponts per annum. 4 Fgure also shows a dramatc ncrease n equty/rates correlaton. An ncrease of equty/rate correlaton reduces the rsk of a portfolo of equtes and Treasury bonds. Consder a portfolo wth equal weghts nvested n equtes and US Treasury bonds. The ncrease of more than 60 ponts n rates/equty correlaton over the past 15 years reduced the rsk of an equty/treasury portfolo by a quarter. Assumng that the freed rsk captal could have been employed to generate the average return of equtes and treasures (6.8% annualzed total return snce 1871), the mplct beneft of the crosscorrelaton ncrease s an estmated at 180 bass ponts per annum. 5 In addton to the descrbed mpact on a mult-asset portfolo, cross-asset correlaton can have a sgnfcant mpact on equty-only portfolos. For nstance, the most recent FX and Ol prce movements have mpacted the performance of equtes. Equty nvestors can also trade cross-asset correlaton drectly through dervatve products such as rate/equty, FX/equty, or commodty/equty hybrd optons (descrbed n the last secton of ths report). We beleve that understandng the fundamentals and techncals of cross-asset correlaton wll be an ncreasngly mportant task for all portfolo managers. Volatlty, Rsk Management, and Alpha as Drvers of Correlaton In tmes of elevated macro uncertanly, nvestors and rsk managers look at equtes, rsky bonds, commodtes, and currences as sources of portfolo rsk. As portfolo rsk s adjusted up or down n a rsk-on/off tradng style, the prces of all rsky assets tend to move n sync. In ths rgd nvestment approach, any asset s vewed as havng an exposure or beta to the macro rsk and some asset-specfc alpha. Gven the level of macro rsk and the magntude of alpha avalable n the asset class, a rsk-on/off tradng approach determnes the market level of cross-asset correlatons. Investopeda webste. 3 For a more exact expresson, see the Appendx. 4 For a portfolo of Equtes, Hgh Yeld Bonds, Commodtes, and Currences, the portfolo s rsk ncreased 1.4% for each cross-asset correlaton pont ncrease. The equvalent performance opportunty cost was 1bps for each pont ncrease n cross-asset correlatons. 5 For a portfolo of Equtes and US Treasures, the portfolo s rsk decreases 0.5% for each pont ncrease n rates/equty correlaton. The equvalent performance beneft s 3bps per pont ncrease n equty/rate correlaton. 4

5 Ths relatonshp between cross-asset correlaton, macro volatlty, and avalablty of alpha n markets s summarzed n Fgure 3 (for a more formal explanaton, see the Appendx). Essentally, a hgh level of macro volatlty causes hgh crossasset correlaton. In addton, a lack of alpha also causes an ncrease of correlatons. Interestngly, n a hgh-alpha envronment spkes n macro volatlty have a muted mpact, whle n a low-alpha envronment macro volatlty can cause a dramatc spke n cross-asset correlaton. Fgure 4 shows theoretcal levels of cross-asset correlaton (vertcal axs) as a functon of alpha and macro volatlty. In order to have a large spke n cross-asset correlaton, not only s macro volatlty needed, but the level of alpha n the markets needs to be depleted. Fgure 3: Relatonshp Between Cross-Asset Correlaton, Macro Volatlty, and the Magntude of Alpha Opportuntes n the Market Fgure 4: Graphcal Representaton of the Relatonshp Between Cross-Asset Correlaton, Macro Volatlty, and Magntude of Alpha More VOLATILITY More Correlaton Less VOLATILITY Less Correlaton Less ALPHA More ALPHA More Correlaton Less Correlaton CORRELATION Less ALPHA Volatlty has greater mpact on Correlaton 65% 5 35% VOLATILITY 5% 5% 35% ALPHA % In the rest of ths report, we explan the fundamentals of cross-asset correlaton between currences, rates, commodtes, credt, equtes, and alternatve assets. We also lnk the ncrease of cross-asset correlaton to the current hgh macro volatlty and to developments n rsk-management and alpha-extracton technques. US Treasures and Rsk Management Dscplned rsk management and portfolo dversfcaton can contrbute to an ncrease of cross-asset correlatons. For nstance, when nvestors ncrease ther equty rsk exposure by purchasng US, Developed World, and Emergng Markets equtes n proporton to market captalzaton, ths leads to a net sellng of USD and buyng of foregn currences. In addton, when the addtonal rsk captal s obtaned by reducton of holdngs of government bonds (n proporton to current government bond market captalzaton), t causes sellng of US Treasures. Ths type of rsk-on/off flows s causng the current negatve correlaton between USD and global equtes, and the postve correlaton between equtes and treasury yelds (see the Currences and Interest Rates sectons). Over the past few years, many nvestors started ncreasng commodty allocaton due to ther low hstorcal correlaton to other rsky assets and resstance to nflaton. Rsk-on flows nto commodtes, along wth USD/Equty correlaton (note that commodtes are prced n USD), recently gave rse to a strong postve correlaton between equtes and commodtes. Rsk hedgng wth lqud dervatve products can also have an mpact on correlatons. However, dervatves are not the cause of correlaton but just facltate the prevously descrbed rsk-management technques. For nstance, hedgng of equty exposure s typcally mplemented va ndex futures on lqud, captalzaton-weghted ndces such as the S&P 500. Tradng of these nstruments can mechancally ncrease correlaton between large-cap stocks. Smlarly, hedgng credt portfolos wth VIX or S&P 500 products can result n ncreased credt-equty correlaton. 5

6 Alpha Extracton A decrease of asset-specfc alpha ncreases the level of cross-asset correlatons. An example of alpha capture that causes correlaton ncrease s statstcal arbtrage. In a smple par strategy, an arbtrageur s tradng two correlated assets buyng the underperformng asset and sellng the outperformng one. The trade ncreases the correlaton between the par and captures (dmnshes) the alpha. Ths type of arbtrage can be mplemented between pars of stocks, sectors, and regonal markets, between ndces and ther consttuents, and more generally between dfferent assets such as currences, rates, and equtes. Smlar to statstcal arbtrage, alpha s extracted by varous relatve-value tradng strateges. Captal structure arbtrage s a relatve-value approach of tradng equty versus credt. It can be employed on an ndvdual securty as well as an ndex level (e.g., tradng CDX aganst S&P 500). Captal structure arbtrage can cause an ncrease of credt/equty correlatons. Currency carry trades nvolve sellng low-yeldng currences (e.g., USD and JPY) and buyng hgh-yeldng currences, or more generally rsky assets denomnated n these currences. Ths generalzed currency carry trade can cause an ncrease of FX/equty correlaton, and even an ncrease n commodty/equty correlaton. An ncrease n the amount of assets nvested n alpha-extracton strateges may have a secular mpact on cross-asset correlatons. Hedge funds assets, currently at ~$T, experenced sgnfcant growth over the past ten years. Whle not all hedge funds can consstently generate alpha, the ncrease of hedge fund assets lkely had a net effect of alpha reducton and thus ncrease of correlaton. The descrbed market changes that contrbuted to a secular ncrease of cross-asset correlatons also brought some benefts. For example, cross-regonal captal flows provde captal to emergng economes, electronc tradng can mprove lqudty for all market partcpants, and credt/equty arbtrage equally dstrbutes rsk and reward between bondholders and shareholders. Cross-asset correlatons wll lkely decrease alongsde macro volatlty. However, the descrbed market developments should persst and reset correlaton levels to a new, hgher, norm. 6

7 Currences Rsk On/Off and Global Currency Flows It s well known that an ncreased rsk appette of nvestors results n an nflow of captal nto Emergng Market stocks. In order to purchase these stocks, funds need to be converted nto local EM currences. Gven the lqudty of EM stocks and currences, these nflows typcally cause both assets (EM stocks and currences) to apprecate at the same tme, gvng rse to postve correlaton between equtes and EM currences. Increased nterest for EM equtes and the rsk-on/off tradng style caused a remarkable ncrease of EM Currency/Equty correlaton over the past seven years (Fgure 5). In fact, the current average correlaton between the S&P 500 and EM Currences s hgher than the average correlaton between largecap US stocks even at the peak of the fnancal crss n 008. Smlar rsk flows drve the correlaton between equtes and currences of major developed economes such as USD, EUR, and JPY. Of partcular nterest for equty nvestors s the strong negatve correlaton between equtes and USD. Developments n global equty markets over the past ten years can help us understand ths relatonshp. Fgure 6 shows the market captalzaton of US, Developed World ex US, and Emergng Equty Markets snce The fgure shows the relatve rse of EM, and declne of US market captalzaton. Ten years ago, US equty markets represented ~6 of global equty market captalzaton, wth emergng markets only 6%. In the decade from 001 to 011 the US equty market halved to ~35% of global market captalzaton, Developed Markets ex US ncreased to 41%, and Emergng Markets expanded to 4% of global equty captalzaton. 6 The relevance of captalzaton changes to currency/equty correlaton s that, whle ten years ago the rsk-on trade nto global equtes (n proporton to global market captalzaton) nvolved net buyng of USD, snce 004 (and n partcular over the past three years) the global rsk-on trade nvolves net sellng of USD n order to purchase EM and Developed World ex US equtes. Fgure 5: Correlaton of EM Currences (vs. USD) and S&P Correlaton of EM Currences wth S&P 500 Jul, 93 May, 96 Mar, 99 Jan, 0 Nov, 04 Sep, 07 Jul, 10-1 Fgure 6: Global Equty Market Captalzaton Snce 1998 Market Captalzaton ($Bn) US DMxUS EM Year US DM ex US EM % % % ,800 5, % 1% ,900 6, % 1% 000 1,300 7, % % ,800 7,500 1,00 57% 37% 6% 00 10,500 6,100 1, % 6% 003 8,100 6,100 1,000 53% 4 7% ,300 8,600 1, % 8% ,300 10,500,00 47% 44% 9% ,300 11,900 3,300 43% 45% 1% 007 1,800 14,700 4, % 15% 008 1,900 16,900 7,800 34% 45% 1% 009 7,900 9,500 3,600 38% 45% 17% 010 9,900 1,300 6,500 34% 43% 3% ,400 13,400 8,000 35% 41% 4% 6 The perod ncludes 9/11/011, wars n Iraq and Afghanstan, emergence of BRICs, and strengthenng of European Monetary Unon. 7

8 Equally mportant s to look at the captalzaton of global government debt markets shown n Fgure 7. Currently, US and Japanese government bonds represent 6% of the market. US Treasures and Japan government bonds are the largest, most lqud, and broadly held rskless assets. US Treasures alone represent almost 3 of all government bonds, and almost 6 of all AAA-rated bonds. In other words, US Government debt s most broadly used as a lqud store of rsk-free assets. A rsk-on trade nvolves shftng allocaton from rskless nto rsky assets, and wll therefore nvolve net sellng of US (or Japan) debt and sellng the USD (or JPY) to buy rsky assets such as equtes two-thrds of whch are denomnated n non-us currences. 7 The rsk-on/off mpact to asset allocaton between government bonds and more rsky assets wll also cause correlaton between nterest rates and equtes dscussed n the next secton. Fgure 8 shows the correlaton of DM currences (excludng JPY) and equtes over the past 0 years. We note that correlaton started sgnfcantly ncreasng n 004, whch s roughly the tme US equty market captalzaton dropped below half of the global market captalzaton. As the US captalzaton dropped to roughly a thrd, correlaton between DM currences (excludng JPY) and equtes further ncreased. The same chart shows correlaton of JPY/USD and equtes. Gven the role of Japan s government bond market (the largest lqud rsk-free asset pool), correlaton of JPY/USD to equtes s negatve, n clear contrast to the rest of DM currences. Fgure 7: Global Government Debt Market Captalzaton Country Debt ($Bn) % of Total S&P Rat. % of GDP Japan 10,779 34% AA-u 6 USA 9,077 8% AAAu 59 Italy,99 7% A+u 118 France 1,869 6% AAAu 84 Germany 1,761 5% AAAu 79 UK 1,76 5% AAAu 77 Span 939 3% AA 63 Canada 633 % AAA 34 Greece 479 1% BB- 144 Belgum 451 1% AA+u 99 Netherlands 449 1% AAAu 65 Austra 76 1% AAA 70 Portugal 06 1% BBB- 83 Australa 03 1% AAAu Next 10 1,05 3% Source: J.P. Morgan Equty Dervatves Strategy, Bloomberg. Fgure 8: Correlaton of DM Currences (vs. USD) wth S&P 500 (Sold); Correlaton of JPY (vs. USD) wth S&P 500 (Dashed) Feb, 91 May, 94 Aug, 97 Nov, 00 Feb, 04 May, 07 Aug, DM Currences (ex JPY) wth SPX JPY wth SPX We have shown how secular changes n global equty and bond market captalzaton as well as rsk-management technques (namely asset allocaton between rsky and rskless assets) mpact the correlaton between currences and equtes. Next we address the role of alpha-extracton technques such as currency carry trades and cross-asset statstcal arbtrage. Currency carry trades nvolve borrowng n low-yeldng currences, and sellng the currency to nvest n hgher-yeldng currences or other hgher-yeldng assets such as equtes. Hstorcally, low-yeldng currences were the JPY, and more recently the USD. Hgher-yeldng currences were typcally rsker EM currences or commodty-drven developed world currences. In both cases the currency carry trade s a rsk-on trade that nvolves sellng USD or JPY whle buyng currences (or assets) postvely correlated wth equty or commodty rsk. Through ths mechansm, the currency carry trade strengthens the USD/equty correlaton, as well as correlaton between equtes, currences, and commodtes. Cross-asset statstcal arbtrage nvolves smultaneous tradng of currences, equtes, and commodtes. A computer model establshes and forecasts covarance between these assets, then algorthmcally trades based on dscrepances between the expected relatve moves of assets and observed moves. Ths type of statstcal tradng can provde lqudty and sap the market mpact from trades n each asset class. However, the result s an ncrease of cross-asset correlaton. We can fnd 7 Or alternatvely buyng rsker corporate or non-us government debt from countres such as Italy, Span, and Greece. 8

9 potental evdence of hgh-frequency statstcal cross-asset tradng actvty n the behavor of currency/equty correlaton calculated over dfferent tme horzons. Asset allocaton flows typcally occur over long-term tme horzons. For nstance, a portfolo manager may decde to revew the allocaton to rsky assets vs. rskless bonds on a weekly bass, but wll not adjust rsk exposure mnute-by-mnute. Fgure 9 below shows EUR/USD correlaton to equtes calculated based on 5-, 15-, 30-, 60-, and 180-mnute returns over the past sx months. We note that EUR/USD to equty correlaton s hghest for the shortest tme nterval (5 mnutes) and decreases for longer tme perods. Ths suggests that some form of cross-asset tradng, most lkely of a statstcal nature, does take place at hgh frequency. Hgh correlaton between currences and equtes has a varety of mplcatons for equty nvestors. The negatve correlaton between USD and equtes ncreases the volatlty of foregn assets (e.g., ADRs) to US nvestors. Smlarly, for foregn nvestors ths makes US equtes less volatle as equty and USD rsks partally offset each other. Another nterestng applcaton of currency/equty correlaton s the possblty of cross-asset hedgng. If FX optons are cheaper than equty ndex optons, nvestors could hedge equty exposure wth FX optons. In ths approach the nvestor reles on the stablty of correlaton between currences and equty, and seeks FX optons that are cheaper than S&P 500 optons. Fgure 10 below shows the sx-month downsde skew for the S&P 500 and the average skew for FX optons of DM currences aganst USD. 8 Skew s expressed as a rato of out-of-the-money (OTM) put mpled volatlty to at-the-money (ATM) mpled volatlty. We note that S&P 500 skew s tradng persstently hgher than FX skew. The reason for ths s the supply/demand mbalance for equty ndex put optons (more buyers than sellers of downsde protecton). Meanwhle, FX skew was farly low pror to 004, but gven the steady ncrease of currency/equty correlaton (Fgure 8), FX skew has been rsng as well. Despte ths ncrease, FX skew for certan currency pars may stll be cheaper than S&P 500 skew, makng FX puts an attractve alternatve hedge for equtes. 9 Fgure 9: EUR/USD Correlaton to S&P 500, Calculated from 5-, 15-, 30-, 60-, and 180-Mnute Returns Fgure 10: S&P 500 and DM Currences vs. USD Downsde Skew 5 48% 1.3 S&P 500 Skew Correlaton % 33% 9% DM FX (ex JPY) Skew % Interval (Mnutes) 1.0 Apr, 01 Sep, 0 Feb, 04 Jul, 05 Dec, 06 May, 08 Oct, 09 Mar, 11 8 Skew measures the dfference between the prce of OTM downsde puts to at-the-money puts. Hgh levels of skew mply a hgh probablty of a large downsde move, whch ncreases the prce of downsde put optons. 9 For specfc examples of currency/equty hedgng, see J.P. Morgan publcatons: Tal-Rsk Hedgng wth FX Optons and VIX, Equtes, and Dollar Carry Trade. 9

10 Interest Rates End of Fed Model and Use of US Treasures as Global Rsk-Free Asset In the prevous secton, we explaned the role of US and Japan government debt as a lqud, rskless storage of assets. When nvestors ncrease rsk exposure, they typcally sell some government debt, and nvest the proceeds n DM and EM equtes, rsky debt, or commodtes. Reducng rsk exposure nvolves sellng rsky assets and buyng treasures (flght to qualty). Ths rsk-on/off asset allocaton approach has caused a postve correlaton between equtes and nterest rates over the past ten years. Postve correlaton between rates and equtes adds sgnfcant dversfcaton benefts to a portfolo of rsky assets and treasury bonds as rsky assets declne n value, treasury bonds apprecate and vce versa (e.g., see Correlaton Rsk/Reward secton). Another reason for use of Treasures as a rsk-free asset and a postve equty/rate correlaton s an actve monetary polcy. If the economy s overheatng and rsky assets rally, the central bank may ncrease rates to cool down the economy. Conversely, f rsky assets are sellng off, the Fed may cut rates to support growth and avod recesson (Greenspan/Bernanke Put). Gven the postve nomnal yeld of treasury bonds and negatve correlaton to equtes, treasures are consdered to be a superor rskless asset to cash deposts. The wdespread usage of US Treasures as rskless storage has caused an ncrease of equty/rate correlatons and decrease of treasury yelds over the past 15 years, as shown n Fgure 11. Hstorcally, the correlaton between equtes and rates was not always postve. Moreover, there are theoretcal reasons why ths correlaton should n fact be negatve. The so-called Fed Model states that treasury yelds should be roughly equal to equty earnngs yeld (E/P or smply the nverse of the P/E rato). 10 The so-called Fed Model therefore mples drect negatve correlaton between treasury yelds and equtes the hgher the stock prce, the lower the equty yeld and hence the lower the treasury yeld. The ratonale behnd the Fed Model s that nvestors compare the yeld generated by holdng treasures to equty earnngs yeld, and nvest ther cash deposts nto the one that looks more attractve (untl treasury yeld and earnngs yeld become equal). Market data over the past ten years have proved ths reasonng to be flawed. Fgure 1 shows a 30-year hstory of rate/equty correlaton. We note that pror to 1997, rate/equty correlaton was ndeed negatve, as predcted by the so-called Fed Model. Ths changed vrtually n one day, when the Asan crss caused rsk contagon across global markets on 10/7/ Ed Yarden, Fed s stock market model fnds overvaluaton, Topc Study #38, US Equty Research, Deutsche Morgan Grenfell,

11 Fgure 11: Correlaton of 10Y Treasury Yeld and S&P 500 Fgure 1: Regme Change of Equty/Rate Correlaton Occurred n 1997/ Correlaton of 10Y Treasury Yeld and Equtes % 5 5% 10/7/97 - The frst 'Global Rsk-off' Event Asan Crss Splls over - Worst 1-day drop of NDX on record, prompts early market close. Treasures yelds drop to mult-year lows. Wthn next 1 months, Fed cuts rates 3 tmes as a response to Asa, Russa and LTCM Crses 5 Apr, 9 May, 95 Jun, 98 Jul, 01 Aug, 04 Sep, 07 Oct, Y Treasury Yeld -8-5% -5-75% Feb, 76 Dec, 80 Oct, 85 Aug, 90 Jun, 95 Apr, 00 Feb, 05 Dec, 09 Fed Model Regme Global Rsk On/Off Regme Investors across the globe sold rsky assets and pled nto Treasury bonds, drvng yelds lower. The frst global Rsk-off event resulted n the worst one-day returns for the Nasdaq and Dow Jones, and caused Treasury yelds to drop to two-year lows. Over the next 1 months and as a response to the crss, the Fed postponed one rate ncrease, and subsequently cut rates three tmes thereby renforcng the postve correlaton between equtes and yelds. Smlar equty selloffs and Treasury ralles occurred twce more n the next year durng the LTCM and Russa debt crses. Rsk-off events have become truly global affectng all asset classes (EM and DM Equtes n the Asa crss, Emergng Market Debt n the Russa crss, Equty Volatlty, Interest Rate Swap Spreads, and M&A Spreads n the LTCM crss). These events establshed treasury bonds as the rskless asset of choce and reversed the levels of equty/rates correlaton for years to come. Despte our vew that equty/rate correlatons wll stay postve, there are certan scenaros that could cause a weakenng or reversal of ths relatonshp. Whle the return of an outdated Fed Model nvestment approach does not pose a rsk for correlaton, the occurrence of Stagflaton or even full-fledged US bond/equty contagon could reverse the equty/rate correlaton. In the case of Stagflaton, treasury yelds are expected to ncrease as a result of ncreased nflaton expectatons. A low or negatve growth outlook and ncreased nflaton expectatons could cause an equty selloff. In ths way, the occurrence of Stagflaton could cause equty/rate correlatons to drop or even turn negatve. The most dramatc reversal of equty/rate correlatons could happen n the event of full-fledged US bond/equty contagon. Ths could occur as a result of a US fscal crss, promptng foregn nvestors to abandon US Treasures as the rsk-free asset of choce. A sharp ncrease n rates would be followed by a broad selloff of all dollar assets. Ths type of tal event could result n equty/rate correlaton droppng towards -10. In addton, ths event would lkely trgger a dramatc reversal of equty/currency and equty/commodty correlatons, lkely weakenng cross-regonal equty correlatons (e.g., US equtes underperformng). Investors wary of a potental US fscal crss and the tal-rsk scenaro descrbed above could use an equty/rate correlaton vew n order to nexpensvely hedge ther equty exposure. An example trade would be to buy an out-of-the-money put opton on the S&P 500 ndex, wth a payoff that s contngent on treasury yelds rsng above a certan level. Gven the current postve correlaton between rates and equtes, the cost of ths type of hybrd would be sgnfcantly cheaper (as compared to the smple S&P 500 put opton). For more detals on ths trade, see the last secton of ths report (Hybrd Dervatve Trades). 11

12 Commodtes Slver Bullet for Asset Allocaton Pror to the fnancal crss n 008, commodtes were essentally uncorrelated to equtes and bonds, and were relatvely weakly correlated among themselves. These attractve features were hghlghted n numerous studes n the md-000s. For nstance, a 006 Ibbotson Assocates study concluded that ncludng commodtes would have mproved performance by 133bps, and suggested that an optmal asset allocaton should nclude a sgnfcant proporton of commodtes. 11 In addton to dversfcaton benefts, commodtes are consdered to be a store of value and a hedge for nflaton. These fndngs were largely based on hstorcal analyses and dd not take nto account the potental prce and correlaton mpact of wdespread commodty allocatons. These attractve hstorcal propertes of commodtes caught nvestors attenton and sgnfcant funds started flowng nto the asset class. The demand for commodtes from Chna and other emergng economes, the bengn monetary polces of central banks, and ncreased geopoltcal tensons caused large prce ncreases, further fuelng nterest n the asset class. For nstance, assets nvested n Commodty ETFs roughly doubled every year snce ther launch n 005 and currently stand at ~$150bn. In addton to ndvdual commodtes, broad commodty ndces such as GS, DJ UBS, and TR/J CRB attracted sgnfcant nvestment assets. Fgure 13 shows the growth of commodty ETF assets, as well as the steady ncrease n correlaton between varous commodtes over the past ten years. Correlaton between ndvdual commodtes was weak n the 1990s, but started ncreasng steadly n the 000s. Ths s lkely the result of ncreased nvestment allocaton to commodtes and commodty ndces. Correlaton between commodtes and equtes was on average negatve n the 1990s and early 000s. However, followng the collapse of Lehman Brothers, commodty/equty correlaton turned postve (Fgure 14). There are several reasons that caused ths quck reversal. Frstly, commodtes sold off alongsde equtes and other rsky assets n the bg rsk-off event of 008/009. As nvestors de-levered and de-rsked, any speculatve premum bult nto commodtes was erased. Alongsde de-rskng, the recesson that followed the crss reduced demand for commodtes, causng a postve correlaton between equtes and commodtes (e.g., a drop n GDP expectatons translates nto reduced demand for ol and lower equty valuatons at the same tme). Another sgnfcant drver of postve commodty/equty correlaton s the negatve correlaton of USD to equtes descrbed n the Currences secton of ths report (see Fgures 5 and 8). As commodtes are prced n USD, currency/equty correlaton splls over to commodty/equty correlaton. For nstance, a 1% ncrease n equtes wll, on average, concde wth a 0bps drop n USD. As commodtes are prced n USD, ths wll mechancally lead to a 0bps ncrease n commodty prces on account of USD/equty correlaton. Currently, about 4 of the postve commodty/equty correlaton can be attrbuted to the (negatve) correlaton of USD to equtes. The ncrease of commodty/equty correlaton snce 008 and the commodty/equty correlaton adjusted for USD prcng of commodtes s shown n Fgure Strategc Asset Allocaton and Commodtes, Ibbotson Assocates,

13 Fgure 13: Correlaton Between Varous Commodtes and Growth of Commodty ETFs Fgure 14: Commodty/Equty Correlaton and the Spllover of Equty/FX Correlaton % 3 5% Average Correlaton Between All Commodtes (LHS) Commodty ETF Assets $Bn (RHS) Average Correlaton of all Commodtes to Equtes 15% % 0 Feb, 91 Dec, 93 Oct, 96 Aug, 99 Jun, 0 Apr, 05 Feb, 08 Dec, May, 91 Oct, 94 Mar, 98 Aug, 01 Jan, 05 Jun, 08 Adjusted for USD Fluctuatons Currently ~4 of Commodty/Equty Correl s a Spllover from USD/Equty Correl Fgure 15 provdes more detals on the shft n commodty/equty correlaton that occurred n 008. The bggest reverson was experenced by Ol/Equty correlaton whch spked from roughly -1 to current levels of over 6. Industral metals and soft commodtes experenced smlar correlaton shfts. Gold/Equty correlatons ntally dropped as nvestors sold equtes and rushed nto the perceved relatve securty of gold. However, correlaton quckly turned postve fueled by speculatve demand and strong negatve correlaton of USD to equtes. Fgure 15: Commodty/Equty Correlaton for Energy, Precous Metals, Industral Metals, and Soft Commodtes Fgure 16: Some Commodtes Are Prone to the Creaton of Bubbles Correlaton of Commodtes to Equtes Energy Slver Thursday Hunts Brothers Collapse 4/8/ Industral Metals Precous Metals Energy Soft Commodtes Precous Metals Jan, 95 Nov, 97 Sep, 00 Jul, 03 May, 06 Mar, Jul, 75 Jun, 80 May, 85 Apr, 90 Mar, 95 Feb, 00 Jan, 05 Dec, 09 The ncrease of commodty/equty correlaton snce 008 dmnshed some of the dversfcaton value to a cross-asset portfolo. At least part of the correlaton ncrease can lkely be attrbuted to the nvestment demand for commodtes. As nvestors ncrease or decrease exposure to all rsky assets (ncludng commodtes and equtes), commodtes/equty correlaton ncreases. More precarous than the reduced dversfcaton beneft s the rsk of creaton and burstng of speculatve bubbles. The burst of an asset bubble can reduce returns and erase dversfcaton benefts acheved over tme. Fgure 16 shows the prce of Slver over the past 35 years. There are two promnent features of the chart. The frst one s the speculatve bubble engneered by the Hunt Brothers and ts burst on Slver Thursday n March 1980, and the second one s the prce of slver at the tme of wrtng of ths report. 13

14 Asde from market rsk, there are ntrgung socal and macroeconomc aspects of commodty nvestng. Some of these ssues were publcly dscussed followng a decson by Calforna State Teachers Retrement System aganst a large nvestment nto commodtes. In the run-up of slver prces durng the Hunt Brothers scheme, Tffany publshed a full-page add n The New York Tmes statng: We thnk t s unconsconable for anyone to hoard several bllon, yes bllon, dollars worth of slver and thus drve the prce up so hgh that others must pay artfcally hgh prces for artcles made of slver. Replacng Slver wth Food or Gas reveals the socoeconomc rsk of potental commodty bubbles. In addton to asset allocaton, commodty/equty correlaton plays an mportant role n valuatons and volatlty estmates for Materals and Energy sector stocks. 1 As dscussed n the Rates secton, nvestors trade hybrd optons based on equty and commodty prces. Two examples of such hybrd opton trades are explaned n the Hybrd Dervatves Trades secton. 1 For further dscusson of Ol/Equty correlaton, and ts mpact on Energy Sector Volatlty, please see our paper Energy Sector Volatlty Fundamentals of Volatlty and Relatve Value Ideas from

15 Credt Captal Structure Arbtraged Correlaton between credt spreads and equtes has been steadly ncreasng over the past ten years. Fgure 17 shows the correlaton of changes n 5-year Hgh Yeld credt spreads and S&P 500 returns, as well as the correlaton between changes n HY credt spreads and changes n VIX levels. Wth correlaton of ~8, credt, equtes, and equty volatlty are currently the most closely correlated assets. There are many theoretcal reasons behnd the strong credt/equty correlaton. Structural models of credt provde prces for both bonds and the stock of a company based on the value and volatlty of the company s assets. If the value of the assets drops below the level of debt, the equty prce s zero. For hgher levels of assets, equty s prced as a call opton on assets struck at the debt level. J.P. Morgan Equty Dervatves Research mantans a smple structural model that can ndentfy dvergences between credt, equty volatlty, and equty levels for ndvdual stocks. 13 Asde from the theoretcal relatonshp, a hgh correlaton between credt and equtes s realzed through relatve-value tradng. Captal structure arbtrage trades and cross-asset hedgng tend to closely algn these three assets. An example of a captal structure arbtrage trade s a relatve-value trade between CDS and equty put optons. 14 Perhaps more mportant drvers of credt and equty correlaton are cross-asset hedges whch are usually mplemented at an ndex level. Due to the lqudty and transparency of the equty optons market, many nvestors hedge ther credt exposure va equty ndex optons and volatlty products (e.g., put spreads and put-spread collars on equty ndces, VIX futures, calls/call spreads and ndex varance). In addton to lqudty and transparency, an advantage of usng equty nstruments for credt hedgng s hedge dversfcaton. Investors dversfy ther hedges to avod potentally crowded postons n credt hedges (such as outrght shortng, or buyng puts on CDX prce ndex). If a hedge s crowded, nvestors that rush to monetze the payoff may mpact the prce of the hedgng nstrument and thus reduce the effectveness of the hedge. For ths reason t may be prudent to have hedges dversfed across lqud nstruments and thus mnmze the mpact of hedge unwnds. Another advantage of usng equty hedges for credt s the potental prcng advantage. Due to hgh levels of equty skew, prcng of equty putspreads and put-spread collars n some nstances may be more attractve than outrght purchases of CDX optons or shortng CDX. An obvous rsk of credt/equty hedges (and more generally cross-asset hedges) s the trackng error between the two assets. The sze of ths trackng error s typcally comparable to or greater than potental savngs n the opton prcng. However, the trackng rsk can also provde great opportuntes for nvestors hedgng credt wth equty (or vce versa). The reason s that credt and equty prces can exhbt sgnfcant dvergence n the short term. Investors who can correctly dentfy a dvergence can buy protecton on the expensve asset to hedge the one that appears laggng. Fgure 18 shows the cumulatve dvergence of HY Credt spreads over equtes and volatlty (S&P 500 and VIX) based on a smple multple regresson model. Ths smple approach can help nvestors dentfy hedgng relatve-value opportuntes. For nstance, the fgure shows a wdenng of credt relatve to equtes n the aftermath of GM s downgrade n the sprng of 005. Another epsode of credt/equty dvergence occurred when the VIX declned to mult-year lows at the end of A Framework for Credt-Equty Investng, Credt and Equty Volatlty Relatve Value Opportuntes,

16 Fgure 17: Correlaton of 5Y HY Credt Spreads to S&P 500 and VIX Fgure 18: Credt/Equty Dvergences over the Past Ten Years HY CDS to S&P 500 (Inverse) HY CDS to VIX Credt Rsk Hgher/Lower Than Equtes (% 75% 5 5% -5% -5 GM VIX Declnes BSAM LEH Equtes Drop Credt Rally Jul, 0 Oct, 03 Jan, 05 Apr, 06 Jul, 07 Oct, 08 Jan, 10 Apr, 11-75% Nov, 0 Mar, 04 Jul, 05 Nov, 06 Mar, 08 Jul, 09 Nov, 10 Perhaps the bggest dvergence and hence credt/equty hedgng opportunty occurred n the summer of 007, followng the collapse of BSAM credt hedge funds. Durng ths epsode, equty markets faled to react to the deteroraton n credt markets leadng nto the 008 fnancal crss. In all of these cases, holdng equty hedges would have been more proftable than holdng credt hedges, as credt ether wdened ahead of equtes or equty volatlty was lower than credt spreads. However, equty hedges are not always more attractve. At the end of 009, credt spreads tghtened more than what would have been expected based on the regresson aganst equtes and the VIX (buyng credt protecton may have been more effectve leadng nto the market correcton that happened n May 010). Despte the recent wdenng of credt spreads relatve to equty volatlty, currently we do not see a large dscrepancy between the two assets. 16

17 Equtes Why We Have a Correlaton Bubble As wth other asset classes, correlaton between varous equty markets and sectors has been trendng hgher over the past 0 years. 15 The equty correlatons most nterestng to nvestors are the correlaton between dfferent regonal markets (e.g., the correlaton between developed world ndces), the correlaton between varous ndustry sectors, and the correlaton between ndvdual stocks. Fgure 19 shows the correlaton between developed and emergng markets and the correlaton between dfferent emergng market country benchmarks (n addton, Fgure 1 shows the regonal correlaton between all country benchmarks). We note that the ncrease of cross-regonal equty correlaton s largely a secular trend (and only to a smaller extent drven by macro volatlty). As explaned n the frst secton of the report, ths trend has been caused by the globalzaton of economes and fnancal markets. We beleve ths globalzaton, and hence the hgh cross-regonal correlaton trend, s not reversble. Whle regon-specfc events such as the recent earthquake n Japan may soften cross-regonal correlatons, markets are not lkely to revert to the levels observed n the md-1990s, when the average correlaton between EM benchmarks was close to zero and EM/DM correlaton was only ~5%. Ths trend of rsng cross-regonal correlaton sgnfcantly dmnshed the once mportant dversfcaton beneft of nvestng across emergng and developed markets. It appears that n the case of crossregonal nvestng, the only free lunch n fnance (a common reference to dversfcaton) has been eaten. The correlatons between ndustry sectors are currently at ther hghest levels. Fgure 0 shows a trend of ncreasng sector correlatons over the past ten years, n partcular the ncrease due to market volatlty n 008. Asde from market volatlty, sector-specfc market trends can have a large mpact on cross-sector equty correlaton. The most promnent s the large drop n sector correlaton durng the creaton and burst of the nternet bubble n 001 as Technology stocks frst ralled and then crashed relatve to old economy sectors. 16 Fgure 0 also shows average correlaton between S&P 500 stocks. The recent ncrease of equty correlaton has largely been drven by the ncreased macro volatlty snce 007. However, other structural reasons contrbuted to ncreased levels of equty correlaton. The wdespread use of ndex products (e.g., futures) and hgh-frequency tradng strateges, such as statstcal arbtrage and ndex arbtrage, are lkely contrbutng to ncreased levels of correlaton. 17 Whle the levels of correlaton should decrease wth reduced macro volatlty (correlaton has already sgnfcantly decreased over the past sx months), the new normal for equty correlaton wll lkely be hgher due to the aforementoned structural developments. The hstorcal average level of correlaton was 8%, and our estmate for the future long-term average s ~35% (sgnfcantly lower than correlaton durng the peak of market crss, but hgher than the hstorcal average). In addton to ncreased longterm average levels, correlaton wll probably be more prone to spkes due to the alpha depleton dscussed n the frst secton. 15 For a detaled dscusson of equty correlatons see our report Why we have a correlaton bubble, For a more detaled dscusson of sector correlatons and ther mpact on market volatlty, see our report New Framework for Tradng Correlaton, Ths was dscussed n detal n our report Why we have a correlaton bubble. 17

18 Fgure 19: Secular Increase of Cross-Regonal Equty Correlaton Fgure 0: Sector and Stock Equty Correlaton 9 8 Between DM and EM Countres 9 8 Between S&P 500 Sectors Between EM Countres 1 Between S&P 500 Stocks Dec, 88 Jan, 9 Feb, 95 Mar, 98 Apr, 01 May, 04 Jun, 07 Jul, 10 Jan, 90 Dec, 9 Nov, 95 Oct, 98 Sep, 01 Aug, 04 Jul, 07 Jun, 10 Equty correlatons are an mportant nput to manage the rsk of a mult-asset portfolo or an equty-only long-short portfolo. More drectly, equty correlatons are used to prce varous dervatves nstruments as descrbed below. Correlaton between markets n dfferent regons s used to prce optons on baskets of global ndces. These World Basket optons are used by both retal and nsttutonal nvestors. An example s a put opton on the best-performng ndex out of the S&P 500, EuroStoxx 50, and Nkke. The buyer of a Best-of put s buyng correlaton,.e., countng that f the markets go down, correlaton between these ndces wll ncrease, causng them all to fall by a smlar amount. Best-of optons can sgnfcantly reduce the cost of hedgng as they cost less than the cheapest put opton on one ndex. Another popular nstrument s outperformance optons. An example s an opton on the outperformance of Emergng Markets (e.g., MSCI EM ndex) over DM (e.g., S&P 500). Prcng of ths opton depends on the projected correlaton between EM and DM, and the nstrument can provde a relatvely secure and levered exposure to strong EM performance (see Hybrd Dervatve Trades secton). Both sector and average stock equty correlatons can be traded through relatve-value tradng of ndex, sector (e.g., ETF), and stock optons. Sellng equty correlaton entals sellng ndex optons and buyng optons on the ndvdual ndex consttuents (stocks) n a specfc rato. Sophstcated nvestors should be aware of the prce of correlaton (mpled correlaton) they are payng when buyng ndex optons (e.g., buyng ndex puts). Due to excessve demand and a lack of supply of ndex optons, equty correlaton typcally trades above ts far value. In many cases, nvestors may be better off buyng optons on ndvdual stocks or sectors than ndex optons. When the prce of equty correlaton s much hgher than levels realzed by stock prces, arbtrage nvestors step n and sell ndex correlaton For more detals see Why we have Correlaton Bubble, Tal Rsk Relatve Value, and New Framework for Correlaton Tradng. 18

19 Alternatve Assets Hedge Funds and Correlaton Throughout ths report we showed examples of ncreasng cross-asset correlaton levels. One may ask f there s an asset class that dd not experence a secular ncrease of correlaton durng recent years. An asset that could consstently generate postve alpha (outperformance) and not have a sgnfcant exposure to market rsk (beta) would be uncorrelated to market rsk. Many hedge funds seek to generate pure alpha through an absolute return mandate and should therefore be less correlated to other rsky assets. Hedge funds are usually classfed as Alternatve Assets, alongsde prvate equty and venture captal. There are varous types of hedge funds ncludng Merger Arbtrage, Global Macro, Dstressed, Equty Market Neutral, Convertble Arbtrage, and others. These hedge fund strateges show relatvely low correlaton between one another. Fgure 1 shows the average correlaton between Hedge Fund Research Indces over the past eght years. 19 Correlaton between varous hedge fund strateges has been low, and s not showng a secular ncreasng trend as we see wth equtes, commodtes, and currences. Correlaton between the average performance of hedge funds (as measured by the HFRXGL Index) and the S&P 500 has been n a 0-8 range. Ths shows that, on average, hedge funds do have a sgnfcant exposure to equty markets. An attractve feature of hedge fund/equty correlaton s that t tends to declne wth an ncrease of market rsk. In other words, on average, hedge funds show the ablty to scale down market exposure n perods of hgh macro volatlty. Ths s shown n Fgure whch plots hedge fund/equty correlaton vs. levels of equty correlaton. Fgure 1: Correlaton Between Hedge Fund Indces 9 8 Fgure : Hedge Fund/Equty Correlaton Declnes n Tmes of Hgh Macro Volatlty Correlaton Between Hedge Funds HF to Equty Correlaton HF/Equty Corr.= -0.5*Equty Corr Dec, 03 Feb, 05 Apr, 06 Jun, 07 Aug, 08 Oct, 09 Dec, Equty Correlaton The low correlaton between hedge fund strateges and lower correlatons to other rsky assets n perods of stress make hedge funds an attractve asset class. Over the past ten years, hedge fund assets ncreased sgnfcantly, both n absolute terms as well as n terms of percentage of global equty market captalzaton. Ths s shown n Fgure 3. Hedge fund managers usually have a dscplned approach to rsk management and neutralze rsk exposures wth the use of ndex-based and leveraged products such as futures and optons. These rsk-management technques, alongsde hgher-thanaverage turnover, can contrbute to ncreased levels of correlaton. 0 Addtonally, hedge funds seek to extract alpha through relatve-value (hedged) tradng. In the frst secton of ths report, we showed that dmnshed levels of alpha ncrease the 19 1M average par-wse correlaton between the followng Hedge Fund Research ndces: HFRXMA, HFRXDS, HFRXEH, HFRXCA, HFRXRVA, HFRXGL, HFRXM, HRXEMN, HFRXCOM, HFRXCRED, and HFRXTEM. 0 See Why we have correlaton bubble,

20 level of correlaton and make markets more susceptble to correlaton spkes. It s a possblty that the growth of hedge fund assets (shown n Fgure 3) contrbuted to the secular ncrease of correlatons over the past ten years (e.g., global macro and emergng market strateges may have contrbuted to an ncrease of cross-regonal correlatons, captal structure arbtrage strateges to credt/equty correlaton, statstcal arbtrage strateges to equty correlaton, etc.). Fgure 3: Growth of Hedge Fund Assets Over the Past 15 Years 8% 6% HF Assets as % of Global Equty Markets (Left),500,000 4% 1,500 1,000 % HF Assets n $Bn (Rght) 500 Dec-97 Jan-00 Feb-0 Mar-04 Apr-06 May-08 Jun-10 Source: J.P. Morgan Equty Dervatves Strategy, BarclayHedge LTD Alternatve Investments database. 0 In ths report we have dscussed structural changes n the market that have led to an ncrease of correlaton levels. Whle the ncrease of correlatons over the past three years s largely drven by macro volatlty, secular market changes are causng a rsng trend n cross-asset correlatons. These changes nclude the ntegraton of global economes and captal markets, and nnovatons n the fnancal ndustry. Advancement of rsk-management technques, such as hedgng and dynamc asset allocaton, use of US Treasures as rsk-free storage, as well as more ntensve extracton of alpha, have lkely contrbuted to a secular ncrease n cross-asset correlatons. Compared to 0 years ago, markets are currently more correlated and there s more pronounced Alpha/Beta separaton. General market rsk or beta s managed more effcently and at sgnfcantly lower cost (e.g., lqud dervatve nstruments and electronc tradng), whle large pools of assets are seekng alpha va relatve-value and arbtrage tradng necessary for the proper functonng of captal markets. 0

21 Hybrd Dervatve Trades Implementng Cross-Asset Vews There are a number of tradng strateges that can take advantage of cross-asset vews. A common approach s to look for a closely correlated par of assets and proxy hedge one wth the other. Ths was brefly dscussed n the Credt and Currences sectons. The man premse of proxy hedgng s that the correlaton between the two assets wll reman stable. Cross-asset hedgng makes the most sense when the prce of one asset appears to be out of lne relatve to the other (e.g., equty volatlty too low relatve to credt spreads), or when the cost of protecton n one asset class s sgnfcantly cheaper than n the other (e.g., FX volatlty cheaper than equty ndex volatlty). Investors can also focus on varous tal-rsk scenaros and look at the cost of tal protecton across a range of assets. The expected benefts of cross-asset hedgng (ether comng from the cheapness of protecton, or expected reverson of prce dvergence) are then compared to the trackng rsk. In ths secton we present several trades to mplement cross-asset vews drectly through over-the-counter Hybrd dervatves. Hybrd dervatves have a payoff that s condtonal on the prce of more than one asset class. An advantage of usng hybrd dervatves s that nvestors can sgnfcantly cheapen the cost of a hedge by buyng protecton aganst a partcular cross-asset scenaro. An example s buyng a put opton on the S&P 500 wth a payoff condtonal on the gold prce rsng above a certan level. If an nvestor beleves that a market crash wll concde wth a run of nvestors nto the relatve securty of gold, buyng ths hybrd opton could be sgnfcantly cheaper than buyng a plan put on the S&P 500. In some cases, hybrd dervatves can have an added cost beneft f there s a natural supply of cross-asset rsk (e.g., from retal structured product ssuance or nsurance ndustry demand). Below we lst several cross-asset hybrd trades based on crossasset relatonshps dscussed n ths report. Rate/Equty S&P Year 9 Put Opton contngent on 10-Year Swap Rate above 6% at maturty. The cost of ths rate/equty hybrd opton s ~3.5%. Ths represents a dscount of ~75% compared to the cost of a vanlla S&P 500 5Y 9 put costng ~14.7%. As dscussed n Interest Rates secton, rates are currently exhbtng postve correlaton to equtes (Fgures 11 and 1). Ths means that f the S&P 500 drops, rates are lkely to drop as well. The reason for ths correlaton relates to rsk flows out of (nto) equtes and nto (out of) US treasury bonds. Gven the current postve correlaton, the probablty that the market wll drop and rates go up s relatvely small. For ths reason the cost of ths hybrd opton s sgnfcantly lower than a plan S&P 500 put. However, there are two scenaros n whch rate/equty correlaton could sharply reverse. The frst one s severe stagflaton n whch rates would go up and the market declne, and the second one s a tal event resultng n a sharp selloff of bonds and stocks (see Interest Rates secton). Investors hedgng aganst these two scenaros can sgnfcantly cheapen the cost of the hedge by purchasng ths hybrd opton. Moreover, there are structural forces that are cheapenng the prce of ths hybrd. Insurance companes that sell varableannuty products wth embedded guarantees are most vulnerable to fallng equtes (reducng the value of the assets used to provde guaranteed returns) and lower long-term nterest rates (lowerng the dscount rate and therefore ncreasng the present value assocated wth future labltes). These companes typcally buy structured and hybrd nvestments that are long equty/rate correlaton n order to hedge aganst the most unfavorable scenaro of equtes and nterest rates fallng smultaneously. Dealers that sell these structures are therefore left short equty/rate correlaton and frequently seek to trade products wth other clents that permt them to buy equty/rate correlaton n order to reduce ther own exposure. S&P 500 puts contngent on hgher nterest rates s an example of such a product. Investors that are wllng to make ther equty protecton contngent on an ncrease n long-term nterest rates can sgnfcantly reduce the cost of ths protecton by explotng dealers desre to buy ths equty/rate correlaton. 1

22 Commodty/Equty S&P Year 95% Put Opton contngent on Crude Ol above 105%. Ths opton costs ~3.3% compared to plan S&P year 95% put at ~6.6%. Ths represents a ~5 lower premum. As dscussed n the Commodtes secton, the current correlaton between equtes and ol s strongly postve (Fgure 15). Ths postve correlaton s caused by the lnk between expected economc actvty and demand for ol, nvestment nflows/outflows nto commodtes as a portfolo rsk asset, and a negatve relatonshp between equtes and USD the currency n whch ol s prced. Investors who beleve that ths hgh correlaton between crude ol and equtes could reverse may reduce the cost of ther equty protecton by makng t contngent on a rsng ol prce. A potental reversal of correlaton could be trggered by a supply shock such as escalaton of MENA crss (e.g., a blockade of ol shpments through the Persan Gulf). In such a scenaro ol prces may sharply ncrease and equtes sell off. Another scenaro n whch ol/equty correlaton may reverse s a potental US fscal crss a sharp selloff of USD could mechancally push commodty prces hgher. S&P Year 95% Put Opton contngent on Spot Gold above 105%. The cost of ths opton s ~.9% compared to vanlla put at ~6.6%. Ths reduces the premum by ~55% compared to the cost of a vanlla S&P year 95% put. The current correlaton between gold and equtes s mldly postve (Fgure 15). Ths s caused by the nvestment demand for gold and a negatve relatonshp between equtes and USD the currency n whch gold s prced. The postve correlaton between equtes and gold s sgnfcantly cheapenng the prce of ths opton (whch s contngent on gold and equtes movng n the opposte drecton). Despte the fact that gold and equtes are now postvely correlated, n the tmes of escalatng macro volatlty (e.g., see Fgure 15, September 008), gold prces are known to exhbt negatve correlaton wth equtes. Ths s drven by the use of gold as a relatvely secure store of value. In addton, an nflatonary shock could prop up the prces of gold whle negatvely mpactng equtes. Investors who beleve that gold/equty correlaton may reverse ether due to macro volatlty shocks or US nflaton may consder cheapenng the cost of ther equty protecton by makng t contngent on a rsng gold prce. Currency/Equty S&P 500 September 011 ATM Put Opton contngent on the Euro rsng 3.5% aganst the USD at maturty. The cost of ths opton s 1.15% compared to a vanlla S&P 500 put that costs 4.8%. Ths represents a ~75% lower premum. The S&P 500 recently exhbted a strong postve correlaton to the Euro/USD (Fgure 8). Therefore, a declne of the S&P 500 s expected to concde wth a declne n the Euro. However, f dollar assets show weakness as a result a potental large selloff n treasury bonds (e.g., trggered by the end of QE), the Euro may strengthen despte a market selloff. Investors who beleve that a potental declne of equtes may be accompaned by a selloff of USD assets can sgnfcantly reduce the cost of ther equty protecton by makng t contngent on the EUR rsng. In ths trade, an nvestor s sellng currently record-hgh levels of equty/fx correlaton and countng on a correlaton reversal. S&P 500 December % Put Opton contngent on the Canadan Dollar strengthenng 3.5% aganst the USD. The cost of ths opton s 0.55% vs. a vanlla put cost of ~4.6%. Ths represents a ~85% lower premum. The current correlaton between CAD and equtes s an astoundng 8. As wth other DM currences (Fgure 8), as equtes rse, the USD weakens causng apprecaton of the CAD. In addton, the CAD s hghly correlated to gold, and the postve correlaton of equtes and gold further ncreases the correlaton of the CAD to equtes. For these reasons the S&P 500 put opton contngent on CAD rsng s ~85% cheaper than the vanlla S&P 500 put. However, there are several scenaros that could cause ths correlaton to reverse. If an equty selloff s caused by a selloff n US assets trggered by end of QE, the occurrence of stagflaton n the US, or a dollar crss, the CAD could strengthen relatve to the USD. In addton, n case of escalaton of macro rsk, gold/equty correlaton would be expected to reverse

23 (Fgure 15, September 008) further supportng the CAD. Investors who beleve that ether equty/usd correlaton or equty/gold correlaton may reverse (causng the USD to weaken relatve to the CAD n a negatve equty envronment) could sgnfcantly beneft from sellng S&P 500/CAD correlaton at record levels. Cross-Regonal Outperformance of MSCI EM over S&P Year Call Opton. The cost of ths opton s ~6.4%. If the opton s made contngent on the S&P 500 beng above ts current level at expry, the cost s further reduced to ~3.9%. Ths represents ~35% and ~6 premum reductons, respectvely, relatve to a vanlla 1-year MSCI EM ATM call opton (currently at ~9.6%). An EM/DM outperformance opton provdes a relatvely secure and levered exposure to strong EM performance, as the loss s lmted to premum nvested and the cost s lower than an outrght opton on EM. The correlaton between EM and DM equtes s currently at record levels (Fgure 19). Hgh levels of EM/DM correlaton are cheapenng the prce of ths opton, as nvestors who purchase the opton are effectvely sellng EM/DM correlaton. Investors who thnk that Emergng Markets may outperform US equtes (e.g., due to rsk of US fscal crss), causng a reversal of EM/DM equty correlaton, would fnd an outperformance opton attractve. For nvestors wth a bullsh outlook on equtes, the addtonal contngency on the S&P 500 beng above the current prce represents an attractve feature. MSCI EM has a beta of ~1.5 to S&P 500, and the postve payoff of EM/DM outperformance s expected to concde wth the S&P 500 rsng n absolute terms. 3-Month 95% Strke Best-of Put on a basket of S&P 500, FTSE 100, and ASX 00. The cost of ths opton s 1.%. Ths represents a 31% dscount compared to the cheapest vanlla put on any of the ndces (premum of 1.75%). One way to cheapen the cost of protecton s buyng best-of puts on a basket of ndces. A best-of put has the same payoff as a standard vanlla put, but the underlyng nstrument s the best-performng ndex wthn the selected basket. By condtonng the payoff on the best performer out of a basket of three ndces, nvestors can cheapen the cost of protecton sgnfcantly. The prce of the best-of put s drven by the correlaton between the consttuents, the number of consttuents, and ther mpled volatltes. A best-of put s typcally cheaper when correlaton s low. Moreover, best-of puts beneft from an ncrease n correlaton and volatlty, whch both typcally occur durng a market selloff. Thus, f equtes sell off sharply, nvestors are lkely to have purchased these optons at a lower correlaton and volatlty level than what s subsequently realzed. All major global ndces sold off together durng the Q4 008 credt crss and the May 010 Euro area soveregn debt crss, suggestng the best-of put structure would have been effectve n protectng a global portfolo durng these sharp sell-offs. 1 1 See European Equty Dervatves Weekly Outlook Revstng tal rsk hedgng, 1-Mar

24 4 Marko Kolanovc Appendx: Smple Correlaton Model Volatlty of a mult-asset portfolo s proportonal to the average correlaton between asset classes (cross-asset correlaton) and the weghted-average volatlty of asset classes n the portfolo.,, ρ ρ ρ ρ ρ = = + = = j j j j j j Portfolo j j j j j j j Portfolo w w w w w w w w w In a smplfed rsk-on/off world, one can model each asset as havng an exposure or beta to the performance of macro rsk and some asset-specfc alpha. Cross-asset correlaton s then a functon of macro volatlty r, exposure of assets to macro volatlty (beta), and asset-specfc rsk (.e., magntude of ndvdual asset s alpha). For two assets (labeled wth ndces x and y), correlaton s calculated from ther returns as: ) )( ( y r y x r x r y x y x y x xy y y y x x x r r r r r r α β α β β β ρ α β α β + + = = + = + = For assets wth a smlar exposure to macro rsk (beta) and smlar magntude of asset-specfc alpha, cross-asset correlaton further smplfes to the followng expresson: 1 1 r xy β α ρ +.

25 Rsks of Common Opton Strateges Rsks to Strateges: Not all opton strateges are sutable for nvestors; certan strateges may expose nvestors to sgnfcant potental losses. We have summarzed the rsks of selected dervatve strateges. For addtonal rsk nformaton, please call your sales representatve for a copy of Characterstcs and Rsks of Standardzed Optons. We advse nvestors to consult ther tax advsors and legal counsel about the tax mplcatons of these strateges. Please also refer to opton rsk dsclosure documents. Put Sale. Investors who sell put optons wll own the underlyng stock f the stock prce falls below the strke prce of the put opton. Investors, therefore, wll be exposed to any declne n the stock prce below the strke potentally to zero, and they wll not partcpate n any stock apprecaton f the opton expres unexercsed. Call Sale. Investors who sell uncovered call optons have exposure on the upsde that s theoretcally unlmted. Call Overwrte or Buywrte. Investors who sell call optons aganst a long poston n the underlyng stock gve up any apprecaton n the stock prce above the strke prce of the call opton, and they reman exposed to the downsde of the underlyng stock n the return for the recept of the opton premum. Booster. In a sell-off, the maxmum realsed downsde potental of a double-up booster s the net premum pad. In a rally, opton losses are potentally unlmted as the nvestor s net short a call. When overlad onto a long stock poston, upsde losses are capped (as for a covered call), but downsde losses are not. Collar. Locks n the amount that can be realzed at maturty to a range defned by the put and call strke. If the collar s not costless, nvestors rsk losng 10 of the premum pad. Snce nvestors are sellng a call opton, they gve up any stock apprecaton above the strke prce of the call opton. Call Purchase. Optons are a decayng asset, and nvestors rsk losng 10 of the premum pad f the stock s below the strke prce of the call opton. Put Purchase. Optons are a decayng asset, and nvestors rsk losng 10 of the premum pad f the stock s above the strke prce of the put opton. Straddle or Strangle. The seller of a straddle or strangle s exposed to stock ncreases above the call strke and stock prce declnes below the put strke. Snce exposure on the upsde s theoretcally unlmted, nvestors who also own the stock would have lmted losses should the stock rally. Covered wrters are exposed to declnes n the long stock poston as well as any addtonal shares put to them should the stock declne below the strke prce of the put opton. Havng sold a covered call opton, the nvestor gves up all apprecaton n the stock above the strke prce of the call opton. Put Spread. The buyer of a put spread rsks losng 10 of the premum pad. The buyer of hgher rato put spread has unlmted downsde below the lower strke (down to zero), dependent on the number of lower struck puts sold. The maxmum gan s lmted to the spread between the two put strkes, when the underlyng s at the lower strke. Investors who own the underlyng stock wll have downsde protecton between the hgher strke put and the lower strke put. However, should the stock prce fall below the strke prce of the lower strke put, nvestors regan exposure to the underlyng stock, and ths exposure s multpled by the number of puts sold. Call Spread. The buyer rsks losng 10 of the premum pad. The gan s lmted to the spread between the two strke prces. The seller of a call spread rsks losng an amount equal to the spread between the two call strkes less the net premum receved. By sellng a covered call spread, the nvestor remans exposed to the downsde of the stock and gves up the spread between the two call strkes should the stock rally. Butterfly Spread. A butterfly spread conssts of two spreads establshed smultaneously. One a bull spread and the other a bear spread. The resultng poston s neutral, that s, the nvestor wll proft f the underlyng s stable. Butterfly spreads are establshed at a net debt. The maxmum proft wll occur at the mddle strke prce, the maxmum loss s the net debt. Prcng Is Illustratve Only: Prces quoted n the above trade deas are our estmate of current market levels, and are not ndcatve tradng levels. 5

26 Dsclosures Ths report s a product of the research department's Global Equty Dervatves and Delta One Strategy group. Vews expressed may dffer from the vews of the research analysts coverng stocks or sectors mentoned n ths report. Structured securtes, optons, futures and other dervatves are complex nstruments, may nvolve a hgh degree of rsk, and may be approprate nvestments only for sophstcated nvestors who are capable of understandng and assumng the rsks nvolved. Because of the mportance of tax consderatons to many opton transactons, the nvestor consderng optons should consult wth hs/her tax advsor as to how taxes affect the outcome of contemplated opton transactons. Analyst Certfcaton: The research analyst(s) denoted by an AC on the cover of ths report certfes (or, where multple research analysts are prmarly responsble for ths report, the research analyst denoted by an AC on the cover or wthn the document ndvdually certfes, wth respect to each securty or ssuer that the research analyst covers n ths research) that: (1) all of the vews expressed n ths report accurately reflect hs or her personal vews about any and all of the subject securtes or ssuers; and () no part of any of the research analyst s compensaton was, s, or wll be drectly or ndrectly related to the specfc recommendatons or vews expressed by the research analyst(s) n ths report. Important Dsclosures MSCI: The MSCI sourced nformaton s the exclusve property of Morgan Stanley Captal Internatonal Inc. (MSCI). Wthout pror wrtten permsson of MSCI, ths nformaton and any other MSCI ntellectual property may not be reproduced, redssemnated or used to create any fnancal products, ncludng any ndces. Ths nformaton s provded on an 'as s' bass. The user assumes the entre rsk of any use made of ths nformaton. MSCI, ts afflates and any thrd party nvolved n, or related to, computng or complng the nformaton hereby expressly dsclam all warrantes of orgnalty, accuracy, completeness, merchantablty or ftness for a partcular purpose wth respect to any of ths nformaton. Wthout lmtng any of the foregong, n no event shall MSCI, any of ts afflates or any thrd party nvolved n, or related to, computng or complng the nformaton have any lablty for any damages of any knd. MSCI, Morgan Stanley Captal Internatonal and the MSCI ndexes are servces marks of MSCI and ts afflates. Explanaton of Equty Research Ratngs and Analyst(s) Coverage Unverse: J.P. Morgan uses the followng ratng system: Overweght [Over the next sx to twelve months, we expect ths stock wll outperform the average total return of the stocks n the analyst s (or the analyst s team s) coverage unverse.] Neutral [Over the next sx to twelve months, we expect ths stock wll perform n lne wth the average total return of the stocks n the analyst s (or the analyst s team s) coverage unverse.] Underweght [Over the next sx to twelve months, we expect ths stock wll underperform the average total return of the stocks n the analyst s (or the analyst s team s) coverage unverse.] The analyst or analyst s team s coverage unverse s the sector and/or country shown on the cover of each publcaton. See below for the specfc stocks n the certfyng analyst(s) coverage unverse. J.P. Morgan Equty Research Ratngs Dstrbuton, as of March 31, 011 Overweght (buy) Neutral (hold) Underweght (sell) J.P. Morgan Global Equty Research Coverage 47% 4% 11% IB clents* 5 45% 33% JPMS Equty Research Coverage 43% 49% 8% IB clents* 7 6% 56% *Percentage of nvestment bankng clents n each ratng category. For purposes only of FINRA/NYSE ratngs dstrbuton rules, our Overweght ratng falls nto a buy ratng category; our Neutral ratng falls nto a hold ratng category; and our Underweght ratng falls nto a sell ratng category. Valuaton and Rsks: Please see the most recent company-specfc research report for an analyss of valuaton methodology and rsks on any securtes recommended heren. Research s avalable at or you can contact the analyst named on the front of ths note or your J.P. Morgan representatve. Analysts Compensaton: The equty research analysts responsble for the preparaton of ths report receve compensaton based upon varous factors, ncludng the qualty and accuracy of research, clent feedback, compettve factors, and overall frm revenues, whch nclude revenues from, among other busness unts, Insttutonal Equtes and Investment Bankng. Regstraton of non-us Analysts: Unless otherwse noted, the non-us analysts lsted on the front of ths report are employees of non-us afflates of JPMS, are not regstered/qualfed as research analysts under FINRA/NYSE rules, may not be assocated persons of JPMS, 6

27 and may not be subject to FINRA Rule 711 and NYSE Rule 47 restrctons on communcatons wth covered companes, publc appearances, and tradng securtes held by a research analyst account. Other Dsclosures J.P. Morgan ("JPM") s the global brand name for J.P. Morgan Securtes LLC ("JPMS") and ts afflates worldwde. J.P. Morgan Cazenove s a marketng name for the U.K. nvestment bankng busnesses and EMEA cash equtes and equty research busnesses of JPMorgan Chase & Co. and ts subsdares. Optons related research: If the nformaton contaned heren regards optons related research, such nformaton s avalable only to persons who have receved the proper opton rsk dsclosure documents. For a copy of the Opton Clearng Corporaton s Characterstcs and Rsks of Standardzed Optons, please contact your J.P. Morgan Representatve or vst the OCC s webste at Legal Enttes Dsclosures U.S.: JPMS s a member of NYSE, FINRA and SIPC. J.P. Morgan Futures Inc. s a member of the NFA. JPMorgan Chase Bank, N.A. s a member of FDIC and s authorzed and regulated n the UK by the Fnancal Servces Authorty. U.K.: J.P. Morgan Securtes Ltd. (JPMSL) s a member of the London Stock Exchange and s authorzed and regulated by the Fnancal Servces Authorty. Regstered n England & Wales No Regstered Offce 15 London Wall, London ECY 5AJ. South Afrca: J.P. Morgan Equtes Lmted s a member of the Johannesburg Securtes Exchange and s regulated by the FSB. Hong Kong: J.P. Morgan Securtes (Asa Pacfc) Lmted (CE number AAJ31) s regulated by the Hong Kong Monetary Authorty and the Securtes and Futures Commsson n Hong Kong. Korea: J.P. Morgan Securtes (Far East) Ltd, Seoul Branch, s regulated by the Korea Fnancal Supervsory Servce. Australa: J.P. Morgan Australa Lmted (ABN /AFS Lcence No: 38188) s regulated by ASIC and J.P. Morgan Securtes Australa Lmted (ABN /AFS Lcence No: 38066) s a Market Partcpant wth the ASX and regulated by ASIC. Tawan: J.P.Morgan Securtes (Tawan) Lmted s a partcpant of the Tawan Stock Exchange (company-type) and regulated by the Tawan Securtes and Futures Bureau. Inda: J.P. Morgan Inda Prvate Lmted, havng ts regstered offce at J.P. Morgan Tower, Off. C.S.T. Road, Kalna, Santacruz East, Mumba , s a member of the Natonal Stock Exchange of Inda Lmted (SEBI Regstraton Number - INB /INF /INE ) and Bombay Stock Exchange Lmted (SEBI Regstraton Number - INB /INB ) and s regulated by Securtes and Exchange Board of Inda. Thaland: JPMorgan Securtes (Thaland) Lmted s a member of the Stock Exchange of Thaland and s regulated by the Mnstry of Fnance and the Securtes and Exchange Commsson. Indonesa: PT J.P. Morgan Securtes Indonesa s a member of the Indonesa Stock Exchange and s regulated by the BAPEPAM LK. Phlppnes: J.P. Morgan Securtes Phlppnes Inc. s a member of the Phlppne Stock Exchange and s regulated by the Securtes and Exchange Commsson. Brazl: Banco J.P. Morgan S.A. s regulated by the Comssao de Valores Moblaros (CVM) and by the Central Bank of Brazl. Mexco: J.P. Morgan Casa de Bolsa, S.A. de C.V., J.P. Morgan Grupo Fnancero s a member of the Mexcan Stock Exchange and authorzed to act as a broker dealer by the Natonal Bankng and Securtes Exchange Commsson. Sngapore: Ths materal s ssued and dstrbuted n Sngapore by J.P. Morgan Securtes Sngapore Prvate Lmted (JPMSS) [MICA (P) 05/01/011 and Co. Reg. No.: R] whch s a member of the Sngapore Exchange Securtes Tradng Lmted and s regulated by the Monetary Authorty of Sngapore (MAS) and/or JPMorgan Chase Bank, N.A., Sngapore branch (JPMCB Sngapore) whch s regulated by the MAS. Malaysa: Ths materal s ssued and dstrbuted n Malaysa by JPMorgan Securtes (Malaysa) Sdn Bhd (18146-X) whch s a Partcpatng Organzaton of Bursa Malaysa Berhad and a holder of Captal Markets Servces Lcense ssued by the Securtes Commsson n Malaysa. Pakstan: J. P. Morgan Pakstan Brokng (Pvt.) Ltd s a member of the Karach Stock Exchange and regulated by the Securtes and Exchange Commsson of Pakstan. Saud Araba: J.P. Morgan Saud Araba Ltd. s authorzed by the Captal Market Authorty of the Kngdom of Saud Araba (CMA) to carry out dealng as an agent, arrangng, advsng and custody, wth respect to securtes busness under lcence number and ts regstered address s at 8th Floor, Al-Fasalyah Tower, Kng Fahad Road, P.O. Box 51907, Ryadh 11553, Kngdom of Saud Araba. Duba: JPMorgan Chase Bank, N.A., Duba Branch s regulated by the Duba Fnancal Servces Authorty (DFSA) and ts regstered address s Duba Internatonal Fnancal Centre - Buldng 3, Level 7, PO Box , Duba, UAE. Country and Regon Specfc Dsclosures U.K. and European Economc Area (EEA): Unless specfed to the contrary, ssued and approved for dstrbuton n the U.K. and the EEA by JPMSL. Investment research ssued by JPMSL has been prepared n accordance wth JPMSL's polces for managng conflcts of nterest arsng as a result of publcaton and dstrbuton of nvestment research. Many European regulators requre a frm to establsh, mplement and mantan such a polcy. Ths report has been ssued n the U.K. only to persons of a knd descrbed n Artcle 19 (5), 38, 47 and 49 of the Fnancal Servces and Markets Act 000 (Fnancal Promoton) Order 005 (all such persons beng referred to as "relevant persons"). Ths document must not be acted on or reled on by persons who are not relevant persons. Any nvestment or nvestment actvty to whch ths document relates s only avalable to relevant persons and wll be engaged n only wth relevant persons. In other EEA countres, the report has been ssued to persons regarded as professonal nvestors (or equvalent) n ther home jursdcton. Australa: Ths materal s ssued and dstrbuted by JPMSAL n Australa to wholesale clents only. JPMSAL does not ssue or dstrbute ths materal to retal clents. The recpent of ths materal must not dstrbute t to any thrd party or outsde Australa wthout the pror wrtten consent of JPMSAL. For the purposes of ths paragraph the terms wholesale clent and retal clent have the meanngs gven to them n secton 761G of the Corporatons Act 001. Germany: Ths materal s dstrbuted n Germany by J.P. Morgan Securtes Ltd., Frankfurt Branch and J.P.Morgan Chase Bank, N.A., Frankfurt Branch whch are regulated by the Bundesanstalt für Fnanzdenstlestungsaufscht. Hong Kong: The 1% ownershp dsclosure as of the prevous month end satsfes the requrements under Paragraph 16.5(a) of the Hong Kong Code of Conduct for Persons Lcensed by or Regstered wth the Securtes and Futures Commsson. (For research publshed wthn the frst ten days of the month, the dsclosure may be based on the month end data from two months pror.) J.P. Morgan Brokng (Hong Kong) Lmted s the lqudty provder/market maker for dervatve warrants, callable bull bear contracts and stock optons lsted on the Stock Exchange of Hong Kong Lmted. An updated lst can be found on HKEx webste: 7

28 Japan: There s a rsk that a loss may occur due to a change n the prce of the shares n the case of share tradng, and that a loss may occur due to the exchange rate n the case of foregn share tradng. In the case of share tradng, JPMorgan Securtes Japan Co., Ltd., wll be recevng a brokerage fee and consumpton tax (shouhze) calculated by multplyng the executed prce by the commsson rate whch was ndvdually agreed between JPMorgan Securtes Japan Co., Ltd., and the customer n advance. Fnancal Instruments Frms: JPMorgan Securtes Japan Co., Ltd., Kanto Local Fnance Bureau (knsho) No. 8 Partcpatng Assocaton / Japan Securtes Dealers Assocaton, The Fnancal Futures Assocaton of Japan. Korea: Ths report may have been edted or contrbuted to from tme to tme by afflates of J.P. Morgan Securtes (Far East) Ltd, Seoul Branch. Sngapore: JPMSS and/or ts afflates may have a holdng n any of the securtes dscussed n ths report; for securtes where the holdng s 1% or greater, the specfc holdng s dsclosed n the Important Dsclosures secton above. Inda: For prvate crculaton only, not for sale. Pakstan: For prvate crculaton only, not for sale. New Zealand: Ths materal s ssued and dstrbuted by JPMSAL n New Zealand only to persons whose prncpal busness s the nvestment of money or who, n the course of and for the purposes of ther busness, habtually nvest money. JPMSAL does not ssue or dstrbute ths materal to members of "the publc" as determned n accordance wth secton 3 of the Securtes Act The recpent of ths materal must not dstrbute t to any thrd party or outsde New Zealand wthout the pror wrtten consent of JPMSAL. Canada: The nformaton contaned heren s not, and under no crcumstances s to be construed as, a prospectus, an advertsement, a publc offerng, an offer to sell securtes descrbed heren, or solctaton of an offer to buy securtes descrbed heren, n Canada or any provnce or terrtory thereof. Any offer or sale of the securtes descrbed heren n Canada wll be made only under an exempton from the requrements to fle a prospectus wth the relevant Canadan securtes regulators and only by a dealer properly regstered under applcable securtes laws or, alternatvely, pursuant to an exempton from the dealer regstraton requrement n the relevant provnce or terrtory of Canada n whch such offer or sale s made. The nformaton contaned heren s under no crcumstances to be construed as nvestment advce n any provnce or terrtory of Canada and s not talored to the needs of the recpent. To the extent that the nformaton contaned heren references securtes of an ssuer ncorporated, formed or created under the laws of Canada or a provnce or terrtory of Canada, any trades n such securtes must be conducted through a dealer regstered n Canada. No securtes commsson or smlar regulatory authorty n Canada has revewed or n any way passed judgment upon these materals, the nformaton contaned heren or the merts of the securtes descrbed heren, and any representaton to the contrary s an offence. Duba: Ths report has been ssued to persons regarded as professonal clents as defned under the DFSA rules. General: Addtonal nformaton s avalable upon request. Informaton has been obtaned from sources beleved to be relable but JPMorgan Chase & Co. or ts afflates and/or subsdares (collectvely J.P. Morgan) do not warrant ts completeness or accuracy except wth respect to any dsclosures relatve to JPMS and/or ts afflates and the analyst s nvolvement wth the ssuer that s the subject of the research. All prcng s as of the close of market for the securtes dscussed, unless otherwse stated. Opnons and estmates consttute our judgment as of the date of ths materal and are subject to change wthout notce. Past performance s not ndcatve of future results. Ths materal s not ntended as an offer or solctaton for the purchase or sale of any fnancal nstrument. The opnons and recommendatons heren do not take nto account ndvdual clent crcumstances, objectves, or needs and are not ntended as recommendatons of partcular securtes, fnancal nstruments or strateges to partcular clents. The recpent of ths report must make ts own ndependent decsons regardng any securtes or fnancal nstruments mentoned heren. JPMS dstrbutes n the U.S. research publshed by non-u.s. afflates and accepts responsblty for ts contents. Perodc updates may be provded on companes/ndustres based on company specfc developments or announcements, market condtons or any other publcly avalable nformaton. Clents should contact analysts and execute transactons through a J.P. Morgan subsdary or afflate n ther home jursdcton unless governng law permts otherwse. Other Dsclosures last revsed January 8, 011. Copyrght 011 JPMorgan Chase & Co. All rghts reserved. Ths report or any porton hereof may not be reprnted, sold or redstrbuted wthout the wrtten consent of J.P. Morgan.#$J&098$#*P 8