全球宏观策略：如何预测美国经济增长的时间

1、GlobalResearch2 April 2019Global Macro StrategyGlobal Macro StrategyGlobal Macro StrategyGlobalHow to time the market with a US growth nowcastGlobalDoes our US macro nowcasting data offer an investment edge?Yes. We show strong evidence of both statistical and economic significance for the anticipato

2、ryinvestmentsignalembeddedinUBSEvidenceLabdata.Inotherwords,the signal(ELM)basedonthisdatamattersforinvestmentdecisions.Relevant systematic investment strategies based on the ELM signal outperform Backtest results of benchmark timing strategies for different asset classes, as well as relativevaluean

3、dcross-assetrotationstrategiesconditionalontheELMsignalacross riskyanddefensiveassetclasses,showimprovementinrisk-adjustedreturnscompared to index-tracking. The results often improve max drawdown characteristics of the reated ecmark aet. e f te et-erfrmg cro-aet rtatin tratee compared to an equally-

4、weighted S&P 500 and US Treasury portfolio, has been to hold US high-yield corporate bonds in periods of acceleration, rotate to a portfolio of defensiveandlow-volatilitystocksduringstablegrowth(nomomentum),andswitchto aportfolioofUSTreasuriesandTIPSwhentheELMsignalindicatesaslowdown.Why does growth

5、 work? Growth momentum captures asset price variation Momentum in officially-reported US private demand growth is a significant factor driving cross-asset risk-adjusted returns due primarily to different growth sensitivities amongassets.Inturn,theELMsignalanticipatessignificanteconomiccyclevariation

6、s, relyingonBigDataanalysisofreal-timeeconomicactivity.Ithascorrectlyrecognised acceleration and slowdown, as confirmed by official data, in 72% of months since January2010.TheELMsignalisthusastrongtacticalindicatorforassetreturnsover theUSgrowthcycle.Whatismore,waitingforofficialdatareleasestotrade

7、USgrowth doesnotwork(unprofitable);theevidenceshowsthatthelargestupsidetotradingUS growthwiththeELMsignalisintheearlyperiodpriortotheofficialdatareleases.ArtourDanilov HYPERLINK mailto:artour.danilov +44-20-75682000Stuart Kaiser,CFA HYPERLINK mailto:stuart.kaiser +1-212-8212069ThemosFiotakis HYPERLI

8、NK mailto:themos.fiotakis +44-20-75677215YianosKontopoulos HYPERLINK mailto:yianos.kontopoulos +44-20-75688924Ajit Agrawal, PhD HYPERLINK mailto:ajit.agrawal +1-212-7132053David Jessop HYPERLINK mailto:david.jessop +44-20-75679882Josie Gerken,PhD HYPERLINK mailto:josephine.gerken +44-20-756835602.5B

9、enchmarksBenchmark Timing Strategies2.5BenchmarksBenchmark Timing StrategiesRelativeValueStrategiesCross-AssetRotationStrategies2.01.51.00.50.0-0.5Sharpe RatioSource: Bloomberg,Haver,Datastream,UBScalculations.Note:theSharperatioiscalculatedasaratiooftheaveragetotalreturnoverthe3-monthUST-billrateto

10、its standarddeviation,bothannualised.ThebacktestsencompasstheperiodfromJanuary2010toJanuary2019atamonthlyfrequency.Inthecross-assetrotationsection, duringaccelerationweconsiderUScorporatehigh-yieldbonds(HY),theS&P500indexwithhigh-yieldbonds(CS),theS&P500index(SP),andS&P500cyclicalwith high-betastock

11、s(EC);duringstability:S&P500defensivewithlow-volatilitystocks(ED);andduringslowdown:TreasurieswithTIPSandUScorporateinvestment-grade bonds (DB). All portfolios are equally weighted. HYPERLINK /investmentresearch /investmentresearchThis report has been prepared by UBS AG London Branch. ANALYST CERTIF

12、ICATION AND REQUIRED DISCLOSURES BEGIN ONPAGE36. UBSdoesandseekstodobusinesswithcompaniescoveredinitsresearchreports.Asaresult,investorsshouldbe aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a singl

13、e factor in making their investment decision.Using the ELM signal to identify market regimesCould a measure of economic growth momentum help portfolio managers systematically enhance their market performance? A high-frequency signal, discriminating well among different economic phases, should. We ha

14、ve shown that growth momentum drives pro-cyclical as well as defensive asset markets. In HYPERLINK /shared/d2RvisrQwB2jAG3 Big Macro 09, we introduced the ELM signal, based on UBSs big data US Macro Nowcasting, which attempts to anticipate actual US growth momentum (Growth Factor). Here, we presenth

15、istorical simulations of out-of-sampletrading strategies using the ELM signal. We show strong evidence of both statistical and economic significance for this signal. In other words, the ELM signal matters.Risky-asset returns have a positive sensitivity (beta) to economic growth rate changes, while d

16、efensive assets have a negative beta. Intuitively, prices of risky assets with pro-cyclical cash flows, such as equities, are positively related to the current and expected future economic growth rate, while defensive assets with stablecashflows,suchasgovernmentbonds,arenegativelyrelatedtogrowthdue

17、to less valuable insurance premia. The ELM signal is a timely indicator of likely economicgrowthratechanges;itisreasonabletoexpecttheELMsinformational contenttosystematicallyhelpimprovetheprofitabilityandothermetricsofvarious investment portfolios.First,letstakealookatthehistoricalperformanceofmajor

18、assetclasstotal-return indices,conditionalontheELMsignal HYPERLINK l _bookmark0 (Figure2).Inthatfigure,welistassetclasses orderedbytheirbetatotheS&P500index,ameasureofbusinesscyclerisk,which also lines up well by their sensitivity to the actual, contemporaneous growth momentum (Growth Factor), the l

19、atter constructed by combining the official data counterparts underlying the ELMsignal.When it comes to anticipating monthly growth momentum, which is the markets natural tendency, ELM signals acceleration, stability or slowdown prior to the official data. The more procyclical the asset class (high

20、beta), the higher therisk- adjusted returns in periods of growth acceleration versus those in periods of slowdown,asidentifiedbytheELMsignal.Equities,pro-cyclicalcommoditiesand UShigh-yieldcorporatebondsareexamplesoftheseassettypes.And,viceversa, n prods of dntfed owdon, oer-beta aets perform betS T

21、reaure, TIPS,USinvestment-gradecorporatebondsandpreciousmetals.TheUSdollaralso exhibitsdefensivecharacteristicssimilartoUSTreasuriesinthisperiod.Itisalso notable how sensitive the international equity indices are to the strength of US economicgrowthmomentum.TheseresultssuggestthattheELMsignalcouldbe

22、 an effective and intuitive systematic market timingindicator.Note that, in the period since January 2010, while the ordering of the asset class performance was done with respect to the beta to the S&P 500 (and also secondarily to the Growth Factor, i.e., actual growth momentum), this doesnt predete

23、rminetheeffectivenessof(orlackthereof)theELMsignal,i.e.,estimated growth momentum. Indeed, as we show in Section IV, the Growth Factor is ineffective, investments-wise1.Anticipating economic growth momentum has systematic investment implications; the ELM signal is a case in point.US economic growth

24、momentum impacts the entire spectrum of assets1 Justtobeextraconservative,wealsocomparetherankingofthetotalreturnindicesinthe 10-year period prior to the availability of the ELM signal: the ordering of the assets with respect to S&P 500 and the Growth Factor is nearly the same. Please see Appendix 2

25、 for details.Global Macro Strategy 2 April 2019Figure 2: Major asset class total return statistics, conditional on the ELM signal, ranked by beta w.r.t S&P 500 IndexGlobal Macro Strategy 2 April 2019Source:Bloomberg,Haver,Datastream,UBScalculations.Note:Theperformancestatisticsarecalculatedout-of-sa

26、mpleonamonthlybasisovertheperiodfromJanuary2010toJanuary2019.Thetotalreturnsarecalculatedstartingattheendofday oftheELMsignalreleasetotheendofthelasttradingdaybeforethefollowingrelease.Therisk-adjustedreturnsarecalculatedbytakingtheratiooftheaveragetotalreturntovolatilityinannualisedterms.Greenareas

27、highlightmetrics,conditional on the ELM signal, that are higher than the corresponding unconditional metrics, whereas red areas highlight those that arelower.In what follows in this report, we will explore how utilizing the ELM signal could mproeand, n whh dmenonon: a) mpe, ong-ony bnhmarks of vario

28、usassetclasses;b)bothestablishedandnovelrelativevaluestrategies;andc) cross-asset absolute return investmentparadigms.Here is a very brief taste of the results:InallsixUS-relevantassetclassestested(equities,highyield&investmentgrade credit,treasuriesandTIPS,andcommodities)usingtheextremestatesoftheE

29、LM signal to improve on the benchmark (benchmark timing) improves Sharpe ratios and reduces the maximum drawdown from simply following the benchmark. The evidenceonwhetherbenchmark-timingwiththehelpoftheELMcanimprovethe time it takes to recover from the max drawdown is mixed but this is also affecte

30、d by less frequent trading, since most times there is no particular momentum present. Using the ELM signal to create effective relative value strategies within eachassetclassalsoproducespositiverisk-adjustedresults,oftenimprovingmax drawdown characteristics of the related benchmarkasset.Further, by

31、combining the best-performing asset classes over the ELM growth momentumcycle,thoughtfulcross-assetrotationstrategiesgeneratehighaverage returns, while outperforming on a risk-adjusted basis simple balanced equity & fixed income benchmarks throughout a period, where even the latter performed well.In

32、terestingly,weshowthatthiscouldbeachievedwithoutadverselyaffecting max drawdown or the duration-to-recovery from the maxdrawdown.ne of the bt-prformng ro-aset roaton trategealo ompared to an equa-weghted SP and US Treaury portfoohs been to hod S hgh-iecorporate bonds in periods of acceleration, rota

33、te to a portfolio of defensive and low-volatility stocks during stable growth (no momentum), and switch to a portfolioofUSTreasuries&TIPSwhentheELMsignalindicatesaslowdown.Importantly, waiting for actual releases (Growth Factor) to trade US growth is unprofitable.UsingtheELMsignalmakesallthedifferen

34、cewithinandacrossasset classes.Indeed,thereisevidencethatthebulkoftheeconomicgainsfromtrading the ELM signal originates in the immediate period right after the signal becomes availableandbeforetheactual,officialdatareleaseshitthemarket.Within traditional US asset classes, across popular relative val

35、ue strategies, and a host of cross-asset rotation programs, the ELM signal improves key investmentmetrics.Being anticipatory is key. On a systematic basis, waiting for the official data is unprofitable.What is the ELM signal, and how do we useit?The ELM (US growth momentum) signal is designed to swi

36、ftly capture high frequency phases in US economic growth (more specifically, final sales to private domestic purchasers), as proxied by four macroeconomic variables: the manufacturing ISM, month-on-month growth in nonfarm payrolls, auto sales,and retail sales, excluding autos and gasstations.TheELMu

37、sesMacroNowcastingdataearlyestimatesofthefourmacroeconomic variablesinquestion.ItfirstbecameavailableinJanuary20102.Crucially,theELM signal is available well ahead of official data releases, around one week prior to ManufacturingISM(Appendix1),whichistheearliestofthefourofficialreleases3.The ELM sig

38、nal combines equally-weighted deviations of standardised current- month ELM estimates of the macroeconomic variables from their previous-month standardisedrealisations(theofficialdata).Theresultingtimeseriesisscaledby dividing it by its standard deviation. Measures above and below +/-0.75standard de

39、viationsarelabelledasaccelerationandslowdownsignals,respectively,while everything in between is stable growth.4 As such, the ELM signal attempts to captureperiodswhenUSeconomicgrowthisincreasingordeclining(momentum), but is agnostic to the growth rate level and its marketsexpectations.The ELM signal

40、 attempts to identify positive or negative growth momentum but is agnostic to the growth level or market expectations of thatlevel.Figure 3: ELM signals have correctly identified the strength in official data in 72% of months since 2010Figure 4: ELM and official data growth momentum distributions ex

41、hibit close signal category correspondence32.25RealisedRealised0y = 0.82x - 0.03 R = 0.62-2.25-3-3-2.25-1.5-0.7500.751.52.253PredictedSource:UBSEvidenceLab,Bloomberg.ThesampleincludesUSMacroNowcasting and corresponding official data for reference months from January 2010 to December 2018.Source: UBS

42、 Evidence lab, Bloomberg. The sample includes US Macro Nowcasting and corresponding official data for reference months from January 2010 to December 2018.2 Most of the ELM time series start in 2010 (Manufacturing ISM and non-farm payrolls in January2010,andretailsalesinMay2010)andthatofautosalesstar

43、tsinFebruary2012. WhereELMdataisunavailable,atthestartofthesample,itissubstitutedwithofficialdata. Thetrulyout-of-sampletimeseries,asalreadypublishedbyUBS,begininOctober2015and thedatapriortothisisreconstructedaccordingtothelatestmethodologiescurrentlyinuse. 3 Appendix 1 provides details and the com

44、ponents of the US macro nowcasting used. We excludedprivateconstructiondataasitdisproportionatelydelayedthesignalavailability.4 In order to standardise the data, we compute the means and standard deviations, usingexponentially-weighted moving average models (EWMA), which allocate a 5% weight to curr

45、ent-monthdata.WeinitiatetheEWMAmodelsinJanuary1992,usingtheofficialdata thisistheearliestdateavailableforAdjustedRetailSales.TheUSMacroNowcastingdataof themacroeconomicvariablesstartsinJanuary2010.WeusetheofficialdataEWMAmodels as a proxy of its historical statistical moments and incorporate the now

46、cast data as it becomes available.How does the signal compare to historical realizations? To test the ELM signals historical performance in classifying US growth momentum, we compare it to signals derived from a perfect foresight momentum measure (the Growth Factor), which is constructed in the same

47、 manner, but using official data in place of ELM estimates. The signal has an overall hit rate of 0.7 HYPERLINK l _bookmark1 (Figure 3).SinceJanuary2010,whentheUSMacroNowcastingdatafirstbecameavailable,it hascorrectlyidentified18of26predictedaccelerations,17of24slowdownsand 42 of 58 months of stabil

48、ity. Thus, the hit rate for all three phases has been the same,0.7,indicatingconsistency.Inonlytwocasesdidthesignalpointtoalarge change in growth only for the official data to indicate a large change in the exact opposite direction (Figure 4). Namely, the ELM signal identified acceleration in Januar

49、y 2014 and slowdown in January 2017, while the official data showed the reereowdon and aceeraton, repete.Thesignalalsoexhibitsclose-to-actualpredictionrates:26predictedto27realised acceleration, 24 to 26 slowdown and 58 to 55 stability months (which is a good indication,inthatthisisnotanarrowexercis

50、ewheredifficultpredictionsaremade only rarely). Related to this, the signal is also characterised by high true positive (conditionalonaccelerationrealized,havingpredictedacceleration)andnegative rates(conditionalondecelerationrealized,havingpredicteddeceleration),bothof 0.7,respectively.Inaddition,c

51、onditionalonstabilitybeingrealised,thesignalhas predicted stability at the rate of 0.8.The ELM signal is potentially effective in selecting the right markets in which to investinahigh-frequency,monthlysetting.Toillustratethisconcept,letsvisualize, in two steps, the core of the results presented in H

52、YPERLINK l _bookmark0 Figure 2, utilizing two more visuals.First, the assets in Figure 2 are differentially exposed to the S&P 500 index, the accepted market (benchmark) proxy to the business cycle; that differentiation is well-mimicked by their exposure to US growth momentum (Growth Factor5) in HYP

53、ERLINK l _bookmark2 Figure5.Sothelatterpresumablycapturesnews(innovations)tooneofthemost relevanteconomicvariablesforthemarkets.Second,theseinnovationsmatterin aneconomicsense.Higherequity-betaassetstendtoproducehigheraveragerisk- adjustedreturns6(RAR)inperiodsofacceleration,asindicatedbytheELMsigna

54、l, and lower RARs during slowdown HYPERLINK l _bookmark3 (Figure 6), while there is no relationship between the betas and RARs in periods of stability (not shown here); and, vice versa for the lower or negative-betaassets7.Section III presents backtest results of investment strategies informed by th

55、is preliminary analysis.The ELM signal features high and consistent hit ratios with respect to actual, high frequency growth phases.5 Inassetreturnbetacalculations,withrespecttotheGrowthFactor,presentedin HYPERLINK l _bookmark0 Figure2, the Growth Factor standard deviation is scaled to equal the vol

56、atility of the asset under consideration over the sampleperiod.6 Theaveragerisk-adjustedreturn(RAR)iscalculatedasaratiooftheaveragetotalreturnto its standard deviation, bothannualised.7 As part of the background work to this report, we generated a broader and more detailed setofhistoricalperformance

57、resultswithinindividualassetclasses,conditionalontheELM signal.So,forexample,wegeneratedresultsforallS&P500broadsectorindices,atleast30 internationalequityindices,differentconstantmaturityUSgovernmentbondindices,credit marketcategoriesaswellas14individualcommodityindices.Allareavailableonrequest.Fig

58、ure 5: US growth momentum closely related to priced cyclical risk factors in different assetsFigure6:Cyclicalriskfactorsexplainassetperformance over the US momentumcycleBeta w.r.t. S&P 500 Beta w.r.t. growth factorDecliningBeta w.r.t. S&P 500 Beta w.r.t. growth factorDecliningRARIncreasing RARy = 0.

59、28x + 0.52 R = 0.76y = 0.10 x + 0.00 R = 0.95-3.0-2.0-1.00.01.02.03.00.9Betaw.r.t.Betaw.r.t.S&P500BetaBetaw.r.t.S&P5000.7Beta w.r.t. growth factor0.5Beta w.r.t. growth factor0.30.0-0.4-0.3-0.2-0.10.00.00.1-0.1-0.5Beta w.r.t. growth factor-0.5RAR difference: Acceln vs Slown-0.3Source: Bloomb

60、erg, Haver Analytics, Datastream,UBScalculationsSource: Bloomberg, Haver Analytics, Datastream, UBScalculationsBox 1: Back-test specification detailsWeutilizetheELMsignaltoimproveonthreebroadinvestmentstrategies.First,forsomeofthecharacteristicassetclasses we attempt to improve on the asset class be